Satellite orbit computation methods

NASA Technical Reports Server (NTRS)

1977-01-01

Mathematical and algorithmical techniques for solution of problems in satellite dynamics were developed, along with solutions to satellite orbit motion. Dynamical analysis of shuttle on-orbit operations were conducted. Computer software routines for use in shuttle mission planning were developed and analyzed, while mathematical models of atmospheric density were formulated.

NASA GPM GV Science Implementation

NASA Technical Reports Server (NTRS)

Petersen, W. A.

2009-01-01

Pre-launch algorithm development & post-launch product evaluation: The GPM GV paradigm moves beyond traditional direct validation/comparison activities by incorporating improved algorithm physics & model applications (end-to-end validation) in the validation process. Three approaches: 1) National Network (surface): Operational networks to identify and resolve first order discrepancies (e.g., bias) between satellite and ground-based precipitation estimates. 2) Physical Process (vertical column): Cloud system and microphysical studies geared toward testing and refinement of physically-based retrieval algorithms. 3) Integrated (4-dimensional): Integration of satellite precipitation products into coupled prediction models to evaluate strengths/limitations of satellite precipitation producers.

Advances in multi-sensor data fusion: algorithms and applications.

PubMed

Dong, Jiang; Zhuang, Dafang; Huang, Yaohuan; Fu, Jingying

2009-01-01

With the development of satellite and remote sensing techniques, more and more image data from airborne/satellite sensors have become available. Multi-sensor image fusion seeks to combine information from different images to obtain more inferences than can be derived from a single sensor. In image-based application fields, image fusion has emerged as a promising research area since the end of the last century. The paper presents an overview of recent advances in multi-sensor satellite image fusion. Firstly, the most popular existing fusion algorithms are introduced, with emphasis on their recent improvements. Advances in main applications fields in remote sensing, including object identification, classification, change detection and maneuvering targets tracking, are described. Both advantages and limitations of those applications are then discussed. Recommendations are addressed, including: (1) Improvements of fusion algorithms; (2) Development of "algorithm fusion" methods; (3) Establishment of an automatic quality assessment scheme.

Early Results from the Global Precipitation Measurement (GPM) Mission in Japan

NASA Astrophysics Data System (ADS)

Kachi, Misako; Kubota, Takuji; Masaki, Takeshi; Kaneko, Yuki; Kanemaru, Kaya; Oki, Riko; Iguchi, Toshio; Nakamura, Kenji; Takayabu, Yukari N.

2015-04-01

The Global Precipitation Measurement (GPM) mission is an international collaboration to achieve highly accurate and highly frequent global precipitation observations. The GPM mission consists of the GPM Core Observatory jointly developed by U.S. and Japan and Constellation Satellites that carry microwave radiometers and provided by the GPM partner agencies. The Dual-frequency Precipitation Radar (DPR) was developed by the Japan Aerospace Exploration Agency (JAXA) and the National Institute of Information and Communications Technology (NICT), and installed on the GPM Core Observatory. The GPM Core Observatory chooses a non-sun-synchronous orbit to carry on diurnal cycle observations of rainfall from the Tropical Rainfall Measuring Mission (TRMM) satellite and was successfully launched at 3:37 a.m. on February 28, 2014 (JST), while the Constellation Satellites, including JAXA's Global Change Observation Mission (GCOM) - Water (GCOM-W1) or "SHIZUKU," are launched by each partner agency sometime around 2014 and contribute to expand observation coverage and increase observation frequency JAXA develops the DPR Level 1 algorithm, and the NASA-JAXA Joint Algorithm Team develops the DPR Level 2 and DPR-GMI combined Level2 algorithms. JAXA also develops the Global Rainfall Map (GPM-GSMaP) algorithm, which is a latest version of the Global Satellite Mapping of Precipitation (GSMaP), as national product to distribute hourly and 0.1-degree horizontal resolution rainfall map. Major improvements in the GPM-GSMaP algorithm is; 1) improvements in microwave imager algorithm based on AMSR2 precipitation standard algorithm, including new land algorithm, new coast detection scheme; 2) Development of orographic rainfall correction method for warm rainfall in coastal area (Taniguchi et al., 2012); 3) Update of database, including rainfall detection over land and land surface emission database; 4) Development of microwave sounder algorithm over land (Kida et al., 2012); and 5) Development of gauge-calibrated GSMaP algorithm (Ushio et al., 2013). In addition to those improvements in the algorithms number of passive microwave imagers and/or sounders used in the GPM-GSMaP was increased compared to the previous version. After the early calibration and validation of the products and evaluation that all products achieved the release criteria, all GPM standard products and the GPM-GSMaP product has been released to the public since September 2014. The GPM products can be downloaded via the internet through the JAXA G-Portal (https://www.gportal.jaxa.jp).

Dissolved Organic Carbon along the Louisiana coast from MODIS and MERIS satellite data

NASA Astrophysics Data System (ADS)

Chaichi Tehrani, N.; D'Sa, E. J.

2012-12-01

Dissolved organic carbon (DOC) plays a critical role in the coastal and ocean carbon cycle. Hence, it is important to monitor and investigate its the distribution and fate in coastal waters. Since DOC cannot be measured directly through satellite remote sensors, chromophoric dissolved organic matter (CDOM) as an optically active fraction of DOC can be used as an alternative proxy to trace DOC concentrations. Here, satellite ocean color data from MODIS, MERIS, and field measurements of CDOM and DOC were used to develop and assess CDOM and DOC ocean color algorithms for coastal waters. To develop a CDOM retrieval algorithm, empirical relationships between CDOM absorption coefficient at 412 nm (aCDOM(412)) and reflectance ratios Rrs(488)/Rrs(555) for MODIS and Rrs(510)/Rrs(560) for MERIS were established. The performance of two CDOM empirical algorithms were evaluated for retrieval of (aCDOM(412)) from MODIS and MERIS in the northern Gulf of Mexico. Further, empirical algorithms were developed to estimate DOC concentration using the relationship between in situ aCDOM(412) and DOC, as well as using the newly developed CDOM empirical algorithms. Accordingly, our results revealed that DOC concentration was strongly correlated to aCDOM (412) for summer and spring-winter periods (r2 = 0.9 for both periods). Then, using the aCDOM(412)-Rrs and the aCDOM(412)-DOC relationships derived from field measurements, a relationship between DOC-Rrs was established for MODIS and MERIS data. The DOC empirical algorithms performed well as indicated by match-up comparisons between satellite estimates and field data (R2=0.52 and 0.58 for MODIS and MERIS for summer period, respectively). These algorithms were then used to examine DOC distribution along the Louisiana coast.

Retrieval of volcanic ash height from satellite-based infrared measurements

NASA Astrophysics Data System (ADS)

Zhu, Lin; Li, Jun; Zhao, Yingying; Gong, He; Li, Wenjie

2017-05-01

A new algorithm for retrieving volcanic ash cloud height from satellite-based measurements is presented. This algorithm, which was developed in preparation for China's next-generation meteorological satellite (FY-4), is based on volcanic ash microphysical property simulation and statistical optimal estimation theory. The MSG satellite's main payload, a 12-channel Spinning Enhanced Visible and Infrared Imager, was used as proxy data to test this new algorithm. A series of eruptions of Iceland's Eyjafjallajökull volcano during April to May 2010 and the Puyehue-Cordón Caulle volcanic complex eruption in the Chilean Andes on 16 June 2011 were selected as two typical cases for evaluating the algorithm under various meteorological backgrounds. Independent volcanic ash simulation training samples and satellite-based Cloud-Aerosol Lidar with Orthogonal Polarization data were used as validation data. It is demonstrated that the statistically based volcanic ash height algorithm is able to rapidly retrieve volcanic ash heights, globally. The retrieved ash heights show comparable accuracy with both independent training data and the lidar measurements, which is consistent with previous studies. However, under complicated background, with multilayers in vertical scale, underlying stratus clouds tend to have detrimental effects on the final retrieval accuracy. This is an unresolved problem, like many other previously published methods using passive satellite sensors. Compared with previous studies, the FY-4 ash height algorithm is independent of simultaneous atmospheric profiles, providing a flexible way to estimate volcanic ash height using passive satellite infrared measurements.

Comparison of satellite reflectance algorithms for estimating ...

EPA Pesticide Factsheets

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

Development of an Algorithm for Satellite Remote Sensing of Sea and Lake Ice

NASA Astrophysics Data System (ADS)

Dorofy, Peter T.

Satellite remote sensing of snow and ice has a long history. The traditional method for many snow and ice detection algorithms has been the use of the Normalized Difference Snow Index (NDSI). This manuscript is composed of two parts. Chapter 1, Development of a Mid-Infrared Sea and Lake Ice Index (MISI) using the GOES Imager, discusses the desirability, development, and implementation of alternative index for an ice detection algorithm, application of the algorithm to the detection of lake ice, and qualitative validation against other ice mapping products; such as, the Ice Mapping System (IMS). Chapter 2, Application of Dynamic Threshold in a Lake Ice Detection Algorithm, continues with a discussion of the development of a method that considers the variable viewing and illumination geometry of observations throughout the day. The method is an alternative to Bidirectional Reflectance Distribution Function (BRDF) models. Evaluation of the performance of the algorithm is introduced by aggregating classified pixels within geometrical boundaries designated by IMS and obtaining sensitivity and specificity statistical measures.

Research on optimal path planning algorithm of task-oriented optical remote sensing satellites

NASA Astrophysics Data System (ADS)

Liu, Yunhe; Xu, Shengli; Liu, Fengjing; Yuan, Jingpeng

2015-08-01

GEO task-oriented optical remote sensing satellite, is very suitable for long-term continuous monitoring and quick access to imaging. With the development of high resolution optical payload technology and satellite attitude control technology, GEO optical remote sensing satellites will become an important developing trend for aerospace remote sensing satellite in the near future. In the paper, we focused on GEO optical remote sensing satellite plane array stare imaging characteristics and real-time leading mission of earth observation mode, targeted on satisfying needs of the user with the minimum cost of maneuver, and put forward the optimal path planning algorithm centered on transformation from geographic coordinate space to Field of plane, and finally reduced the burden of the control system. In this algorithm, bounded irregular closed area on the ground would be transformed based on coordinate transformation relations in to the reference plane for field of the satellite payload, and then using the branch and bound method to search for feasible solutions, cutting off the non-feasible solution in the solution space based on pruning strategy; and finally trimming some suboptimal feasible solutions based on the optimization index until a feasible solution for the global optimum. Simulation and visualization presentation software testing results verified the feasibility and effectiveness of the strategy.

Satellite Doppler data processing using a microcomputer

NASA Technical Reports Server (NTRS)

Schmid, P. E.; Lynn, J. J.

1977-01-01

A microcomputer which was developed to compute ground radio beacon position locations using satellite measurements of Doppler frequency shift is described. Both the computational algorithms and the microcomputer hardware incorporating these algorithms were discussed. Results are presented where the microcomputer in conjunction with the NIMBUS-6 random access measurement system provides real time calculation of beacon latitude and longitude.

Comparison of satellite reflectance algorithms for estimating chlorophyll-a in a temperate reservoir using coincident hyperspectral aircraft imagery and dense coincident surface observations

EPA Science Inventory

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 si...

SPHERES Facility

NASA Technical Reports Server (NTRS)

Martinez, Andres; Benavides, Jose Victor; Ormsby, Steve L.; GuarnerosLuna, Ali

2014-01-01

Synchronized Position Hold, Engage, Reorient, Experimental Satellites (SPHERES) are bowling-ball sized satellites that provide a test bed for development and research into multi-body formation flying, multi-spacecraft control algorithms, and free-flying physical and material science investigations. Up to three self-contained free-flying satellites can fly within the cabin of the International Space Station (ISS), performing flight formations, testing of control algorithms or as a platform for investigations requiring this unique free-flying test environment. Each satellite is a self-contained unit with power, propulsion, computers, navigation equipment, and provides physical and electrical connections (via standardized expansion ports) for Principal Investigator (PI) provided hardware and sensors.

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

NASA Astrophysics Data System (ADS)

Weaver, Oesa A.

In the last two decades, small satellites have opened up the use of space to groups other than governments and large corporations, allowing for increased participation and experimentation. This democratization of space was primarily enabled by two factors: improved technology and reduced launch costs. Improved technology allowed the miniaturization of components and reduced overall cost meaning many of the capabilities of larger satellites could be replicated at a fraction of the cost. In addition, new launcher systems that could host many small satellites as ride-shares on manifested vehicles lowered launch costs and simplified the process of getting a satellite into orbit. The potential of these smaller satellites to replace or augment existing systems has led to a flood of potential satellite and mission concepts, often with little rigorous study of whether the proposed satellite or mission is achievable or necessary. This work proposes an analytical framework to aid system designers in evaluating the ability of an existing concept or small satellite to perform a particular imaging mission, either replacing or augmenting existing capabilities. This framework was developed and then refined by application to the problem of using small satellites to perform a wide area search mission -- a mission not possible with existing imaging satellites, but one that would add to current capabilities. Requirements for a wide area search mission were developed, along with a list of factors that would affect image quality and system performance. Two existing small satellite concepts were evaluated for use by examining image quality from the systems, selecting an algorithm to perform the search function automatically, and then assessing mission feasibility by applying the algorithm to simulated imagery. Finally, a notional constellation design was developed to assess the number of satellites required to perform the mission. It was found that a constellation of 480 CubeSats producing 4 m spatial resolution panchromatic imagery and employing an on-board processing algorithm would be sufficient to perform a wide area search mission.

A study of autonomous satellite navigation methods using the global positioning satellite system

NASA Technical Reports Server (NTRS)

Tapley, B. D.

1980-01-01

Special orbit determination algorithms were developed to accommodate the size and speed limitations of on-board computer systems of the NAVSTAR Global Positioning System. The algorithms use square root sequential filtering methods. A new method for the time update of the square root covariance matrix was also developed. In addition, the time update method was compared with another square root convariance propagation method to determine relative performance characteristics. Comparisions were based on the results of computer simulations of the LANDSAT-D satellite processing pseudo range and pseudo range-rate measurements from the phase one GPS. A summary of the comparison results is presented.

Smoothing-Based Relative Navigation and Coded Aperture Imaging

NASA Technical Reports Server (NTRS)

Saenz-Otero, Alvar; Liebe, Carl Christian; Hunter, Roger C.; Baker, Christopher

2017-01-01

This project will develop an efficient smoothing software for incremental estimation of the relative poses and velocities between multiple, small spacecraft in a formation, and a small, long range depth sensor based on coded aperture imaging that is capable of identifying other spacecraft in the formation. The smoothing algorithm will obtain the maximum a posteriori estimate of the relative poses between the spacecraft by using all available sensor information in the spacecraft formation.This algorithm will be portable between different satellite platforms that possess different sensor suites and computational capabilities, and will be adaptable in the case that one or more satellites in the formation become inoperable. It will obtain a solution that will approach an exact solution, as opposed to one with linearization approximation that is typical of filtering algorithms. Thus, the algorithms developed and demonstrated as part of this program will enhance the applicability of small spacecraft to multi-platform operations, such as precisely aligned constellations and fractionated satellite systems.

Engineering calculations for solving the orbital allotment problem

NASA Technical Reports Server (NTRS)

Reilly, C.; Walton, E. K.; Mount-Campbell, C.; Caldecott, R.; Aebker, E.; Mata, F.

1988-01-01

Four approaches for calculating downlink interferences for shaped-beam antennas are described. An investigation of alternative mixed-integer programming models for satellite synthesis is summarized. Plans for coordinating the various programs developed under this grant are outlined. Two procedures for ordering satellites to initialize the k-permutation algorithm are proposed. Results are presented for the k-permutation algorithms. Feasible solutions are found for 5 of the 6 problems considered. Finally, it is demonstrated that the k-permutation algorithm can be used to solve arc allotment problems.

Rainfall estimation for real time flood monitoring using geostationary meteorological satellite data

NASA Astrophysics Data System (ADS)

Veerakachen, Watcharee; Raksapatcharawong, Mongkol

2015-09-01

Rainfall estimation by geostationary meteorological satellite data provides good spatial and temporal resolutions. This is advantageous for real time flood monitoring and warning systems. However, a rainfall estimation algorithm developed in one region needs to be adjusted for another climatic region. This work proposes computationally-efficient rainfall estimation algorithms based on an Infrared Threshold Rainfall (ITR) method calibrated with regional ground truth. Hourly rain gauge data collected from 70 stations around the Chao-Phraya river basin were used for calibration and validation of the algorithms. The algorithm inputs were derived from FY-2E satellite observations consisting of infrared and water vapor imagery. The results were compared with the Global Satellite Mapping of Precipitation (GSMaP) near real time product (GSMaP_NRT) using the probability of detection (POD), root mean square error (RMSE) and linear correlation coefficient (CC) as performance indices. Comparison with the GSMaP_NRT product for real time monitoring purpose shows that hourly rain estimates from the proposed algorithm with the error adjustment technique (ITR_EA) offers higher POD and approximately the same RMSE and CC with less data latency.

Incorporation of quality updates for JPSS CGS Products

NASA Astrophysics Data System (ADS)

Cochran, S.; Grant, K. D.; Ibrahim, W.; Brueske, K. F.; Smit, P.

2016-12-01

NOAA's next-generation environmental satellite, the Joint Polar Satellite System (JPSS) replaces the current Polar-orbiting Operational Environmental Satellites (POES). JPSS satellites carry sensors which collect meteorological, oceanographic, climatological, and solar-geophysical observations of the earth, atmosphere, and space. The first JPSS satellite was launched in 2011 and is currently NOAA's primary operational polar satellite. The JPSS ground system is the Common Ground System (CGS), and provides command, control, and communications (C3) and data processing (DP). A multi-mission system, CGS provides combinations of C3/DP for numerous NASA, NOAA, DoD, and international missions. In preparation for the next JPSS satellite, CGS improved its multi-mission capabilities to enhance mission operations for larger constellations of earth observing satellites with the added benefit of streamlining mission operations for other NOAA missions. This paper will discuss both the theoretical basis and the actual practices used to date to identify, test and incorporate algorithm updates into the CGS processing baseline. To provide a basis for this support, Raytheon developed a theoretical analysis framework, and the application of derived engineering processes, for the maintenance of consistency and integrity of remote sensing operational algorithm outputs. The framework is an abstraction of the operationalization of the science-grade algorithm (Sci2Ops) process used throughout the JPSS program. By combining software and systems engineering controls, manufacturing disciplines to detect and reduce defects, and a standard process to control analysis, an environment to maintain operational algorithm maturity is achieved. Results of the use of this approach to implement algorithm changes into operations will also be detailed.

Methods and Tools for Product Quality Maintenance in JPSS CGS

NASA Astrophysics Data System (ADS)

Cochran, S.; Smit, P.; Grant, K. D.; Jamilkowski, M. L.

2015-12-01

NOAA's next-generation environmental satellite, the Joint Polar Satellite System (JPSS) replaces the current Polar-orbiting Operational Environmental Satellites (POES). JPSS satellites carry sensors which collect meteorological, oceanographic, climatological, and solar-geophysical observations of the earth, atmosphere, and space. The first JPSS satellite was launched in 2011 and is currently NOAA's primary operational polar satellite. The JPSS ground system is the Common Ground System (CGS), and provides command, control, and communications (C3) and data processing (DP). A multi-mission system, CGS provides combinations of C3/DP for numerous NASA, NOAA, DoD, and international missions. In preparation for the next JPSS satellite, CGS improved its multi-mission capabilities to enhance mission operations for larger constellations of earth observing satellites with the added benefit of streamlining mission operations for other NOAA missions. This paper will discuss both the theoretical basis and the actual practices used to date to identify, test and incorporate algorithm updates into the CGS processing baseline. To provide a basis for this support, Raytheon developed a theoretical analysis framework, and the application of derived engineering processes, for the maintenance of consistency and integrity of remote sensing operational algorithm outputs. The framework is an abstraction of the operationalization of the science-grade algorithm (Sci2Ops) process used throughout the JPSS program. By combining software and systems engineering controls, manufacturing disciplines to detect and reduce defects, and a standard process to control analysis, an environment to maintain operational algorithm maturity is achieved. Results of the use of this approach to implement algorithm changes into operations will also be detailed.

Variational and symplectic integrators for satellite relative orbit propagation including drag

NASA Astrophysics Data System (ADS)

Palacios, Leonel; Gurfil, Pini

2018-04-01

Orbit propagation algorithms for satellite relative motion relying on Runge-Kutta integrators are non-symplectic—a situation that leads to incorrect global behavior and degraded accuracy. Thus, attempts have been made to apply symplectic methods to integrate satellite relative motion. However, so far all these symplectic propagation schemes have not taken into account the effect of atmospheric drag. In this paper, drag-generalized symplectic and variational algorithms for satellite relative orbit propagation are developed in different reference frames, and numerical simulations with and without the effect of atmospheric drag are presented. It is also shown that high-order versions of the newly-developed variational and symplectic propagators are more accurate and are significantly faster than Runge-Kutta-based integrators, even in the presence of atmospheric drag.

Developing NOAA's Climate Data Records From AVHRR and Other Data

NASA Astrophysics Data System (ADS)

Privette, J. L.; Bates, J. J.; Kearns, E. J.

2010-12-01

As part of the provisional NOAA Climate Service, NOAA is providing leadership in the development of authoritative, measurement-based information on climate change and variability. NOAA’s National Climatic Data Center (NCDC) recently initiated a satellite Climate Data Record Program (CDRP) to provide sustained and objective climate information derived from meteorological satellite data that NOAA has collected over the past 30+ years - particularly from its Polar Orbiting Environmental Satellites (POES) program. These are the longest sustained global measurement records in the world and represent billions of dollars of investment. NOAA is now applying advanced analysis methods -- which have improved remarkably over the last decade -- to the POES AVHRR and other instrument data. Data from other satellite programs, including NASA and international research programs and the Defense Meteorological Satellite Program (DMSP), are also being used. This process will unravel the underlying climate trend and variability information and return new value from the records. In parallel, NCDC will extend these records by applying the same methods to present-day and future satellite measurements, including the Joint Polar Satellite System (JPSS) and Jason-3. In this presentation, we will describe the AVHRR-related algorithm development activities that CDRP recently selected and funded through open competitions. We will particularly discuss some of the technical challenges related to adapting and using AVHRR algorithms with the VIIRS data that should become available with the launch of the NPOESS Preparatory Project (NPP) satellite in early 2012. We will also describe IT system development activities that will provide data processing and reprocessing, storage and management. We will also outline the maturing Program framework, including the strategies for coding and development standards, community reviews, independent program oversight, and research-to-operations algorithm migration and execution. Timeline of NOAA's polar orbiters that carried AVHRR. NOAA's approach to flying the same or similar instruments sequentially is well-suited to CDR development.

Seasonal to Decadal-Scale Variability in Satellite Ocean Color and Sea Surface Temperature for the California Current System

NASA Technical Reports Server (NTRS)

Mitchell, B. Greg; Kahru, Mati; Marra, John (Technical Monitor)

2002-01-01

Support for this project was used to develop satellite ocean color and temperature indices (SOCTI) for the California Current System (CCS) using the historic record of CZCS West Coast Time Series (WCTS), OCTS, WiFS and AVHRR SST. The ocean color satellite data have been evaluated in relation to CalCOFI data sets for chlorophyll (CZCS) and ocean spectral reflectance and chlorophyll OCTS and SeaWiFS. New algorithms for the three missions have been implemented based on in-water algorithm data sets, or in the case of CZCS, by comparing retrieved pigments with ship-based observations. New algorithms for absorption coefficients, diffuse attenuation coefficients and primary production have also been evaluated. Satellite retrievals are being evaluated based on our large data set of pigments and optics from CalCOFI.

VIIRS validation and algorithm development efforts in coastal and inland Waters

NASA Astrophysics Data System (ADS)

Stengel, E.; Ondrusek, M.

2016-02-01

Accurate satellite ocean color measurements in coastal and inland waters are more challenging than open-ocean measurements. Complex water and atmospheric conditions can limit the utilization of remote sensing data in coastal waters where it is most needed. The Coastal Optical Characterization Experiment (COCE) is an ongoing project at NOAA/NESDIS/STAR Satellite Oceanography and Climatology Division. The primary goals of COCE are satellite ocean color validation and application development. Currently, this effort concentrates on the initialization and validation of the Joint Polar Satellite System (JPSS) VIIRS sensor using a Satlantic HyperPro II radiometer as a validation tool. A report on VIIRS performance in coastal waters will be given by presenting comparisons between in situ ground truth measurements and VIIRS retrievals made in the Chesapeake Bay, and inland waters of the Gulf of Mexico and Puerto Rico. The COCE application development effort focuses on developing new ocean color satellite remote sensing tools for monitoring relevant coastal ocean parameters. A new VIIRS total suspended matter algorithm will be presented for the Chesapeake Bay. These activities improve the utility of ocean color satellite data in monitoring and analyzing coastal and oceanic processes. Progress on these activities will be reported.

Optimizing the Attitude Control of Small Satellite Constellations for Rapid Response Imaging

NASA Astrophysics Data System (ADS)

Nag, S.; Li, A.

2016-12-01

Distributed Space Missions (DSMs) such as formation flight and constellations, are being recognized as important solutions to increase measurement samples over space and time. Given the increasingly accurate attitude control systems emerging in the commercial market, small spacecraft now have the ability to slew and point within few minutes of notice. In spite of hardware development in CubeSats at the payload (e.g. NASA InVEST) and subsystems (e.g. Blue Canyon Technologies), software development for tradespace analysis in constellation design (e.g. Goddard's TAT-C), planning and scheduling development in single spacecraft (e.g. GEO-CAPE) and aerial flight path optimizations for UAVs (e.g. NASA Sensor Web), there is a gap in open-source, open-access software tools for planning and scheduling distributed satellite operations in terms of pointing and observing targets. This paper will demonstrate results from a tool being developed for scheduling pointing operations of narrow field-of-view (FOV) sensors over mission lifetime to maximize metrics such as global coverage and revisit statistics. Past research has shown the need for at least fourteen satellites to cover the Earth globally everyday using a LandSat-like sensor. Increasing the FOV three times reduces the need to four satellites, however adds image distortion and BRDF complexities to the observed reflectance. If narrow FOV sensors on a small satellite constellation were commanded using robust algorithms to slew their sensor dynamically, they would be able to coordinately cover the global landmass much faster without compensating for spatial resolution or BRDF effects. Our algorithm to optimize constellation satellite pointing is based on a dynamic programming approach under the constraints of orbital mechanics and existing attitude control systems for small satellites. As a case study for our algorithm, we minimize the time required to cover the 17000 Landsat images with maximum signal to noise ratio fall-off and minimum image distortion among the satellites, using Landsat's specifications. Attitude-specific constraints such as power consumption, response time, and stability were factored into the optimality computations. The algorithm can integrate cloud cover predictions, specific ground and air assets and angular constraints.

Amazon Forest Structure from IKONOS Satellite Data and the Automated Characterization of Forest Canopy Properties

Treesearch

Michael Palace; Michael Keller; Gregory P. Asner; Stephen Hagen; Bobby Braswell

2008-01-01

We developed an automated tree crown analysis algorithm using 1-m panchromatic IKONOS satellite images to examine forest canopy structure in the Brazilian Amazon. The algorithm was calibrated on the landscape level with tree geometry and forest stand data at the Fazenda Cauaxi (3.75◦ S, 48.37◦ W) in the eastern Amazon, and then compared with forest...

The combined control algorithm for large-angle maneuver of HITSAT-1 small satellite

NASA Astrophysics Data System (ADS)

Zhaowei, Sun; Yunhai, Geng; Guodong, Xu; Ping, He

2004-04-01

The HITSAT-1 is the first small satellite developed by Harbin Institute of Technology (HIT) whose mission objective is to test several pivotal techniques. The large angle maneuver control is one of the pivotal techniques of HITSAT-1 and the instantaneous Eulerian axis control algorithm (IEACA) has been applied. Because of using the reaction wheels and magnetorquer as the control actuators, the combined control algorithm has been adopted during the large-angle maneuver course. The computer simulation based on the MATRIX×6.0 software has finished and the results indicated that the combined control algorithm reduced the reaction wheel speeds obviously, and the IEACA algorithm has the advantages of simplicity and efficiency.

Development of a fire detection algorithm for the COMS (Communication Ocean and Meteorological Satellite)

NASA Astrophysics Data System (ADS)

Kim, Goo; Kim, Dae Sun; Lee, Yang-Won

2013-10-01

The forest fires do much damage to our life in ecological and economic aspects. South Korea is probably more liable to suffer from the forest fire because mountain area occupies more than half of land in South Korea. They have recently launched the COMS(Communication Ocean and Meteorological Satellite) which is a geostationary satellite. In this paper, we developed forest fire detection algorithm using COMS data. Generally, forest fire detection algorithm uses characteristics of 4 and 11 micrometer brightness temperature. Our algorithm additionally uses LST(Land Surface Temperature). We confirmed the result of our fire detection algorithm using statistical data of Korea Forest Service and ASTER(Advanced Spaceborne Thermal Emission and Reflection Radiometer) images. We used the data in South Korea On April 1 and 2, 2011 because there are small and big forest fires at that time. The detection rate was 80% in terms of the frequency of the forest fires and was 99% in terms of the damaged area. Considering the number of COMS's channels and its low resolution, this result is a remarkable outcome. To provide users with the result of our algorithm, we developed a smartphone application for users JSP(Java Server Page). This application can work regardless of the smartphone's operating system. This study can be unsuitable for other areas and days because we used just two days data. To improve the accuracy of our algorithm, we need analysis using long-term data as future work.

Lessons Learned from the Deployment and Integration of a Microwave Sounder Based Tropical Cyclone Intensity and Surface Wind Estimation Algorithm into NOAA/NESDIS Satellite Product Operations

NASA Astrophysics Data System (ADS)

Longmore, S. P.; Knaff, J. A.; Schumacher, A.; Dostalek, J.; DeMaria, R.; Chirokova, G.; Demaria, M.; Powell, D. C.; Sigmund, A.; Yu, W.

2014-12-01

The Colorado State University (CSU) Cooperative Institute for Research in the Atmosphere (CIRA) has recently deployed a tropical cyclone (TC) intensity and surface wind radii estimation algorithm that utilizes Suomi National Polar-orbiting Partnership (S-NPP) satellite Advanced Technology Microwave Sounder (ATMS) and Advanced Microwave Sounding Unit (AMSU) from the NOAA18, NOAA19 and METOPA polar orbiting satellites for testing, integration and operations for the Product System Development and Implementation (PSDI) projects at NOAA's National Environmental Satellite, Data, and Information Service (NESDIS). This presentation discusses the evolution of the CIRA NPP/AMSU TC algorithms internally at CIRA and its migration and integration into the NOAA Data Exploitation (NDE) development and testing frameworks. The discussion will focus on 1) the development cycle of internal NPP/AMSU TC algorithms components by scientists and software engineers, 2) the exchange of these components into the NPP/AMSU TC software systems using the subversion version control system and other exchange methods, 3) testing, debugging and integration of the NPP/AMSU TC systems both at CIRA/NESDIS and 4) the update cycle of new releases through continuous integration. Lastly, a discussion of the methods that were effective and those that need revision will be detailed for the next iteration of the NPP/AMSU TC system.

Development of a remote sensing algorithm to retrieve atmospheric aerosol properties using multiwavelength and multipixel information

NASA Astrophysics Data System (ADS)

Hashimoto, Makiko; Nakajima, Teruyuki

2017-06-01

We developed a satellite remote sensing algorithm to retrieve the aerosol optical properties using satellite-received radiances for multiple wavelengths and pixels. Our algorithm utilizes spatial inhomogeneity of surface reflectance to retrieve aerosol properties, and the main target is urban aerosols. This algorithm can simultaneously retrieve aerosol optical thicknesses (AOT) for fine- and coarse-mode aerosols, soot volume fraction in fine-mode aerosols (SF), and surface reflectance over heterogeneous surfaces such as urban areas that are difficult to obtain by conventional pixel-by-pixel methods. We applied this algorithm to radiances measured by the Greenhouse Gases Observing Satellite/Thermal and Near Infrared Sensor for Carbon Observations-Cloud and Aerosol Image (GOSAT/TANSO-CAI) at four wavelengths and were able to retrieve the aerosol parameters in several urban regions and other surface types. A comparison of the retrieved AOTs with those from the Aerosol Robotic Network (AERONET) indicated retrieval accuracy within ±0.077 on average. It was also found that the column-averaged SF and the aerosol single scattering albedo (SSA) underwent seasonal changes as consistent with the ground surface measurements of SSA and black carbon at Beijing, China.

Time series analysis of infrared satellite data for detecting thermal anomalies: a hybrid approach

NASA Astrophysics Data System (ADS)

Koeppen, W. C.; Pilger, E.; Wright, R.

2011-07-01

We developed and tested an automated algorithm that analyzes thermal infrared satellite time series data to detect and quantify the excess energy radiated from thermal anomalies such as active volcanoes. Our algorithm enhances the previously developed MODVOLC approach, a simple point operation, by adding a more complex time series component based on the methods of the Robust Satellite Techniques (RST) algorithm. Using test sites at Anatahan and Kīlauea volcanoes, the hybrid time series approach detected ~15% more thermal anomalies than MODVOLC with very few, if any, known false detections. We also tested gas flares in the Cantarell oil field in the Gulf of Mexico as an end-member scenario representing very persistent thermal anomalies. At Cantarell, the hybrid algorithm showed only a slight improvement, but it did identify flares that were undetected by MODVOLC. We estimate that at least 80 MODIS images for each calendar month are required to create good reference images necessary for the time series analysis of the hybrid algorithm. The improved performance of the new algorithm over MODVOLC will result in the detection of low temperature thermal anomalies that will be useful in improving our ability to document Earth's volcanic eruptions, as well as detecting low temperature thermal precursors to larger eruptions.

An Improved Algorithm for Retrieving Surface Downwelling Longwave Radiation from Satellite Measurements

NASA Technical Reports Server (NTRS)

Zhou, Yaping; Kratz, David P.; Wilber, Anne C.; Gupta, Shashi K.; Cess, Robert D.

2006-01-01

Retrieving surface longwave radiation from space has been a difficult task since the surface downwelling longwave radiation (SDLW) are integrations from radiation emitted by the entire atmosphere, while those emitted from the upper atmosphere are absorbed before reaching the surface. It is particularly problematic when thick clouds are present since thick clouds will virtually block all the longwave radiation from above, while satellites observe atmosphere emissions mostly from above the clouds. Zhou and Cess developed an algorithm for retrieving SDLW based upon detailed studies using radiative transfer model calculations and surface radiometric measurements. Their algorithm linked clear sky SDLW with surface upwelling longwave flux and column precipitable water vapor. For cloudy sky cases, they used cloud liquid water path as an additional parameter to account for the effects of clouds. Despite the simplicity of their algorithm, it performed very well for most geographical regions except for those regions where the atmospheric conditions near the surface tend to be extremely cold and dry. Systematic errors were also found for areas that were covered with ice clouds. An improved version of the algorithm was developed that prevents the large errors in the SDLW at low water vapor amounts. The new algorithm also utilizes cloud fraction and cloud liquid and ice water paths measured from the Cloud and the Earth's Radiant Energy System (CERES) satellites to separately compute the clear and cloudy portions of the fluxes. The new algorithm has been validated against surface measurements at 29 stations around the globe for the Terra and Aqua satellites. The results show significant improvement over the original version. The revised Zhou-Cess algorithm is also slightly better or comparable to more sophisticated algorithms currently implemented in the CERES processing. It will be incorporated in the CERES project as one of the empirical surface radiation algorithms.

Miniature Rotorcraft Flight Control Stabilization System

DTIC Science & Technology

2008-05-30

The first algorithm is based on the well known QUEST algorithm used for spacecraft and satellites. Due to large vibration in sensors a pseudo...for spacecraft and satellites. Due to large vibration in sensors a pseudo-measurement is developed from gyroscope measurements and rotational...using any valid set of orientation map. Note, in Eq. (6) Euler angles were used to describe . A common alternative to Euler angles is a quaternion

Development of a surface isolation estimation technique suitable for application of polar orbiting satellite data

NASA Technical Reports Server (NTRS)

Davis, P. A.; Penn, L. M. (Principal Investigator)

1981-01-01

A technique is developed for the estimation of total daily insolation on the basis of data derivable from operational polar-orbiting satellites. Although surface insolation and meteorological observations are used in the development, the algorithm is constrained in application by the infrequent daytime polar-orbiter coverage.

NASA GPM GV Science Requirements

NASA Technical Reports Server (NTRS)

Smith, E.

2003-01-01

An important scientific objective of the NASA portion of the GPM Mission is to generate quantitatively-based error characterization information along with the rainrate retrievals emanating from the GPM constellation of satellites. These data must serve four main purposes: (1) they must be of sufficient quality, uniformity, and timeliness to govern the observation weighting schemes used in the data assimilation modules of numerical weather prediction models; (2) they must extend over that portion of the globe accessible by the GPM core satellite to which the NASA GV program is focused - (approx.65 degree inclination); (3) they must have sufficient specificity to enable detection of physically-formulated microphysical and meteorological weaknesses in the standard physical level 2 rainrate algorithms to be used in the GPM Precipitation Processing System (PPS), i.e., algorithms which will have evolved from the TRMM standard physical level 2 algorithms; and (4) they must support the use of physical error modeling as a primary validation tool and as the eventual replacement of the conventional GV approach of statistically intercomparing surface rainrates fiom ground and satellite measurements. This approach to ground validation research represents a paradigm shift vis-&-vis the program developed for the TRMM mission, which conducted ground validation largely as a statistical intercomparison process between raingauge-derived or radar-derived rainrates and the TRMM satellite rainrate retrievals -- long after the original satellite retrievals were archived. This approach has been able to quantify averaged rainrate differences between the satellite algorithms and the ground instruments, but has not been able to explain causes of algorithm failures or produce error information directly compatible with the cost functions of data assimilation schemes. These schemes require periodic and near-realtime bias uncertainty (i.e., global space-time distributed conditional accuracy of the retrieved rainrates) and local error covariance structure (i.e., global space-time distributed error correlation information for the local 4-dimensional space-time domain -- or in simpler terms, the matrix form of precision error). This can only be accomplished by establishing a network of high quality-heavily instrumented supersites selectively distributed at a few oceanic, continental, and coastal sites. Economics and pragmatics dictate that the network must be made up of a relatively small number of sites (6-8) created through international cooperation. This presentation will address some of the details of the methodology behind the error characterization approach, some proposed solutions for expanding site-developed error properties to regional scales, a data processing and communications concept that would enable rapid implementation of algorithm improvement by the algorithm developers, and the likely available options for developing the supersite network.

Accounting of fundamental components of the rotation parameters of the Earth in the formation of a high-accuracy orbit of navigation satellites

NASA Astrophysics Data System (ADS)

Markov, Yu. G.; Mikhailov, M. V.; Pochukaev, V. N.

2012-07-01

An analysis of perturbing factors influencing the motion of a navigation satellite (NS) is carried out, and the degree of influence of each factor on the GLONASS orbit is estimated. It is found that fundamental components of the Earth's rotation parameters (ERP) are one substantial factor commensurable with maximum perturbations. Algorithms for the calculation of orbital perturbations caused by these parameters are given; these algorithms can be implemented in a consumer's equipment. The daily prediction of NS coordinates is performed on the basis of real GLONASS satellite ephemerides transmitted to a consumer, using the developed prediction algorithms taking the ERP into account. The obtained accuracy of the daily prediction of GLONASS ephemerides exceeds by tens of times the accuracy of the daily prediction performed using algorithms recommended in interface control documents.

Performance of a low data rate speech codec for land-mobile satellite communications

NASA Technical Reports Server (NTRS)

Gersho, Allen; Jedrey, Thomas C.

1990-01-01

In an effort to foster the development of new technologies for the emerging land mobile satellite communications services, JPL funded two development contracts in 1984: one to the Univ. of Calif., Santa Barbara and the other to the Georgia Inst. of Technology, to develop algorithms and real time hardware for near toll quality speech compression at 4800 bits per second. Both universities have developed and delivered speech codecs to JPL, and the UCSB codec was extensively tested by JPL in a variety of experimental setups. The basic UCSB speech codec algorithms and the test results of the various experiments performed with this codec are presented.

JPSS-1 Algorithm Updates and upgrades

NASA Astrophysics Data System (ADS)

Weinrich, J. A.

2017-12-01

The National Oceanic and Atmospheric Administration (NOAA) is acquiring the next-generation weather and environmental satellite system, named the Joint Polar Satellite System (JPSS). The Suomi National Polar-orbiting Partnership (S-NPP) satellite was launched on 28 October, 2011, and is a pathfinder for JPSS and provides continuity for the NASA Earth Observation System and the NOAA Polar-orbiting Operational Environmental Satellite (POES) system. JPSS-1 is scheduled to launch in 2017. NASA is developing the Common Ground System which will process JPSS data and has the flexibility to process data from other satellites. This presentation will review the JPSS readiness from a Calibration/Validation perspective. Examples of JPSS Readiness will be presented including algorithm and table updates. The outcomes will show the Cal/Val planning as we going into Launch in 2017.

Algorithm Development and Validation of CDOM Properties for Estuarine and Continental Shelf Waters Along the Northeastern U.S. Coast

NASA Technical Reports Server (NTRS)

Mannino, Antonio; Novak, Michael G.; Hooker, Stanford B.; Hyde, Kimberly; Aurin, Dick

2014-01-01

An extensive set of field measurements have been collected throughout the continental margin of the northeastern U.S. from 2004 to 2011 to develop and validate ocean color satellite algorithms for the retrieval of the absorption coefficient of chromophoric dissolved organic matter (aCDOM) and CDOM spectral slopes for the 275:295 nm and 300:600 nm spectral range (S275:295 and S300:600). Remote sensing reflectance (Rrs) measurements computed from in-water radiometry profiles along with aCDOM() data are applied to develop several types of algorithms for the SeaWiFS and MODIS-Aqua ocean color satellite sensors, which involve least squares linear regression of aCDOM() with (1) Rrs band ratios, (2) quasi-analytical algorithm-based (QAA based) products of total absorption coefficients, (3) multiple Rrs bands within a multiple linear regression (MLR) analysis, and (4) diffuse attenuation coefficient (Kd). The relative error (mean absolute percent difference; MAPD) for the MLR retrievals of aCDOM(275), aCDOM(355), aCDOM(380), aCDOM(412) and aCDOM(443) for our study region range from 20.4-23.9 for MODIS-Aqua and 27.3-30 for SeaWiFS. Because of the narrower range of CDOM spectral slope values, the MAPD for the MLR S275:295 and QAA-based S300:600 algorithms are much lower ranging from 9.9 and 8.3 for SeaWiFS, respectively, and 8.7 and 6.3 for MODIS, respectively. Seasonal and spatial MODIS-Aqua and SeaWiFS distributions of aCDOM, S275:295 and S300:600 processed with these algorithms are consistent with field measurements and the processes that impact CDOM levels along the continental shelf of the northeastern U.S. Several satellite data processing factors correlate with higher uncertainty in satellite retrievals of aCDOM, S275:295 and S300:600 within the coastal ocean, including solar zenith angle, sensor viewing angle, and atmospheric products applied for atmospheric corrections. Algorithms that include ultraviolet Rrs bands provide a better fit to field measurements than algorithms without the ultraviolet Rrs bands. This suggests that satellite sensors with ultraviolet capability could provide better retrievals of CDOM. Because of the strong correlations between CDOM parameters and DOM constituents in the coastal ocean, satellite observations of CDOM parameters can be applied to study the distributions, sources and sinks of DOM, which are relevant for understanding the carbon cycle, modeling the Earth system, and to discern how the Earth is changing.

Differences in estimating terrestrial water flux from three satellite-based Priestley-Taylor algorithms

NASA Astrophysics Data System (ADS)

Yao, Yunjun; Liang, Shunlin; Yu, Jian; Zhao, Shaohua; Lin, Yi; Jia, Kun; Zhang, Xiaotong; Cheng, Jie; Xie, Xianhong; Sun, Liang; Wang, Xuanyu; Zhang, Lilin

2017-04-01

Accurate estimates of terrestrial latent heat of evaporation (LE) for different biomes are essential to assess energy, water and carbon cycles. Different satellite- based Priestley-Taylor (PT) algorithms have been developed to estimate LE in different biomes. However, there are still large uncertainties in LE estimates for different PT algorithms. In this study, we evaluated differences in estimating terrestrial water flux in different biomes from three satellite-based PT algorithms using ground-observed data from eight eddy covariance (EC) flux towers of China. The results reveal that large differences in daily LE estimates exist based on EC measurements using three PT algorithms among eight ecosystem types. At the forest (CBS) site, all algorithms demonstrate high performance with low root mean square error (RMSE) (less than 16 W/m2) and high squared correlation coefficient (R2) (more than 0.9). At the village (HHV) site, the ATI-PT algorithm has the lowest RMSE (13.9 W/m2), with bias of 2.7 W/m2 and R2 of 0.66. At the irrigated crop (HHM) site, almost all models algorithms underestimate LE, indicating these algorithms may not capture wet soil evaporation by parameterization of the soil moisture. In contrast, the SM-PT algorithm shows high values of R2 (comparable to those of ATI-PT and VPD-PT) at most other (grass, wetland, desert and Gobi) biomes. There are no obvious differences in seasonal LE estimation using MODIS NDVI and LAI at most sites. However, all meteorological or satellite-based water-related parameters used in the PT algorithm have uncertainties for optimizing water constraints. This analysis highlights the need to improve PT algorithms with regard to water constraints.

Research Supporting Satellite Communications Technology

NASA Technical Reports Server (NTRS)

Horan Stephen; Lyman, Raphael

2005-01-01

This report describes the second year of research effort under the grant Research Supporting Satellite Communications Technology. The research program consists of two major projects: Fault Tolerant Link Establishment and the design of an Auto-Configurable Receiver. The Fault Tolerant Link Establishment protocol is being developed to assist the designers of satellite clusters to manage the inter-satellite communications. During this second year, the basic protocol design was validated with an extensive testing program. After this testing was completed, a channel error model was added to the protocol to permit the effects of channel errors to be measured. This error generation was used to test the effects of channel errors on Heartbeat and Token message passing. The C-language source code for the protocol modules was delivered to Goddard Space Flight Center for integration with the GSFC testbed. The need for a receiver autoconfiguration capability arises when a satellite-to-ground transmission is interrupted due to an unexpected event, the satellite transponder may reset to an unknown state and begin transmitting in a new mode. During Year 2, we completed testing of these algorithms when noise-induced bit errors were introduced. We also developed and tested an algorithm for estimating the data rate, assuming an NRZ-formatted signal corrupted with additive white Gaussian noise, and we took initial steps in integrating both algorithms into the SDR test bed at GSFC.

GPS Modeling and Analysis. Summary of Research: GPS Satellite Axial Ratio Predictions

NASA Technical Reports Server (NTRS)

Axelrad, Penina; Reeh, Lisa

2002-01-01

This report outlines the algorithms developed at the Colorado Center for Astrodynamics Research to model yaw and predict the axial ratio as measured from a ground station. The algorithms are implemented in a collection of Matlab functions and scripts that read certain user input, such as ground station coordinates, the UTC time, and the desired GPS (Global Positioning System) satellites, and compute the above-mentioned parameters. The position information for the GPS satellites is obtained from Yuma almanac files corresponding to the prescribed date. The results are displayed graphically through time histories and azimuth-elevation plots.

Attitude guidance and simulation with animation of a land-survey satellite motion

NASA Astrophysics Data System (ADS)

Somova, Tatyana

2017-01-01

We consider problems of synthesis of the vector spline attitude guidance laws for a land-survey satellite and an in-flight support of the satellite attitude control system with the use of computer animation of its motion. We have presented the results on the efficiency of the developed algorithms.

Technical Report Series on Global Modeling and Data Assimilation. Volume 12; Comparison of Satellite Global Rainfall Algorithms

NASA Technical Reports Server (NTRS)

Suarez, Max J. (Editor); Chang, Alfred T. C.; Chiu, Long S.

1997-01-01

Seventeen months of rainfall data (August 1987-December 1988) from nine satellite rainfall algorithms (Adler, Chang, Kummerow, Prabhakara, Huffman, Spencer, Susskind, and Wu) were analyzed to examine the uncertainty of satellite-derived rainfall estimates. The variability among algorithms, measured as the standard deviation computed from the ensemble of algorithms, shows regions of high algorithm variability tend to coincide with regions of high rain rates. Histograms of pattern correlation (PC) between algorithms suggest a bimodal distribution, with separation at a PC-value of about 0.85. Applying this threshold as a criteria for similarity, our analyses show that algorithms using the same sensor or satellite input tend to be similar, suggesting the dominance of sampling errors in these satellite estimates.

Development, Validation, and Potential Enhancements to the Second-Generation Operational Aerosol Product at the National Environmental Satellite, Data, and Information Service of the National Oceanic and Atmospheric Administration

NASA Technical Reports Server (NTRS)

Stowe, Larry L.; Ignatov, Alexander M.; Singh, Ramdas R.

1997-01-01

A revised (phase 2) single-channel algorithm for aerosol optical thickness, tau(sup A)(sub SAT), retrieval over oceans from radiances in channel 1 (0.63 microns) of the Advanced Very High Resolution Radiometer (AVHRR) has been implemented at the National Oceanic and Atmospheric Administration's National Environmental Satellite Data and Information Service for the NOAA 14 satellite launched December 30, 1994. It is based on careful validation of its operational predecessor (phase 1 algorithm), implemented for NOAA 14 in 1989. Both algorithms scale the upward satellite radiances in cloud-free conditions to aerosol optical thickness using an updated radiative transfer model of the ocean and atmosphere. Application of the phase 2 algorithm to three matchup Sun-photometer and satellite data sets, one with NOAA 9 in 1988 and two with NOAA 11 in 1989 and 1991, respectively, show systematic error is less than 10%, with a random error of sigma(sub tau) approx. equal 0.04. First results of tau(sup A)(sub SAT) retrievals from NOAA 14 using the phase 2 algorithm, and from checking its internal consistency, are presented. The potential two-channel (phase 3) algorithm for the retrieval of an aerosol size parameter, such as the Junge size distribution exponent, by adding either channel 2 (0.83 microns) from the current AVHRR instrument, or a 1.6-microns channel to be available on the Tropical Rainfall Measurement Mission and the NOAA-KLM satellites by 1997 is under investigation. The possibility of using this additional information in the retrieval of a more accurate estimate of aerosol optical thickness is being explored.

A sustainable genetic algorithm for satellite resource allocation

NASA Technical Reports Server (NTRS)

Abbott, R. J.; Campbell, M. L.; Krenz, W. C.

1995-01-01

A hybrid genetic algorithm is used to schedule tasks for 8 satellites, which can be modelled as a robot whose task is to retrieve objects from a two dimensional field. The objective is to find a schedule that maximizes the value of objects retrieved. Typical of the real-world tasks to which this corresponds is the scheduling of ground contacts for a communications satellite. An important feature of our application is that the amount of time available for running the scheduler is not necessarily known in advance. This requires that the scheduler produce reasonably good results after a short period but that it also continue to improve its results if allowed to run for a longer period. We satisfy this requirement by developing what we call a sustainable genetic algorithm.

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

NASA Astrophysics Data System (ADS)

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/.

Nowcasting Aircraft Icing Conditions in Moscow Region Using Geostationary Meteorological Satellite Data

NASA Astrophysics Data System (ADS)

Barabanova, Olga

2013-04-01

Nowadays the Main Aviation Meteorological Centre in Moscow (MAMC) provides forecasts of icing conditions in Moscow Region airports using information of surface observation network, weather radars and atmospheric sounding. Unfortunately, satellite information is not used properly in aviation meteorological offices in Moscow Region: weather forecasters deal with satellites images of cloudiness only. The main forecasters of MAMC realise that it is necessary to employ meteorological satellite numerical data from different channels in aviation forecasting and especially in nowcasting. Algorithm of nowcasting aircraft in-flight icing conditions has been developed using data from geostationary meteorological satellites "Meteosat-7" and "Meteosat-9". The algorithm is based on the brightness temperature differences. Calculation of brightness temperature differences help to discriminate clouds with supercooled large drops where severe icing conditions are most likely. Due to the lack of visible channel data, the satellite icing detection methods will be less accurate at night. Besides this method is limited by optically thick ice clouds where it is not possible to determine the extent to which supercooled large drops exists within the underlying clouds. However, we determined that most of the optically thick cases are associated with convection or mid-latitude cyclones and they will nearly always have a layer where which supercooled large drops exists with an icing threat. This product is created hourly for the Moscow Air Space and mark zones with moderate or severe icing hazards. The results were compared with mesoscale numerical atmospheric model COSMO-RU output. Verification of the algorithms results using aircraft pilot reports shows that this algorithm is a good instrument for the operational practise in aviation meteorological offices in Moscow Region. The satellite-based algorithms presented here can be used in real time to diagnose areas of icing for pilots to avoid.

Early Benchmarks of Product Generation Capabilities of the GOES-R Ground System for Operational Weather Prediction

NASA Astrophysics Data System (ADS)

Kalluri, S. N.; Haman, B.; Vititoe, D.

2014-12-01

The ground system under development for Geostationary Operational Environmental Satellite-R (GOES-R) series of weather satellite has completed a key milestone in implementing the science algorithms that process raw sensor data to higher level products in preparation for launch. Real time observations from GOES-R are expected to make significant contributions to Earth and space weather prediction, and there are stringent requirements to product weather products at very low latency to meet NOAA's operational needs. Simulated test data from all the six GOES-R sensors are being processed by the system to test and verify performance of the fielded system. Early results show that the system development is on track to meet functional and performance requirements to process science data. Comparison of science products generated by the ground system from simulated data with those generated by the algorithm developers show close agreement among data sets which demonstrates that the algorithms are implemented correctly. Successful delivery of products to AWIPS and the Product Distribution and Access (PDA) system from the core system demonstrate that the external interfaces are working.

Instrument-induced spatial crosstalk deconvolution algorithm

NASA Technical Reports Server (NTRS)

Wright, Valerie G.; Evans, Nathan L., Jr.

1986-01-01

An algorithm has been developed which reduces the effects of (deconvolves) instrument-induced spatial crosstalk in satellite image data by several orders of magnitude where highly precise radiometry is required. The algorithm is based upon radiance transfer ratios which are defined as the fractional bilateral exchange of energy betwen pixels A and B.

An Online Tilt Estimation and Compensation Algorithm for a Small Satellite Camera

NASA Astrophysics Data System (ADS)

Lee, Da-Hyun; Hwang, Jai-hyuk

2018-04-01

In the case of a satellite camera designed to execute an Earth observation mission, even after a pre-launch precision alignment process has been carried out, misalignment will occur due to external factors during the launch and in the operating environment. In particular, for high-resolution satellite cameras, which require submicron accuracy for alignment between optical components, misalignment is a major cause of image quality degradation. To compensate for this, most high-resolution satellite cameras undergo a precise realignment process called refocusing before and during the operation process. However, conventional Earth observation satellites only execute refocusing upon de-space. Thus, in this paper, an online tilt estimation and compensation algorithm that can be utilized after de-space correction is executed. Although the sensitivity of the optical performance degradation due to the misalignment is highest in de-space, the MTF can be additionally increased by correcting tilt after refocusing. The algorithm proposed in this research can be used to estimate the amount of tilt that occurs by taking star images, and it can also be used to carry out automatic tilt corrections by employing a compensation mechanism that gives angular motion to the secondary mirror. Crucially, this algorithm is developed using an online processing system so that it can operate without communication with the ground.

A demand assignment control in international business satellite communications network

NASA Astrophysics Data System (ADS)

Nohara, Mitsuo; Takeuchi, Yoshio; Takahata, Fumio; Hirata, Yasuo

An experimental system is being developed for use in an international business satellite (IBS) communications network based on demand-assignment (DA) and TDMA techniques. This paper discusses its system design, in particular from the viewpoints of a network configuration, a DA control, and a satellite channel-assignment algorithm. A satellite channel configuration is also presented along with a tradeoff study on transmission rate, HPA output power, satellite resource efficiency, service quality, and so on.

Algorithm integration using ADL (Algorithm Development Library) for improving CrIMSS EDR science product quality

NASA Astrophysics Data System (ADS)

Das, B.; Wilson, M.; Divakarla, M. G.; Chen, W.; Barnet, C.; Wolf, W.

2013-05-01

Algorithm Development Library (ADL) is a framework that mimics the operational system IDPS (Interface Data Processing Segment) that is currently being used to process data from instruments aboard Suomi National Polar-orbiting Partnership (S-NPP) satellite. The satellite was launched successfully in October 2011. The Cross-track Infrared and Microwave Sounder Suite (CrIMSS) consists of the Advanced Technology Microwave Sounder (ATMS) and Cross-track Infrared Sounder (CrIS) instruments that are on-board of S-NPP. These instruments will also be on-board of JPSS (Joint Polar Satellite System) that will be launched in early 2017. The primary products of the CrIMSS Environmental Data Record (EDR) include global atmospheric vertical temperature, moisture, and pressure profiles (AVTP, AVMP and AVPP) and Ozone IP (Intermediate Product from CrIS radiances). Several algorithm updates have recently been proposed by CrIMSS scientists that include fixes to the handling of forward modeling errors, a more conservative identification of clear scenes, indexing corrections for daytime products, and relaxed constraints between surface temperature and air temperature for daytime land scenes. We have integrated these improvements into the ADL framework. This work compares the results from ADL emulation of future IDPS system incorporating all the suggested algorithm updates with the current official processing results by qualitative and quantitative evaluations. The results prove these algorithm updates improve science product quality.

Developing the science product algorithm testbed for Chinese next-generation geostationary meteorological satellites: Fengyun-4 series

NASA Astrophysics Data System (ADS)

Min, Min; Wu, Chunqiang; Li, Chuan; Liu, Hui; Xu, Na; Wu, Xiao; Chen, Lin; Wang, Fu; Sun, Fenglin; Qin, Danyu; Wang, Xi; Li, Bo; Zheng, Zhaojun; Cao, Guangzhen; Dong, Lixin

2017-08-01

Fengyun-4A (FY-4A), the first of the Chinese next-generation geostationary meteorological satellites, launched in 2016, offers several advances over the FY-2: more spectral bands, faster imaging, and infrared hyperspectral measurements. To support the major objective of developing the prototypes of FY-4 science algorithms, two science product algorithm testbeds for imagers and sounders have been developed by the scientists in the FY-4 Algorithm Working Group (AWG). Both testbeds, written in FORTRAN and C programming languages for Linux or UNIX systems, have been tested successfully by using Intel/g compilers. Some important FY-4 science products, including cloud mask, cloud properties, and temperature profiles, have been retrieved successfully through using a proxy imager, Himawari-8/Advanced Himawari Imager (AHI), and sounder data, obtained from the Atmospheric InfraRed Sounder, thus demonstrating their robustness. In addition, in early 2016, the FY-4 AWG was developed based on the imager testbed—a near real-time processing system for Himawari-8/AHI data for use by Chinese weather forecasters. Consequently, robust and flexible science product algorithm testbeds have provided essential and productive tools for popularizing FY-4 data and developing substantial improvements in FY-4 products.

Fast segmentation of satellite images using SLIC, WebGL and Google Earth Engine

NASA Astrophysics Data System (ADS)

Donchyts, Gennadii; Baart, Fedor; Gorelick, Noel; Eisemann, Elmar; van de Giesen, Nick

2017-04-01

Google Earth Engine (GEE) is a parallel geospatial processing platform, which harmonizes access to petabytes of freely available satellite images. It provides a very rich API, allowing development of dedicated algorithms to extract useful geospatial information from these images. At the same time, modern GPUs provide thousands of computing cores, which are mostly not utilized in this context. In the last years, WebGL became a popular and well-supported API, allowing fast image processing directly in web browsers. In this work, we will evaluate the applicability of WebGL to enable fast segmentation of satellite images. A new implementation of a Simple Linear Iterative Clustering (SLIC) algorithm using GPU shaders will be presented. SLIC is a simple and efficient method to decompose an image in visually homogeneous regions. It adapts a k-means clustering approach to generate superpixels efficiently. While this approach will be hard to scale, due to a significant amount of data to be transferred to the client, it should significantly improve exploratory possibilities and simplify development of dedicated algorithms for geoscience applications. Our prototype implementation will be used to improve surface water detection of the reservoirs using multispectral satellite imagery.

MODIS. Volume 2: MODIS level 1 geolocation, characterization and calibration algorithm theoretical basis document, version 1

NASA Technical Reports Server (NTRS)

Barker, John L.; Harnden, Joann M. K.; Montgomery, Harry; Anuta, Paul; Kvaran, Geir; Knight, ED; Bryant, Tom; Mckay, AL; Smid, Jon; Knowles, Dan, Jr.

1994-01-01

The EOS Moderate Resolution Imaging Spectrometer (MODIS) is being developed by NASA for flight on the Earth Observing System (EOS) series of satellites, the first of which (EOS-AM-1) is scheduled for launch in 1998. This document describes the algorithms and their theoretical basis for the MODIS Level 1B characterization, calibration, and geolocation algorithms which must produce radiometrically, spectrally, and spatially calibrated data with sufficient accuracy so that Global change research programs can detect minute changes in biogeophysical parameters. The document first describes the geolocation algorithm which determines geodetic latitude, longitude, and elevation of each MODIS pixel and the determination of geometric parameters for each observation (satellite zenith angle, satellite azimuth, range to the satellite, solar zenith angle, and solar azimuth). Next, the utilization of the MODIS onboard calibration sources, which consist of the Spectroradiometric Calibration Assembly (SRCA), Solar Diffuser (SD), Solar Diffuser Stability Monitor (SDSM), and the Blackbody (BB), is treated. Characterization of these sources and integration of measurements into the calibration process is described. Finally, the use of external sources, including the Moon, instrumented sites on the Earth (called vicarious calibration), and unsupervised normalization sites having invariant reflectance and emissive properties is treated. Finally, algorithms for generating utility masks needed for scene-based calibration are discussed. Eight appendices are provided, covering instrument design and additional algorithm details.

Monitoring of Arctic Conditions from a Virtual Constellation of Synthetic Aperture Radar Satellites

DTIC Science & Technology

2014-09-30

Constellation of Synthetic Aperture Radar Satellites RSMAS – Department of Ocean Sciences Center for Southeastern Tropical Advanced Remote Sensing...fax: (305) 421-4696 email: pminnett@rsmas.miami.edu Award Number: N00014-12-1-0448 LONG-TERM GOALS Utilize a constellation of satellite...OBJECTIVES a) Provide daily Arctic situational awareness from the CSTARS SAR satellite constellation . b) Develop a Neural Network algorithm for ice-type

An Environmental for Hardware-in-the-Loop Formation Navigation and Control

NASA Technical Reports Server (NTRS)

Burns, Rich; Naasz, Bo; Gaylor, Dave; Higinbotham, John

2004-01-01

Recent interest in formation flying satellite systems has spurred a considerable amount of research in the relative navigation and control of satellites. Development in this area has included new estimation and control algorithms as well as sensor and actuator development specifically geared toward the relative control problem. This paper describes a simulation facility, the Formation Flying Test Bed (FFTB) at NASA Goddard Space Flight Center, which allows engineers to test new algorithms for the formation flying problem with relevant GN&C hardware in a closed loop simulation. The FFTB currently supports the inclusion of GPS receiver hardware in the simulation loop. Support for satellite crosslink ranging technology is at a prototype stage. This closed-loop, hardware inclusive simulation capability permits testing of navigation and control software in the presence of the actual hardware with which the algorithms must interact. This capability provides the navigation or control developer with a perspective on how the algorithms perform as part of the closed-loop system. In this paper, the overall design and evolution of the FFTB are presented. Each component of the FFTB is then described. Interfaces between the components of the FFTB are shown and the interfaces to and between navigation and control software are described. Finally, an example of closed-loop formation control with GPS receivers in the loop is presented.

A new algorithm for agile satellite-based acquisition operations

NASA Astrophysics Data System (ADS)

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.

Machine Learning Algorithms for Automated Satellite Snow and Sea Ice Detection

NASA Astrophysics Data System (ADS)

Bonev, George

The continuous mapping of snow and ice cover, particularly in the arctic and poles, are critical to understanding the earth and atmospheric science. Much of the world's sea ice and snow covers the most inhospitable places, making measurements from satellite-based remote sensors essential. Despite the wealth of data from these instruments many challenges remain. For instance, remote sensing instruments reside on-board different satellites and observe the earth at different portions of the electromagnetic spectrum with different spatial footprints. Integrating and fusing this information to make estimates of the surface is a subject of active research. In response to these challenges, this dissertation will present two algorithms that utilize methods from statistics and machine learning, with the goal of improving on the quality and accuracy of current snow and sea ice detection products. The first algorithm aims at implementing snow detection using optical/infrared instrument data. The novelty in this approach is that the classifier is trained using ground station measurements of snow depth that are collocated with the reflectance observed at the satellite. Several classification methods are compared using this training data to identify the one yielding the highest accuracy and optimal space/time complexity. The algorithm is then evaluated against the current operational NASA snow product and it is found that it produces comparable and in some cases superior accuracy results. The second algorithm presents a fully automated approach to sea ice detection that integrates data obtained from passive microwave and optical/infrared satellite instruments. For a particular region of interest the algorithm generates sea ice maps of each individual satellite overpass and then aggregates them to a daily composite level, maximizing the amount of high resolution information available. The algorithm is evaluated at both, the individual satellite overpass level, and at the daily composite level. Results show that at the single overpass level for clear-sky regions, the developed multi-sensor algorithm performs with accuracy similar to that of the optical/infrared products, with the advantage of being able to also classify partially cloud-obscured regions with the help of passive microwave data. At the daily composite level, results show that the algorithm's performance with respect to total ice extent is in line with other daily products, with the novelty of being fully automated and having higher resolution.

Development of a generalized algorithm of satellite remote sensing using multi-wavelength and multi-pixel information (MWP method) for aerosol properties by satellite-borne imager

NASA Astrophysics Data System (ADS)

Hashimoto, M.; Nakajima, T.; Morimoto, S.; Takenaka, H.

2014-12-01

We have developed a new satellite remote sensing algorithm to retrieve the aerosol optical characteristics using multi-wavelength and multi-pixel information of satellite imagers (MWP method). In this algorithm, the inversion method is a combination of maximum a posteriori (MAP) method (Rodgers, 2000) and the Phillips-Twomey method (Phillips, 1962; Twomey, 1963) as a smoothing constraint for the state vector. Furthermore, with the progress of computing technique, this method has being combined with the direct radiation transfer calculation numerically solved by each iteration step of the non-linear inverse problem, without using LUT (Look Up Table) with several constraints.Retrieved parameters in our algorithm are aerosol optical properties, such as aerosol optical thickness (AOT) of fine and coarse mode particles, a volume soot fraction in fine mode particles, and ground surface albedo of each observed wavelength. We simultaneously retrieve all the parameters that characterize pixels in each of horizontal sub-domains consisting the target area. Then we successively apply the retrieval method to all the sub-domains in the target area.We conducted numerical tests for the retrieval of aerosol properties and ground surface albedo for GOSAT/CAI imager data to test the algorithm for the land area. The result of the experiment showed that AOTs of fine mode and coarse mode, soot fraction and ground surface albedo are successfully retrieved within expected accuracy. We discuss the accuracy of the algorithm for various land surface types. Then, we applied this algorithm to GOSAT/CAI imager data, and we compared retrieved and surface-observed AOTs at the CAI pixel closest to an AERONET (Aerosol Robotic Network) or SKYNET site in each region. Comparison at several sites in urban area indicated that AOTs retrieved by our method are in agreement with surface-observed AOT within ±0.066.Our future work is to extend the algorithm for analysis of AGEOS-II/GLI and GCOM/C-SGLI data.

Traffic model for the satellite component of UMTS

NASA Technical Reports Server (NTRS)

Hu, Y. F.; Sheriff, R. E.

1995-01-01

An algorithm for traffic volume estimation for satellite mobile communications systems has been developed. This algorithm makes use of worldwide databases for demographic and economic data. In order to provide for such an estimation, the effects of competing services have been considered so that likely market demand can be forecasted. Different user groups of the predicted market have been identified according to expectations in the quality of services and mobility requirement. The number of users for different user groups are calculated taking into account the gross potential market, the penetration rate of the identified services and the profitability to provide such services via satellite.

Near-Real-Time Satellite Cloud Products for Icing Detection and Aviation Weather over the USA

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Smith, William L., Jr.; Nguyen, Louis; Murray, J. J.; Heck, Patrick W.; Khaiyer, Mandana M.

2003-01-01

A set of physically based retrieval algorithms has been developed to derive from multispectral satellite imagery a variety of cloud properties that can be used to diagnose icing conditions when upper-level clouds are absent. The algorithms are being applied in near-real time to the Geostationary Operational Environmental Satellite (GOES) data over Florida, the Southern Great Plains, and the midwestern USA. The products are available in image and digital formats on the world-wide web. The analysis system is being upgraded to analyze GOES data over the CONUS. Validation, 24-hour processing, and operational issues are discussed.

Remote Sensing Applications to Water Quality Management in Florida

EPA Science Inventory

Increasingly, optical datasets from estuarine and coastal systems are becoming available for remote sensing algorithm development, validation, and application. With validated algorithms, the data streams from satellite sensors can provide unprecedented spatial and temporal data ...

Progress towards a Drag-free SmallSat

NASA Astrophysics Data System (ADS)

Saraf, Shailendhar

The net force acting on a drag-free satellite is purely gravitational as all other forces, mainly atmospheric drag and solar radiation pressure, are canceled out. In order to achieve this, a free floating reference (test mass) inside the satellite is shielded against all forces but gravity and a system of thrusters is commanded by a control algorithm such that the relative displacement between the reference and the satellite stays constant. The main input to that control algorithm is the output of a sensor which measures the relative displacement between the satellite and the test mass. Internal disturbance forces such as electrostatic or magnetic forces cannot be canceled out his way and have to be minimized by a careful design of the satellite. A drag-free technology package is under development at Stanford since 2004. It includes an optical displacement sensor to measure the relative position of the test mass inside the satellite, a caging mechanism to lock the test mass during launch, a UV LED based charge management system to minimize the effect of electrostatic forces, a thermal enclosure, and the drag-free control algorithms. Possible applications of drag-free satellites in fundamental physics (Gravity Probe B, LISA), geodesy (GOCE), and navigation (TRIAD I). In this presentation we will highlight the progress of the technology development towards a drag-free mission. The planned mission on a SaudiSat bus will demonstrate drag-free technology on a small spacecraft at a fraction of the cost of previous drag-free missions. The target acceleration noise is 10-12 m/sec2. With multiple such satellites a GRACE-like mission with improved sensitivity and potentially improved spatial and temporal resolution can be achieved.

Definition of an Enhanced Map-Matching Algorithm for Urban Environments with Poor GNSS Signal Quality.

PubMed

Jiménez, Felipe; Monzón, Sergio; Naranjo, Jose Eugenio

2016-02-04

Vehicle positioning is a key factor for numerous information and assistance applications that are included in vehicles and for which satellite positioning is mainly used. However, this positioning process can result in errors and lead to measurement uncertainties. These errors come mainly from two sources: errors and simplifications of digital maps and errors in locating the vehicle. From that inaccurate data, the task of assigning the vehicle's location to a link on the digital map at every instant is carried out by map-matching algorithms. These algorithms have been developed to fulfil that need and attempt to amend these errors to offer the user a suitable positioning. In this research; an algorithm is developed that attempts to solve the errors in positioning when the Global Navigation Satellite System (GNSS) signal reception is frequently lost. The algorithm has been tested with satisfactory results in a complex urban environment of narrow streets and tall buildings where errors and signal reception losses of the GPS receiver are frequent.

Definition of an Enhanced Map-Matching Algorithm for Urban Environments with Poor GNSS Signal Quality

PubMed Central

Jiménez, Felipe; Monzón, Sergio; Naranjo, Jose Eugenio

2016-01-01

Vehicle positioning is a key factor for numerous information and assistance applications that are included in vehicles and for which satellite positioning is mainly used. However, this positioning process can result in errors and lead to measurement uncertainties. These errors come mainly from two sources: errors and simplifications of digital maps and errors in locating the vehicle. From that inaccurate data, the task of assigning the vehicle’s location to a link on the digital map at every instant is carried out by map-matching algorithms. These algorithms have been developed to fulfil that need and attempt to amend these errors to offer the user a suitable positioning. In this research; an algorithm is developed that attempts to solve the errors in positioning when the Global Navigation Satellite System (GNSS) signal reception is frequently lost. The algorithm has been tested with satisfactory results in a complex urban environment of narrow streets and tall buildings where errors and signal reception losses of the GPS receiver are frequent. PMID:26861320

Three Dimensional Computer Graphics Federates for the 2012 Smackdown Simulation

NASA Technical Reports Server (NTRS)

Fordyce, Crystal; Govindaiah, Swetha; Muratet, Sean; O'Neil, Daniel A.; Schricker, Bradley C.

2012-01-01

The Simulation Interoperability Standards Organization (SISO) Smackdown is a two-year old annual event held at the 2012 Spring Simulation Interoperability Workshop (SIW). A primary objective of the Smackdown event is to provide college students with hands-on experience in developing distributed simulations using High Level Architecture (HLA). Participating for the second time, the University of Alabama in Huntsville (UAHuntsville) deployed four federates, two federates simulated a communications server and a lunar communications satellite with a radio. The other two federates generated 3D computer graphics displays for the communication satellite constellation and for the surface based lunar resupply mission. Using the Light-Weight Java Graphics Library, the satellite display federate presented a lunar-texture mapped sphere of the moon and four Telemetry Data Relay Satellites (TDRS), which received object attributes from the lunar communications satellite federate to drive their motion. The surface mission display federate was an enhanced version of the federate developed by ForwardSim, Inc. for the 2011 Smackdown simulation. Enhancements included a dead-reckoning algorithm and a visual indication of which communication satellite was in line of sight of Hadley Rille. This paper concentrates on these two federates by describing the functions, algorithms, HLA object attributes received from other federates, development experiences and recommendations for future, participating Smackdown teams.

GLASS daytime all-wave net radiation product: Algorithm development and preliminary validation

DOE PAGES

Jiang, Bo; Liang, Shunlin; Ma, Han; ...

2016-03-09

Mapping surface all-wave net radiation (R n) is critically needed for various applications. Several existing R n products from numerical models and satellite observations have coarse spatial resolutions and their accuracies may not meet the requirements of land applications. In this study, we develop the Global LAnd Surface Satellite (GLASS) daytime R n product at a 5 km spatial resolution. Its algorithm for converting shortwave radiation to all-wave net radiation using the Multivariate Adaptive Regression Splines (MARS) model is determined after comparison with three other algorithms. The validation of the GLASS R n product based on high-quality in situ measurementsmore » in the United States shows a coefficient of determination value of 0.879, an average root mean square error value of 31.61 Wm -2, and an average bias of 17.59 Wm -2. Furthermore, we also compare our product/algorithm with another satellite product (CERES-SYN) and two reanalysis products (MERRA and JRA55), and find that the accuracy of the much higher spatial resolution GLASS R n product is satisfactory. The GLASS R n product from 2000 to the present is operational and freely available to the public.« less

GEONEX: algorithm development and validation of Gross Primary Production from geostationary satellites

NASA Astrophysics Data System (ADS)

Hashimoto, H.; Wang, W.; Ganguly, S.; Li, S.; Michaelis, A.; Higuchi, A.; Takenaka, H.; Nemani, R. R.

2017-12-01

New geostationary sensors such as the AHI (Advanced Himawari Imager on Himawari-8) and the ABI (Advanced Baseline Imager on GOES-16) have the potential to advance ecosystem modeling particularly of diurnally varying phenomenon through frequent observations. These sensors have similar channels as in MODIS (MODerate resolution Imaging Spectroradiometer), and allow us to utilize the knowledge and experience in MODIS data processing. Here, we developed sub-hourly Gross Primary Production (GPP) algorithm, leverating the MODIS 17 GPP algorithm. We run the model at 1-km resolution over Japan and Australia using geo-corrected AHI data. Solar radiation was directly calculated from AHI using a neural network technique. The other necessary climate data were derived from weather stations and other satellite data. The sub-hourly estimates of GPP were first compared with ground-measured GPP at various Fluxnet sites. We also compared the AHI GPP with MODIS 17 GPP, and analyzed the differences in spatial patterns and the effect of diurnal changes in climate forcing. The sub-hourly GPP products require massive storage and strong computational power. We use NEX (NASA Earth Exchange) facility to produce the GPP products. This GPP algorithm can be applied to other geostationary satellites including GOES-16 in future.

GLASS daytime all-wave net radiation product: Algorithm development and preliminary validation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiang, Bo; Liang, Shunlin; Ma, Han

Mapping surface all-wave net radiation (R n) is critically needed for various applications. Several existing R n products from numerical models and satellite observations have coarse spatial resolutions and their accuracies may not meet the requirements of land applications. In this study, we develop the Global LAnd Surface Satellite (GLASS) daytime R n product at a 5 km spatial resolution. Its algorithm for converting shortwave radiation to all-wave net radiation using the Multivariate Adaptive Regression Splines (MARS) model is determined after comparison with three other algorithms. The validation of the GLASS R n product based on high-quality in situ measurementsmore » in the United States shows a coefficient of determination value of 0.879, an average root mean square error value of 31.61 Wm -2, and an average bias of 17.59 Wm -2. Furthermore, we also compare our product/algorithm with another satellite product (CERES-SYN) and two reanalysis products (MERRA and JRA55), and find that the accuracy of the much higher spatial resolution GLASS R n product is satisfactory. The GLASS R n product from 2000 to the present is operational and freely available to the public.« less

Optimal slew path planning for the Sino-French Space-based multiband astronomical Variable Objects Monitor mission

NASA Astrophysics Data System (ADS)

She, Yuchen; Li, Shuang

2018-01-01

The planning algorithm to calculate a satellite's optimal slew trajectory with a given keep-out constraint is proposed. An energy-optimal formulation is proposed for the Space-based multiband astronomical Variable Objects Monitor Mission Analysis and Planning (MAP) system. The innovative point of the proposed planning algorithm lies in that the satellite structure and control limitation are not considered as optimization constraints but are formulated into the cost function. This modification is able to relieve the burden of the optimizer and increases the optimization efficiency, which is the major challenge for designing the MAP system. Mathematical analysis is given to prove that there is a proportional mapping between the formulation and the satellite controller output. Simulations with different scenarios are given to demonstrate the efficiency of the developed algorithm.

Path planning on satellite images for unmanned surface vehicles

NASA Astrophysics Data System (ADS)

Yang, Joe-Ming; Tseng, Chien-Ming; Tseng, P. S.

2015-01-01

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

NOSS Altimeter Detailed Algorithm specifications

NASA Technical Reports Server (NTRS)

Hancock, D. W.; Mcmillan, J. D.

1982-01-01

The details of the algorithms and data sets required for satellite radar altimeter data processing are documented in a form suitable for (1) development of the benchmark software and (2) coding the operational software. The algorithms reported in detail are those established for altimeter processing. The algorithms which required some additional development before documenting for production were only scoped. The algorithms are divided into two levels of processing. The first level converts the data to engineering units and applies corrections for instrument variations. The second level provides geophysical measurements derived from altimeter parameters for oceanographic users.

Heuristic approach to Satellite Range Scheduling with Bounds using Lagrangian Relaxation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, Nathanael J. K.; Arguello, Bryan; Nozick, Linda Karen

This paper focuses on scheduling antennas to track satellites using a heuristic method. In order to validate the performance of the heuristic, bounds are developed using Lagrangian relaxation. The performance of the algorithm is established using several illustrative problems.

Early Detection of Rapidly Developing Cumulus Area using HIMAWARI-8

NASA Astrophysics Data System (ADS)

Yamada, Y.; Kadosaki, G.

2017-12-01

In recent years, many disasters have been occured by influence of meteorological change in Japan. So, it becomes more important to inform rapid weather change caused by cumulus which brings concentrated heavy rain/hail, wind gust, lightning in a short period. These severe events should inclease in the future by global warming. Therefore we are developping the alert system for Rapidly Developing Cumulus Area (RDCA) detection using Japanese new satellite. At July 2015, Japan Meteorological Agency started operation of new geostationary meteorological satellite "Himawari-8". This satellite has optical imager named Advanced Himawari Imager (AHI). It can observe Japan area every 2.5 minutes. The frequently infrared image with high resolution (2km) is the key of our alert system. We took some special functions in the algorithm of this system. One of the points is cloud location which shifts to north from true location around Japan by viewing angle from the satellite above the equator. We moved clouds to the correct position using geometric correction method according to its height and latitude. This algorithm also follows a movement of cloud every 2.5 minutes during several observations. It derives the information about degree of the development of cumulus. The prototype system gives the alert before 30 to 60 minutes in advance to the first lightning in typical cumulus case. However, we understand that there are some difficult cases to alert. For example, winter low cloud over the Japan Sea which brings a winter lightning, and tornado (although it is not cumulus). Now, we are adjusting some parameters of the algorithm. In the near future, our algorithm will be used in weather information delivery service to the customer.

Use of NTRIP for optimizing the decoding algorithm for real-time data streams.

PubMed

He, Zhanke; Tang, Wenda; Yang, Xuhai; Wang, Liming; Liu, Jihua

2014-10-10

As a network transmission protocol, Networked Transport of RTCM via Internet Protocol (NTRIP) is widely used in GPS and Global Orbiting Navigational Satellite System (GLONASS) Augmentation systems, such as Continuous Operational Reference System (CORS), Wide Area Augmentation System (WAAS) and Satellite Based Augmentation Systems (SBAS). With the deployment of BeiDou Navigation Satellite system(BDS) to serve the Asia-Pacific region, there are increasing needs for ground monitoring of the BeiDou Navigation Satellite system and the development of the high-precision real-time BeiDou products. This paper aims to optimize the decoding algorithm of NTRIP Client data streams and the user authentication strategies of the NTRIP Caster based on NTRIP. The proposed method greatly enhances the handling efficiency and significantly reduces the data transmission delay compared with the Federal Agency for Cartography and Geodesy (BKG) NTRIP. Meanwhile, a transcoding method is proposed to facilitate the data transformation from the BINary EXchange (BINEX) format to the RTCM format. The transformation scheme thus solves the problem of handing real-time data streams from Trimble receivers in the BeiDou Navigation Satellite System indigenously developed by China.

Implementation of a state of the art automated system for the production of cloud/water vapor motion winds from geostationary satellites

NASA Technical Reports Server (NTRS)

Velden, Christopher

1995-01-01

The research objectives in this proposal were part of a continuing program at UW-CIMSS to develop and refine an automated geostationary satellite winds processing system which can be utilized in both research and operational environments. The majority of the originally proposed tasks were successfully accomplished, and in some cases the progress exceeded the original goals. Much of the research and development supported by this grant resulted in upgrades and modifications to the existing automated satellite winds tracking algorithm. These modifications were put to the test through case study demonstrations and numerical model impact studies. After being successfully demonstrated, the modifications and upgrades were implemented into the NESDIS algorithms in Washington DC, and have become part of the operational support. A major focus of the research supported under this grant attended to the continued development of water vapor tracked winds from geostationary observations. The fully automated UW-CIMSS tracking algorithm has been tuned to provide complete upper-tropospheric coverage from this data source, with data set quality close to that of operational cloud motion winds. Multispectral water vapor observations were collected and processed from several different geostationary satellites. The tracking and quality control algorithms were tuned and refined based on ground-truth comparisons and case studies involving impact on numerical model analyses and forecasts. The results have shown the water vapor motion winds are of good quality, complement the cloud motion wind data, and can have a positive impact in NWP on many meteorological scales.

Global satellite composites - 20 years of evolution

NASA Astrophysics Data System (ADS)

Kohrs, Richard A.; Lazzara, Matthew A.; Robaidek, Jerrold O.; Santek, David A.; Knuth, Shelley L.

2014-01-01

For two decades, the University of Wisconsin Space Science and Engineering Center (SSEC) and the Antarctic Meteorological Research Center (AMRC) have been creating global, regional and hemispheric satellite composites. These composites have proven useful in research, operational forecasting, commercial applications and educational outreach. Using the Man computer Interactive Data System (McIDAS) software developed at SSEC, infrared window composites were created by combining Geostationary Operational Environmental Satellite (GOES), and polar orbiting data from the SSEC Data Center and polar data acquired at McMurdo and Palmer stations, Antarctica. Increased computer processing speed has allowed for more advanced algorithms to address the decision making process for co-located pixels. The algorithms have evolved from a simplistic maximum brightness temperature to those that account for distance from the sub-satellite point, parallax displacement, pixel time and resolution. The composites are the state-of-the-art means for merging/mosaicking satellite imagery.

Total ozone column derived from GOME and SCIAMACHY using KNMI retrieval algorithms: Validation against Brewer measurements at the Iberian Peninsula

NASA Astrophysics Data System (ADS)

Antón, M.; Kroon, M.; López, M.; Vilaplana, J. M.; Bañón, M.; van der A, R.; Veefkind, J. P.; Stammes, P.; Alados-Arboledas, L.

2011-11-01

This article focuses on the validation of the total ozone column (TOC) data set acquired by the Global Ozone Monitoring Experiment (GOME) and the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) satellite remote sensing instruments using the Total Ozone Retrieval Scheme for the GOME Instrument Based on the Ozone Monitoring Instrument (TOGOMI) and Total Ozone Retrieval Scheme for the SCIAMACHY Instrument Based on the Ozone Monitoring Instrument (TOSOMI) retrieval algorithms developed by the Royal Netherlands Meteorological Institute. In this analysis, spatially colocated, daily averaged ground-based observations performed by five well-calibrated Brewer spectrophotometers at the Iberian Peninsula are used. The period of study runs from January 2004 to December 2009. The agreement between satellite and ground-based TOC data is excellent (R2 higher than 0.94). Nevertheless, the TOC data derived from both satellite instruments underestimate the ground-based data. On average, this underestimation is 1.1% for GOME and 1.3% for SCIAMACHY. The SCIAMACHY-Brewer TOC differences show a significant solar zenith angle (SZA) dependence which causes a systematic seasonal dependence. By contrast, GOME-Brewer TOC differences show no significant SZA dependence and hence no seasonality although processed with exactly the same algorithm. The satellite-Brewer TOC differences for the two satellite instruments show a clear and similar dependence on the viewing zenith angle under cloudy conditions. In addition, both the GOME-Brewer and SCIAMACHY-Brewer TOC differences reveal a very similar behavior with respect to the satellite cloud properties, being cloud fraction and cloud top pressure, which originate from the same cloud algorithm (Fast Retrieval Scheme for Clouds from the Oxygen A-Band (FRESCO+)) in both the TOSOMI and TOGOMI retrieval algorithms.

Cooperative network clustering and task allocation for heterogeneous small satellite network

NASA Astrophysics Data System (ADS)

Qin, Jing

The research of small satellite has emerged as a hot topic in recent years because of its economical prospects and convenience in launching and design. Due to the size and energy constraints of small satellites, forming a small satellite network(SSN) in which all the satellites cooperate with each other to finish tasks is an efficient and effective way to utilize them. In this dissertation, I designed and evaluated a weight based dominating set clustering algorithm, which efficiently organizes the satellites into stable clusters. The traditional clustering algorithms of large monolithic satellite networks, such as formation flying and satellite swarm, are often limited on automatic formation of clusters. Therefore, a novel Distributed Weight based Dominating Set(DWDS) clustering algorithm is designed to address the clustering problems in the stochastically deployed SSNs. Considering the unique features of small satellites, this algorithm is able to form the clusters efficiently and stably. In this algorithm, satellites are separated into different groups according to their spatial characteristics. A minimum dominating set is chosen as the candidate cluster head set based on their weights, which is a weighted combination of residual energy and connection degree. Then the cluster heads admit new neighbors that accept their invitations into the cluster, until the maximum cluster size is reached. Evaluated by the simulation results, in a SSN with 200 to 800 nodes, the algorithm is able to efficiently cluster more than 90% of nodes in 3 seconds. The Deadline Based Resource Balancing (DBRB) task allocation algorithm is designed for efficient task allocations in heterogeneous LEO small satellite networks. In the task allocation process, the dispatcher needs to consider the deadlines of the tasks as well as the residue energy of different resources for best energy utilization. We assume the tasks adopt a Map-Reduce framework, in which a task can consist of multiple subtasks. The DBRB algorithm is deployed on the head node of a cluster. It gathers the status from each cluster member and calculates their Node Importance Factors (NIFs) from the carried resources, residue power and compute capacity. The algorithm calculates the number of concurrent subtasks based on the deadlines, and allocates the subtasks to the nodes according to their NIF values. The simulation results show that when cluster members carry multiple resources, resource are more balanced and rare resources serve longer in DBRB than in the Earliest Deadline First algorithm. We also show that the algorithm performs well in service isolation by serving multiple tasks with different deadlines. Moreover, the average task response time with various cluster size settings is well controlled within deadlines as well. Except non-realtime tasks, small satellites may execute realtime tasks as well. The location-dependent tasks, such as image capturing, data transmission and remote sensing tasks are realtime tasks that are required to be started / finished on specific time. The resource energy balancing algorithm for realtime and non-realtime mixed workload is developed to efficiently schedule the tasks for best system performance. It calculates the residue energy for each resource type and tries to preserve resources and node availability when distributing tasks. Non-realtime tasks can be preempted by realtime tasks to provide better QoS to realtime tasks. I compared the performance of proposed algorithm with a random-priority scheduling algorithm, with only realtime tasks, non-realtime tasks and mixed tasks. It shows the resource energy reservation algorithm outperforms the latter one with both balanced and imbalanced workloads. Although the resource energy balancing task allocation algorithm for mixed workload provides preemption mechanism for realtime tasks, realtime tasks can still fail due to resource exhaustion. For LEO small satellite flies around the earth on stable orbits, the location-dependent realtime tasks can be considered as periodical tasks. Therefore, it is possible to reserve energy for these realtime tasks. The resource energy reservation algorithm preserves energy for the realtime tasks when the execution routine of periodical realtime tasks is known. In order to reserve energy for tasks starting very early in each period that the node does not have enough energy charged, an energy wrapping mechanism is also designed to calculate the residue energy from the previous period. The simulation results show that without energy reservation, realtime task failure rate can reach more than 60% when the workload is highly imbalanced. In contrast, the resource energy reservation produces zero RT task failures and leads to equal or better aggregate system throughput than the non-reservation algorithm. The proposed algorithm also preserves more energy because it avoids task preemption. (Abstract shortened by ProQuest.).

Early Examples from the Integrated Multi-Satellite Retrievals for GPM (IMERG)

NASA Astrophysics Data System (ADS)

Huffman, George; Bolvin, David; Braithwaite, Daniel; Hsu, Kuolin; Joyce, Robert; Kidd, Christopher; Sorooshian, Soroosh; Xie, Pingping

2014-05-01

The U.S. GPM Science Team's Day-1 algorithm for computing combined precipitation estimates as part of GPM is the Integrated Multi-satellitE Retrievals for GPM (IMERG). The goal is to compute the best time series of (nearly) global precipitation from "all" precipitation-relevant satellites and global surface precipitation gauge analyses. IMERG is being developed as a unified U.S. algorithm drawing on strengths in the three contributing groups, whose previous work includes: 1) the TRMM Multi-satellite Precipitation Analysis (TMPA); 2) the CPC Morphing algorithm with Kalman Filtering (K-CMORPH); and 3) the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS). We review the IMERG design and development, plans for testing, and current status. Some of the lessons learned in running and reprocessing the previous data sets include the importance of quality-controlling input data sets, strategies for coping with transitions in the various input data sets, and practical approaches to retrospective analysis of multiple output products (namely the real- and post-real-time data streams). IMERG output will be illustrated using early test data, including the variety of supporting fields, such as the merged-microwave and infrared estimates, and the precipitation type. We end by considering recent changes in input data specifications, the transition from TRMM-based calibration to GPM-based, and further "Day 2" development.

Tomographic inversion of satellite photometry

NASA Technical Reports Server (NTRS)

Solomon, S. C.; Hays, P. B.; Abreu, V. J.

1984-01-01

An inversion algorithm capable of reconstructing the volume emission rate of thermospheric airglow features from satellite photometry has been developed. The accuracy and resolution of this technique are investigated using simulated data, and the inversions of several sets of observations taken by the Visible Airglow Experiment are presented.

Satellite remote sensing of harmful algal blooms: A new multi-algorithm method for detecting the Florida Red Tide (Karenia brevis).

PubMed

Carvalho, Gustavo A; Minnett, Peter J; Fleming, Lora E; Banzon, Viva F; Baringer, Warner

2010-06-01

In a continuing effort to develop suitable methods for the surveillance of Harmful Algal Blooms (HABs) of Karenia brevis using satellite radiometers, a new multi-algorithm method was developed to explore whether improvements in the remote sensing detection of the Florida Red Tide was possible. A Hybrid Scheme was introduced that sequentially applies the optimized versions of two pre-existing satellite-based algorithms: an Empirical Approach (using water-leaving radiance as a function of chlorophyll concentration) and a Bio-optical Technique (using particulate backscatter along with chlorophyll concentration). The long-term evaluation of the new multi-algorithm method was performed using a multi-year MODIS dataset (2002 to 2006; during the boreal Summer-Fall periods - July to December) along the Central West Florida Shelf between 25.75°N and 28.25°N. Algorithm validation was done with in situ measurements of the abundances of K. brevis; cell counts ≥1.5×10(4) cells l(-1) defined a detectable HAB. Encouraging statistical results were derived when either or both algorithms correctly flagged known samples. The majority of the valid match-ups were correctly identified (~80% of both HABs and non-blooming conditions) and few false negatives or false positives were produced (~20% of each). Additionally, most of the HAB-positive identifications in the satellite data were indeed HAB samples (positive predictive value: ~70%) and those classified as HAB-negative were almost all non-bloom cases (negative predictive value: ~86%). These results demonstrate an excellent detection capability, on average ~10% more accurate than the individual algorithms used separately. Thus, the new Hybrid Scheme could become a powerful tool for environmental monitoring of K. brevis blooms, with valuable consequences including leading to the more rapid and efficient use of ships to make in situ measurements of HABs.

Satellite remote sensing of harmful algal blooms: A new multi-algorithm method for detecting the Florida Red Tide (Karenia brevis)

PubMed Central

Carvalho, Gustavo A.; Minnett, Peter J.; Fleming, Lora E.; Banzon, Viva F.; Baringer, Warner

2010-01-01

In a continuing effort to develop suitable methods for the surveillance of Harmful Algal Blooms (HABs) of Karenia brevis using satellite radiometers, a new multi-algorithm method was developed to explore whether improvements in the remote sensing detection of the Florida Red Tide was possible. A Hybrid Scheme was introduced that sequentially applies the optimized versions of two pre-existing satellite-based algorithms: an Empirical Approach (using water-leaving radiance as a function of chlorophyll concentration) and a Bio-optical Technique (using particulate backscatter along with chlorophyll concentration). The long-term evaluation of the new multi-algorithm method was performed using a multi-year MODIS dataset (2002 to 2006; during the boreal Summer-Fall periods – July to December) along the Central West Florida Shelf between 25.75°N and 28.25°N. Algorithm validation was done with in situ measurements of the abundances of K. brevis; cell counts ≥1.5×104 cells l−1 defined a detectable HAB. Encouraging statistical results were derived when either or both algorithms correctly flagged known samples. The majority of the valid match-ups were correctly identified (~80% of both HABs and non-blooming conditions) and few false negatives or false positives were produced (~20% of each). Additionally, most of the HAB-positive identifications in the satellite data were indeed HAB samples (positive predictive value: ~70%) and those classified as HAB-negative were almost all non-bloom cases (negative predictive value: ~86%). These results demonstrate an excellent detection capability, on average ~10% more accurate than the individual algorithms used separately. Thus, the new Hybrid Scheme could become a powerful tool for environmental monitoring of K. brevis blooms, with valuable consequences including leading to the more rapid and efficient use of ships to make in situ measurements of HABs. PMID:21037979

Satellite-Based Stratospheric and Tropospheric Measurements: Determination of Global Ozone and other Trace Species

NASA Technical Reports Server (NTRS)

Chance, K. V.

2001-01-01

This report summarizes research done under NASA Grant NAG5-3461 from November 1, 1996 through December 31, 2000. The research performed during this reporting period includes development and maintenance of scientific software for the GOME retrieval algorithms, consultation on operational software development for GOME, sensitivity and instrument studies to help finalize the definition of the SCIAMACHY instrument, leading the development of the SCIAMACHY Scientific Requirements Document for Data and Algorithm Development, consultation and development for SCIAMACHY near-real-time (NRT) and off-line (OL) data products, radiative transfer model development for utilization in GOME, SCIAMACHY and other programs, development of infrared line-by-line atmospheric modeling and retrieval capability for SCIAMACHY, and participation in GOME and SCIAMACHY validation studies. The Global Ozone Monitoring Experiment was successfully launched on the ERS-2 satellite on April 20, 1995, and remains working in normal fashion. SCIAMACHY is currently planned for launch in late 2001 on the ESA Envisat satellite. Three GOME-2 instruments are now scheduled to fly on the Metop series of operational meteorological satellites (Eumetsat). K. Chance is a member of the reconstituted GOME Scientific Advisory Group, which will guide the GOME-2 program as well as the continuing ERS-2 GOME program.

Swarm satellite mission scheduling & planning using Hybrid Dynamic Mutation Genetic Algorithm

NASA Astrophysics Data System (ADS)

Zheng, Zixuan; Guo, Jian; Gill, Eberhard

2017-08-01

Space missions have traditionally been controlled by operators from a mission control center. Given the increasing number of satellites for some space missions, generating a command list for multiple satellites can be time-consuming and inefficient. Developing multi-satellite, onboard mission scheduling & planning techniques is, therefore, a key research field for future space mission operations. In this paper, an improved Genetic Algorithm (GA) using a new mutation strategy is proposed as a mission scheduling algorithm. This new mutation strategy, called Hybrid Dynamic Mutation (HDM), combines the advantages of both dynamic mutation strategy and adaptive mutation strategy, overcoming weaknesses such as early convergence and long computing time, which helps standard GA to be more efficient and accurate in dealing with complex missions. HDM-GA shows excellent performance in solving both unconstrained and constrained test functions. The experiments of using HDM-GA to simulate a multi-satellite, mission scheduling problem demonstrates that both the computation time and success rate mission requirements can be met. The results of a comparative test between HDM-GA and three other mutation strategies also show that HDM has outstanding performance in terms of speed and reliability.

Concept design and cluster control of advanced space connectable intelligent microsatellite

NASA Astrophysics Data System (ADS)

Wang, Xiaohui; Li, Shuang; She, Yuchen

2017-12-01

In this note, a new type of advanced space connectable intelligent microsatellite is presented to extend the range of potential application of microsatellite and improve the efficiency of cooperation. First, the overall concept of the micro satellite cluster is described, which is characterized by autonomously connecting with each other and being able to realize relative rotation through the external interfaces. Second, the multi-satellite autonomous assembly algorithm and control algorithm of the cluster motion are developed to make the cluster system combine into a variety of configurations in order to achieve different types of functionality. Finally, the design of the satellite cluster system is proposed, and the possible applications are discussed.

A review of ocean color remote sensing methods and statistical techniques for the detection, mapping and analysis of phytoplankton blooms in coastal and open oceans

NASA Astrophysics Data System (ADS)

Blondeau-Patissier, David; Gower, James F. R.; Dekker, Arnold G.; Phinn, Stuart R.; Brando, Vittorio E.

2014-04-01

The need for more effective environmental monitoring of the open and coastal ocean has recently led to notable advances in satellite ocean color technology and algorithm research. Satellite ocean color sensors' data are widely used for the detection, mapping and monitoring of phytoplankton blooms because earth observation provides a synoptic view of the ocean, both spatially and temporally. Algal blooms are indicators of marine ecosystem health; thus, their monitoring is a key component of effective management of coastal and oceanic resources. Since the late 1970s, a wide variety of operational ocean color satellite sensors and algorithms have been developed. The comprehensive review presented in this article captures the details of the progress and discusses the advantages and limitations of the algorithms used with the multi-spectral ocean color sensors CZCS, SeaWiFS, MODIS and MERIS. Present challenges include overcoming the severe limitation of these algorithms in coastal waters and refining detection limits in various oceanic and coastal environments. To understand the spatio-temporal patterns of algal blooms and their triggering factors, it is essential to consider the possible effects of environmental parameters, such as water temperature, turbidity, solar radiation and bathymetry. Hence, this review will also discuss the use of statistical techniques and additional datasets derived from ecosystem models or other satellite sensors to characterize further the factors triggering or limiting the development of algal blooms in coastal and open ocean waters.

An algorithm for estimating aerosol optical depth from HIMAWARI-8 data over Ocean

NASA Astrophysics Data System (ADS)

Lee, Kwon Ho

2016-04-01

The paper presents currently developing algorithm for aerosol detection and retrieval over ocean for the next generation geostationary satellite, HIMAWARI-8. Enhanced geostationary remote sensing observations are now enables for aerosol retrieval of dust, smoke, and ash, which began a new era of geostationary aerosol observations. Sixteen channels of the Advanced HIMAWARI Imager (AHI) onboard HIMAWARI-8 offer capabilities for aerosol remote sensing similar to those currently provided by the Moderate Resolution Imaging Spectroradiometer (MODIS). Aerosols were estimated in detection processing from visible and infrared channel radiances, and in retrieval processing using the inversion-optimization of satellite-observed radiances with those calculated from radiative transfer model. The retrievals are performed operationally every ten minutes for pixel sizes of ~8 km. The algorithm currently under development uses a multichannel approach to estimate the effective radius, aerosol optical depth (AOD) simultaneously. The instantaneous retrieved AOD is evaluated by the MODIS level 2 operational aerosol products (C006), and the daily retrieved AOD was compared with ground-based measurements from the AERONET databases. The results show that the detection of aerosol and estimated AOD are in good agreement with the MODIS data and ground measurements with a correlation coefficient of ˜0.90 and a bias of 4%. These results suggest that the proposed method applied to the HIMAWARI-8 satellite data can accurately estimate continuous AOD. Acknowledgments This work was supported by "Development of Geostationary Meteorological Satellite Ground Segment(NMSC-2014-01)" program funded by National Meteorological Satellite Centre(NMSC) of Korea Meteorological Administration(KMA).

Advancements of in-flight mass moment of inertia and structural deflection algorithms for satellite attitude simulators

NASA Astrophysics Data System (ADS)

Wright, Jonathan W.

Experimental satellite attitude simulators have long been used to test and analyze control algorithms in order to drive down risk before implementation on an operational satellite. Ideally, the dynamic response of a terrestrial-based experimental satellite attitude simulator would be similar to that of an on-orbit satellite. Unfortunately, gravitational disturbance torques and poorly characterized moments of inertia introduce uncertainty into the system dynamics leading to questionable attitude control algorithm experimental results. This research consists of three distinct, but related contributions to the field of developing robust satellite attitude simulators. In the first part of this research, existing approaches to estimate mass moments and products of inertia are evaluated followed by a proposition and evaluation of a new approach that increases both the accuracy and precision of these estimates using typical on-board satellite sensors. Next, in order to better simulate the micro-torque environment of space, a new approach to mass balancing satellite attitude simulator is presented, experimentally evaluated, and verified. Finally, in the third area of research, we capitalize on the platform improvements to analyze a control moment gyroscope (CMG) singularity avoidance steering law. Several successful experiments were conducted with the CMG array at near-singular configurations. An evaluation process was implemented to verify that the platform remained near the desired test momentum, showing that the first two components of this research were effective in allowing us to conduct singularity avoidance experiments in a representative space-like test environment.

Web-Based Library and Algorithm System for Satellite and Airborne Image Products

DTIC Science & Technology

2011-01-01

the spectrum matching approach to inverting hyperspectral imagery created by Drs. C. Mobley ( Sequoia Scientific) and P. Bissett (FERI). 5...matching algorithms developed by Sequoia Scientific and FERI. Testing and Implementation of Library This project will result in the delivery of a...transitioning VSW algorithms developed by Dr. Curtis D. Mobley at Sequoia Scientific, Inc., and Dr. Paul Bissett at FERI, under other 6.1/6.2 program funding.

An Environment for Hardware-in-the-Loop Formation Navigation and Control Simulation

NASA Technical Reports Server (NTRS)

Burns, Rich

2004-01-01

Recent interest in formation flying satellite systems has spurred a considerable amount of research in the relative navigation and control of satellites. Development in this area has included new estimation and control algorithms as well as sensor and actuator development specifically geared toward the relative control problem. This paper describes a simulation facility, the Formation Flying Testbed (FFTB) at NASA's Goddard Space Flight Center, which allows engineers to test new algorithms for the formation flying problem with relevant GN&C hardware in a closed loop simulation. The FFTB currently supports the injection of GPS receiver hardware into the simulation loop, and support for satellite crosslink ranging technology is at a prototype stage. This closed-loop, hardware inclusive simulation capability permits testing of navigation and control software in the presence of the actual hardware with which the algorithms must interact. This capability provides the navigation or control developer with a perspective on how the algorithms perform as part of the closed-loop system. In this paper, the overall design and evolution of the FFTB are presented. Each component of the FFTB is then described in detail. Interfaces between the components of the FFTB are shown and the interfaces to and between navigation and control software are described in detail. Finally, an example of closed-loop formation control with GPS receivers in the loop is presented and results are analyzed.

A satellite AOT derived from the ground sky transmittance measurements

NASA Astrophysics Data System (ADS)

Lim, H. S.; MatJafri, M. Z.; Abdullah, K.; Tan, K. C.; Wong, C. J.; Saleh, N. Mohd.

2008-10-01

The optical properties of aerosols such as smoke from burning vary due to aging processes and these particles reach larger sizes at high concentrations. The objectives of this study are to develop and evaluate an algorithm for estimating atmospheric optical thickness from Landsat TM image. This study measured the sky transmittance at the ground using a handheld spectroradiometer in a wide wavelength spectrum to retrieve atmospheric optical thickness. The in situ measurement of atmospheric transmittance data were collected simultaneously with the acquisition of remotely sensed satellite data. The digital numbers for the three visible bands corresponding to the in situ locations were extracted and then converted into reflectance values. The reflectance measured from the satellite was subtracted by the amount given by the surface reflectance to obtain the atmospheric reflectance. These atmospheric reflectance values were used for calibration of the AOT algorithm. This study developed an empirical method to estimate the AOT values from the sky transmittance values. Finally, a AOT map was generated using the proposed algorithm and colour-coded for visual interpretation.

Improved candidate generation and coverage analysis methods for design optimization of symmetric multi-satellite constellations

NASA Astrophysics Data System (ADS)

Matossian, Mark G.

1997-01-01

Much attention in recent years has focused on commercial telecommunications ventures involving constellations of spacecraft in low and medium Earth orbit. These projects often require investments on the order of billions of dollars (US$) for development and operations, but surprisingly little work has been published on constellation design optimization for coverage analysis, traffic simulation and launch sequencing for constellation build-up strategies. This paper addresses the two most critical aspects of constellation orbital design — efficient constellation candidate generation and coverage analysis. Inefficiencies and flaws in the current standard algorithm for constellation modeling are identified, and a corrected and improved algorithm is presented. In the 1970's, John Walker and G. V. Mozhaev developed innovative strategies for continuous global coverage using symmetric non-geosynchronous constellations. (These are sometimes referred to as rosette, or Walker constellations. An example is pictured above.) In 1980, the late Arthur Ballard extended and generalized the work of Walker into a detailed algorithm for the NAVSTAR/GPS program, which deployed a 24 satellite symmetric constellation. Ballard's important contribution was published in his "Rosette Constellations of Earth Satellites."

The SASS scattering coefficient algorithm. [Seasat-A Satellite Scatterometer

NASA Technical Reports Server (NTRS)

Bracalente, E. M.; Grantham, W. L.; Boggs, D. H.; Sweet, J. L.

1980-01-01

This paper describes the algorithms used to convert engineering unit data obtained from the Seasat-A satellite scatterometer (SASS) to radar scattering coefficients and associated supporting parameters. A description is given of the instrument receiver and related processing used by the scatterometer to measure signal power backscattered from the earth's surface. The applicable radar equation used for determining scattering coefficient is derived. Sample results of SASS data processed through current algorithm development facility (ADF) scattering coefficient algorithms are presented which include scattering coefficient values for both water and land surfaces. Scattering coefficient signatures for these two surface types are seen to have distinctly different characteristics. Scattering coefficient measurements of the Amazon rain forest indicate the usefulness of this type of data as a stable calibration reference target.

An automatic editing algorithm for GPS data

NASA Technical Reports Server (NTRS)

Blewitt, Geoffrey

1990-01-01

An algorithm has been developed to edit automatically Global Positioning System data such that outlier deletion, cycle slip identification, and correction are independent of clock instability, selective availability, receiver-satellite kinematics, and tropospheric conditions. This algorithm, called TurboEdit, operates on undifferenced, dual frequency carrier phase data, and requires the use of P code pseudorange data and a smoothly varying ionospheric electron content. TurboEdit was tested on the large data set from the CASA Uno experiment, which contained over 2500 cycle slips.Analyst intervention was required on 1 percent of the station-satellite passes, almost all of these problems being due to difficulties in extrapolating variations in the ionospheric delay. The algorithm is presently being adapted for real time data editing in the Rogue receiver for continuous monitoring applications.

Global navigation satellite system receiver for weak signals under all dynamic conditions

NASA Astrophysics Data System (ADS)

Ziedan, Nesreen Ibrahim

The ability of the Global Navigation Satellite System (GNSS) receiver to work under weak signal and various dynamic conditions is required in some applications. For example, to provide a positioning capability in wireless devices, or orbit determination of Geostationary and high Earth orbit satellites. This dissertation develops Global Positioning System (GPS) receiver algorithms for such applications. Fifteen algorithms are developed for the GPS C/A signal. They cover all the receiver main functions, which include acquisition, fine acquisition, bit synchronization, code and carrier tracking, and navigation message decoding. They are integrated together, and they can be used in any software GPS receiver. They also can be modified to fit any other GPS or GNSS signals. The algorithms have new capabilities. The processing and memory requirements are considered in the design to allow the algorithms to fit the limited resources of some applications; they do not require any assisting information. Weak signals can be acquired in the presence of strong interfering signals and under high dynamic conditions. The fine acquisition, bit synchronization, and tracking algorithms are based on the Viterbi algorithm and Extended Kalman filter approaches. The tracking algorithms capabilities increase the time to lose lock. They have the ability to adaptively change the integration length and the code delay separation. More than one code delay separation can be used in the same time. Large tracking errors can be detected and then corrected by a re-initialization and an acquisition-like algorithms. Detecting the navigation message is needed to increase the coherent integration; decoding it is needed to calculate the navigation solution. The decoding algorithm utilizes the message structure to enable its decoding for signals with high Bit Error Rate. The algorithms are demonstrated using simulated GPS C/A code signals, and TCXO clocks. The results have shown the algorithms ability to reliably work with 15 dB-Hz signals and acceleration over 6 g.

Use of GOES, SSM/I, TRMM Satellite Measurements Estimating Water Budget Variations in Gulf of Mexico - Caribbean Sea Basins

NASA Technical Reports Server (NTRS)

Smith, Eric A.

2004-01-01

This study presents results from a multi-satellite/multi-sensor retrieval system designed to obtain the atmospheric water budget over the open ocean. A combination of 3ourly-sampled monthly datasets derived from the GOES-8 5-channel Imager, the TRMM TMI radiometer, and the DMSP 7-channel passive microwave radiometers (SSM/I) have been acquired for the combined Gulf of Mexico-Caribbean Sea basin. Whereas the methodology has been tested over this basin, the retrieval system is designed for portability to any open-ocean region. Algorithm modules using the different datasets to retrieve individual geophysical parameters needed in the water budget equation are designed in a manner that takes advantage of the high temporal resolution of the GOES-8 measurements, as well as the physical relationships inherent to the TRMM and SSM/I passive microwave measurements in conjunction with water vapor, cloud liquid water, and rainfall. The methodology consists of retrieving the precipitation, surface evaporation, and vapor-cloud water storage terms in the atmospheric water balance equation from satellite techniques, with the water vapor advection term being obtained as the residue needed for balance. Thus, the intent is to develop a purely satellite-based method for obtaining the full set of terms in the atmospheric water budget equation without requiring in situ sounding information on the wind profile. The algorithm is validated by cross-checking all the algorithm components through multiple- algorithm retrieval intercomparisons. A further check on the validation is obtained by directly comparing water vapor transports into the targeted basin diagnosed from the satellite algorithms to those obtained observationally from a network of land-based upper air stations that nearly uniformly surround the basin, although it is fair to say that these checks are more effective m identifying problems in estimating vapor transports from a leaky operational radiosonde network than in verifying the transport estimates determined from the satellite algorithm system Total columnar atmospheric water budget results are presented for an extended annual cycle consisting of the months of October-97, January-98, April-98, July-98,October-98, and January 1999. These results are used to emphasize the changing relationship in E-P, as well as in the varying roles of storage and advection in balancing E-P both on daily and monthly time scales and on localized and basin space scales. Results from the algorithm-to-algorithm intercomparisons are also presented in the context of sensitivity testing to help understand the intrinsic uncertainties in evaluating the water budget terms by an all-satellite algorithm approach.

Monthly-Diurnal Water Budget Variability Over Gulf of Mexico-Caribbean Sea Basin from Satellite Observations

NASA Technical Reports Server (NTRS)

Smith, E. A.; Santos, P.

2006-01-01

This study presents results from a multi-satellite/multi-sensor retrieval system design d to obtain the atmospheric water budget over the open ocean. A combination of hourly-sampled monthly datasets derived from the GOES-8 5-channel Imager, the TRMM TMI radiometer, and the DMSP 7-channel passive microwave radiometers (SSM/I) have been acquired for the combined Gulf of Mexico-Caribbean Sea basin. Whereas the methodology has been tested over this basin, the retrieval system is designed for portability to any open-ocean region. Algorithm modules using the different datasets to retrieve individual geophysical parameters needed in the water budget equation are designed in a manner that takes advantage of the high temporal resolution of the GOES-8 measurements, as well as the physical relationships inherent to the TRMM and SSM/I passive microwave measurements in conjunction with water vapor, cloud liquid water, and rainfall. The methodology consists of retrieving the precipitation, surface evaporation, and vapor-cloud water storage terms in the atmospheric water balance equation from satellite techniques, with the water vapor advection term being obtained as the residue needed for balance. Thus, the intent is to develop a purely satellite-based method for obtaining the full set of terms in the atmospheric water budget equation without requiring in situ sounding information on the wind profile. The algorithm is validated by cross-checking all the algorithm components through multiple-algorithm retrieval intercomparisons. A further check on the validation is obtained by directly comparing water vapor transports into the targeted basin diagnosed from the satellite algorithms to those obtained observationally from a network of land-based upper air stations that nearly uniformly surround the basin, although it is fair to say that these checks are more effective in identifying problems in estimating vapor transports from a "leaky" operational radiosonde network than in verifying the transport estimates determined from the satellite algorithm system. Total columnar atmospheric water budget results are presented for an extended annual cycle consisting of the months of October-97, January-98, April-98, July-98,October-98, and January- 1999. These results are used to emphasize the changing relationship in E-P, as well as in the varying roles of storage and advection in balancing E-P both on daily and monthly time scales and on localized and basin space scales. Results from the algorithm-to-algorithm intercomparisons are also presented in the context of sensitivity testing to help understand the intrinsic uncertainties in evaluating the water budget terms by an all-satellite algorithm approach.

Infrared Algorithm Development for Ocean Observations with EOS/MODIS

NASA Technical Reports Server (NTRS)

Brown, Otis B.

1997-01-01

Efforts continue under this contract to develop algorithms for the computation of sea surface temperature (SST) from MODIS infrared measurements. This effort includes radiative transfer modeling, comparison of in situ and satellite observations, development and evaluation of processing and networking methodologies for algorithm computation and data accession, evaluation of surface validation approaches for IR radiances, development of experimental instrumentation, and participation in MODIS (project) related activities. Activities in this contract period have focused on radiative transfer modeling, evaluation of atmospheric correction methodologies, undertake field campaigns, analysis of field data, and participation in MODIS meetings.

Bridging Ground Validation and Algorithms: Using Scattering and Integral Tables to Incorporate Observed DSD Correlations into Satellite Algorithms

NASA Astrophysics Data System (ADS)

Williams, C. R.

2012-12-01

The NASA Global Precipitation Mission (GPM) raindrop size distribution (DSD) Working Group is composed of NASA PMM Science Team Members and is charged to "investigate the correlations between DSD parameters using Ground Validation (GV) data sets that support, or guide, the assumptions used in satellite retrieval algorithms." Correlations between DSD parameters can be used to constrain the unknowns and reduce the degrees-of-freedom in under-constrained satellite algorithms. Over the past two years, the GPM DSD Working Group has analyzed GV data and has found correlations between the mass-weighted mean raindrop diameter (Dm) and the mass distribution standard deviation (Sm) that follows a power-law relationship. This Dm-Sm power-law relationship appears to be robust and has been observed in surface disdrometer and vertically pointing radar observations. One benefit of a Dm-Sm power-law relationship is that a three parameter DSD can be modeled with just two parameters: Dm and Nw that determines the DSD amplitude. In order to incorporate observed DSD correlations into satellite algorithms, the GPM DSD Working Group is developing scattering and integral tables that can be used by satellite algorithms. Scattering tables describe the interaction of electromagnetic waves on individual particles to generate cross sections of backscattering, extinction, and scattering. Scattering tables are independent of the distribution of particles. Integral tables combine scattering table outputs with DSD parameters and DSD correlations to generate integrated normalized reflectivity, attenuation, scattering, emission, and asymmetry coefficients. Integral tables contain both frequency dependent scattering properties and cloud microphysics. The GPM DSD Working Group has developed scattering tables for raindrops at both Dual Precipitation Radar (DPR) frequencies and at all GMI radiometer frequencies less than 100 GHz. Scattering tables include Mie and T-matrix scattering with H- and V-polarization at the instrument view angles of nadir to 17 degrees (for DPR) and 48 & 53 degrees off nadir (for GMI). The GPM DSD Working Group is generating integral tables with GV observed DSD correlations and is performing sensitivity and verification tests. One advantage of keeping scattering tables separate from integral tables is that research can progress on the electromagnetic scattering of particles independent of cloud microphysics research. Another advantage of keeping the tables separate is that multiple scattering tables will be needed for frozen precipitation. Scattering tables are being developed for individual frozen particles based on habit, density and operating frequency. And a third advantage of keeping scattering and integral tables separate is that this framework provides an opportunity to communicate GV findings about DSD correlations into integral tables, and thus, into satellite algorithms.

An Adaptive Low-Cost INS/GNSS Tightly-Coupled Integration Architecture Based on Redundant Measurement Noise Covariance Estimation.

PubMed

Li, Zheng; Zhang, Hai; Zhou, Qifan; Che, Huan

2017-09-05

The main objective of the introduced study is to design an adaptive Inertial Navigation System/Global Navigation Satellite System (INS/GNSS) tightly-coupled integration system that can provide more reliable navigation solutions by making full use of an adaptive Kalman filter (AKF) and satellite selection algorithm. To achieve this goal, we develop a novel redundant measurement noise covariance estimation (RMNCE) theorem, which adaptively estimates measurement noise properties by analyzing the difference sequences of system measurements. The proposed RMNCE approach is then applied to design both a modified weighted satellite selection algorithm and a type of adaptive unscented Kalman filter (UKF) to improve the performance of the tightly-coupled integration system. In addition, an adaptive measurement noise covariance expanding algorithm is developed to mitigate outliers when facing heavy multipath and other harsh situations. Both semi-physical simulation and field experiments were conducted to evaluate the performance of the proposed architecture and were compared with state-of-the-art algorithms. The results validate that the RMNCE provides a significant improvement in the measurement noise covariance estimation and the proposed architecture can improve the accuracy and reliability of the INS/GNSS tightly-coupled systems. The proposed architecture can effectively limit positioning errors under conditions of poor GNSS measurement quality and outperforms all the compared schemes.

An Adaptive Low-Cost INS/GNSS Tightly-Coupled Integration Architecture Based on Redundant Measurement Noise Covariance Estimation

PubMed Central

Li, Zheng; Zhang, Hai; Zhou, Qifan; Che, Huan

2017-01-01

The main objective of the introduced study is to design an adaptive Inertial Navigation System/Global Navigation Satellite System (INS/GNSS) tightly-coupled integration system that can provide more reliable navigation solutions by making full use of an adaptive Kalman filter (AKF) and satellite selection algorithm. To achieve this goal, we develop a novel redundant measurement noise covariance estimation (RMNCE) theorem, which adaptively estimates measurement noise properties by analyzing the difference sequences of system measurements. The proposed RMNCE approach is then applied to design both a modified weighted satellite selection algorithm and a type of adaptive unscented Kalman filter (UKF) to improve the performance of the tightly-coupled integration system. In addition, an adaptive measurement noise covariance expanding algorithm is developed to mitigate outliers when facing heavy multipath and other harsh situations. Both semi-physical simulation and field experiments were conducted to evaluate the performance of the proposed architecture and were compared with state-of-the-art algorithms. The results validate that the RMNCE provides a significant improvement in the measurement noise covariance estimation and the proposed architecture can improve the accuracy and reliability of the INS/GNSS tightly-coupled systems. The proposed architecture can effectively limit positioning errors under conditions of poor GNSS measurement quality and outperforms all the compared schemes. PMID:28872629

Genetic algorithm for investigating flight MH370 in Indian Ocean using remotely sensed data

NASA Astrophysics Data System (ADS)

Marghany, Maged; Mansor, Shattri; Shariff, Abdul Rashid Bin Mohamed

2016-06-01

This study utilized Genetic algorithm (GA) for automatic detection and simulation trajectory movements of flight MH370 debris. In doing so, the Ocean Surface Topography Mission(OSTM) on the Jason- 2 satellite have been used within 1 and half year covers data to simulate the pattern of Flight MH370 debris movements across the southern Indian Ocean. Further, multi-objectives evolutionary algorithm also used to discriminate uncertainty of flight MH370 imagined and detection. The study shows that the ocean surface current speed is 0.5 m/s. This current patterns have developed a large anticlockwise gyre over a water depth of 8,000 m. The multi-objectives evolutionary algorithm suggested that objects are existed on satellite data are not flight MH370 debris. In addition, multiobjectives evolutionary algorithm suggested that the difficulties to acquire the exact location of flight MH370 due to complicated hydrodynamic movements across the southern Indian Ocean.

Evolution of the JPSS Ground Project Calibration and Validation System

NASA Technical Reports Server (NTRS)

Purcell, Patrick; Chander, Gyanesh; Jain, Peyush

2016-01-01

The Joint Polar Satellite System (JPSS) is the National Oceanic and Atmospheric Administration's (NOAA) next-generation operational Earth observation Program that acquires and distributes global environmental data from multiple polar-orbiting satellites. The JPSS Program plays a critical role to NOAA's mission to understand and predict changes in weather, climate, oceans, coasts, and space environments, which supports the Nation's economy and protection of lives and property. The National Aeronautics and Space Administration (NASA) is acquiring and implementing the JPSS, comprised of flight and ground systems, on behalf of NOAA. The JPSS satellites are planned to fly in the afternoon orbit and will provide operational continuity of satellite-based observations and products for NOAA Polar-orbiting Operational Environmental Satellites (POES) and the Suomi National Polar-orbiting Partnership (SNPP) satellite. To support the JPSS Calibration and Validation (CalVal) node Government Resource for Algorithm Verification, Independent Test, and Evaluation (GRAVITE) services facilitate: Algorithm Integration and Checkout, Algorithm and Product Operational Tuning, Instrument Calibration, Product Validation, Algorithm Investigation, and Data Quality Support and Monitoring. GRAVITE is a mature, deployed system that currently supports the SNPP Mission and has been in operations since SNPP launch. This paper discusses the major re-architecture for Block 2.0 that incorporates SNPP lessons learned, architecture of the system, and demonstrates how GRAVITE has evolved as a system with increased performance. It is now a robust, stable, reliable, maintainable, scalable, and secure system that supports development, test, and production strings, replaces proprietary and custom software, uses open source software, and is compliant with NASA and NOAA standards.

Evolution of the JPSS Ground Project Calibration and Validation System

NASA Technical Reports Server (NTRS)

Chander, Gyanesh; Jain, Peyush

2014-01-01

The Joint Polar Satellite System (JPSS) is the National Oceanic and Atmospheric Administrations (NOAA) next-generation operational Earth observation Program that acquires and distributes global environmental data from multiple polar-orbiting satellites. The JPSS Program plays a critical role to NOAAs mission to understand and predict changes in weather, climate, oceans, coasts, and space environments, which supports the Nation’s economy and protection of lives and property. The National Aerospace and Atmospheric Administration (NASA) is acquiring and implementing the JPSS, comprised of flight and ground systems on behalf of NOAA. The JPSS satellites are planned to fly in the afternoon orbit and will provide operational continuity of satellite-based observations and products for NOAA Polar-orbiting Operational Environmental Satellites (POES) and the Suomi National Polar-orbiting Partnership (SNPP) satellite. To support the JPSS Calibration and Validation (CalVal) node Government Resource for Algorithm Verification, Independent Test, and Evaluation (GRAVITE) services facilitate: Algorithm Integration and Checkout, Algorithm and Product Operational Tuning, Instrument Calibration, Product Validation, Algorithm Investigation, and Data Quality Support and Monitoring. GRAVITE is a mature, deployed system that currently supports the SNPP Mission and has been in operations since SNPP launch. This paper discusses the major re-architecture for Block 2.0 that incorporates SNPP lessons learned, architecture of the system, and demonstrates how GRAVITE has evolved as a system with increased performance. It is now a robust, stable, reliable, maintainable, scalable, and secure system that supports development, test, and production strings, replaces proprietary and custom software, uses open source software, and is compliant with NASA and NOAA standards.

Congestion control and routing over satellite networks

NASA Astrophysics Data System (ADS)

Cao, Jinhua

Satellite networks and transmissions find their application in fields of computer communications, telephone communications, television broadcasting, transportation, space situational awareness systems and so on. This thesis mainly focuses on two networking issues affecting satellite networking: network congestion control and network routing optimization. Congestion, which leads to long queueing delays, packet losses or both, is a networking problem that has drawn the attention of many researchers. The goal of congestion control mechanisms is to ensure high bandwidth utilization while avoiding network congestion by regulating the rate at which traffic sources inject packets into a network. In this thesis, we propose a stable congestion controller using data-driven, safe switching control theory to improve the dynamic performance of satellite Transmission Control Protocol/Active Queue Management (TCP/AQM) networks. First, the stable region of the Proportional-Integral (PI) parameters for a nominal model is explored. Then, a PI controller, whose parameters are adaptively tuned by switching among members of a given candidate set, using observed plant data, is presented and compared with some classical AQM policy examples, such as Random Early Detection (RED) and fixed PI control. A new cost detectable switching law with an interval cost function switching algorithm, which improves the performance and also saves the computational cost, is developed and compared with a law commonly used in the switching control literature. Finite-gain stability of the system is proved. A fuzzy logic PI controller is incorporated as a special candidate to achieve good performance at all nominal points with the available set of candidate controllers. Simulations are presented to validate the theory. An effocient routing algorithm plays a key role in optimizing network resources. In this thesis, we briefly analyze Low Earth Orbit (LEO) satellite networks, review the Cross Entropy (CE) method and then develop a novel on-demand routing system named Cross Entropy Accelerated Ant Routing System (CEAARS) for regular constellation LEO satellite networks. By implementing simulations on an Iridium-like satellite network, we compare the proposed CEAARS algorithm with the two approaches to adaptive routing protocols on the Internet: distance-vector (DV) and link-state (LS), as well as with the original Cross Entropy Ant Routing System (CEARS). DV algorithms are based on distributed Bellman Ford algorithm, and LS algorithms are implementation of Dijkstras single source shortest path. The results show that CEAARS not only remarkably improves the convergence speed of achieving optimal or suboptimal paths, but also reduces the number of overhead ants (management packets).

The Day-1 GPM Combined Precipitation Algorithm: IMERG

NASA Astrophysics Data System (ADS)

Huffman, G. J.; Bolvin, D. T.; Braithwaite, D.; Hsu, K.; Joyce, R.; Kidd, C.; Sorooshian, S.; Xie, P.

2012-12-01

The Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG) algorithm will provide the at-launch combined-sensor precipitation dataset being produced by the U.S. GPM Science Team. IMERG is being developed as a unified U.S. algorithm that takes advantage of strengths in three current U.S. algorithms: - the TRMM Multi-satellite Precipitation Analysis (TMPA), which addresses inter-satellite calibration of precipitation estimates and monthly scale combination of satellite and gauge analyses; - the CPC Morphing algorithm with Kalman Filtering (KF-CMORPH), which provides quality-weighted time interpolation of precipitation patterns following storm motion; and - the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS), which provides a neural-network-based scheme for generating microwave-calibrated precipitation estimates from geosynchronous infrared brightness temperatures, and filters out some non-raining cold clouds. The goal is to provide a long-term, fine-scale record of global precipitation from the entire constellation of precipitation-relevant satellite sensors, with input from surface precipitation gauges. The record will begin January 1998 at the start of the Tropical Rainfall Measuring Mission (TRMM) and extend as GPM records additional data. Although homogeneity is considered desirable, the use of diverse and evolving data sources works against the strict long-term homogeneity that characterizes a Climate Data Record (CDR). This talk will briefly review the design requirements for IMERG, including multiple runs at different latencies (most likely around 4 hours, 12 hours, and 2 months after observation time), various intermediate data fields as part of the IMERG data file, and the plans to bring up IMERG with calibration by TRMM initially, transitioning to GPM when its individual-sensor precipitation algorithms are fully functional. Then we will present some early examples of IMERG data products and compare them with existing products to illustrate how the design of IMERG affects the overall performance of the algorithm.

Development of a validation model for the defense meteorological satellite program's special sensor microwave imager

NASA Technical Reports Server (NTRS)

Swift, C. T.; Goodberlet, M. A.; Wilkerson, J. C.

1990-01-01

The Defence Meteorological Space Program's (DMSP) Special Sensor Microwave/Imager (SSM/I), an operational wind speed algorithm was developed. The algorithm is based on the D-matrix approach which seeks a linear relationship between measured SSM/I brightness temperatures and environmental parameters. D-matrix performance was validated by comparing algorithm derived wind speeds with near-simultaneous and co-located measurements made by off-shore ocean buoys. Other topics include error budget modeling, alternate wind speed algorithms, and D-matrix performance with one or more inoperative SSM/I channels.

Satellite observation of particulate organic carbon dynamics in ...

EPA Pesticide Factsheets

Particulate organic carbon (POC) plays an important role in coastal carbon cycling and the formation of hypoxia. Yet, coastal POC dynamics are often poorly understood due to a lack of long-term POC observations and the complexity of coastal hydrodynamic and biogeochemical processes that influence POC sources and sinks. Using field observations and satellite ocean color products, we developed a nw multiple regression algorithm to estimate POC on the Louisiana Continental Shelf (LCS) from satellite observations. The algorithm had reliable performance with mean relative error (MRE) of ?40% and root mean square error (RMSE) of ?50% for MODIS and SeaWiFS images for POC ranging between ?80 and ?1200 mg m23, and showed similar performance for a large estuary (Mobile Bay). Substantial spatiotemporal variability in the satellite-derived POC was observed on the LCS, with high POC found on the inner shelf (<10 m depth) and lower POC on the middle (10–50 m depth) and outer shelf (50–200 m depth), and with high POC found in winter (January–March) and lower POC in summer to fall (August–October). Correlation analysis between long-term POC time series and several potential influencing factors indicated that river discharge played a dominant role in POC dynamics on the LCS, while wind and surface currents also affected POC spatial patterns on short time scales. This study adds another example where satellite data with carefully developed algorithms can greatly increase

Classification of Aerosol Retrievals from Spaceborne Polarimetry Using a Multiparameter Algorithm

NASA Technical Reports Server (NTRS)

Russell, Philip B.; Kacenelenbogen, Meloe; Livingston, John M.; Hasekamp, Otto P.; Burton, Sharon P.; Schuster, Gregory L.; Johnson, Matthew S.; Knobelspiesse, Kirk D.; Redemann, Jens; Ramachandran, S.;

Retrieval Algorithms for the Halogen Occultation Experiment

NASA Technical Reports Server (NTRS)

Thompson, Robert E.; Gordley, Larry L.

2009-01-01

The Halogen Occultation Experiment (HALOE) on the Upper Atmosphere Research Satellite (UARS) provided high quality measurements of key middle atmosphere constituents, aerosol characteristics, and temperature for 14 years (1991-2005). This report is an outline of the Level 2 retrieval algorithms, and it also describes the great care that was taken in characterizing the instrument prior to launch and throughout its mission life. It represents an historical record of the techniques used to analyze the data and of the steps that must be considered for the development of a similar experiment for future satellite missions.

Global positioning system network analysis with phase ambiguity resolution applied to crustal deformation studies in California

NASA Technical Reports Server (NTRS)

Dong, Da-Nan; Bock, Yehuda

1989-01-01

An efficient algorithm is developed for multisession adjustment of GPS data with simultaneous orbit determination and ambiguity resolution. Application of the algorithm to the analysis of data from a five-year campaign in progress in southern and central California to monitor tectonic motions using observations by GPS satellites, demonstrates improvements in estimates of station position and satellite orbits when the phase ambiguities are resolved. Most of the phase ambiguities in the GPS network were resolved, particularly for all the baselines of geophysical interest in California.

Plumes and Blooms: Observations, Analysis and Modeling for SIMBIOS

NASA Technical Reports Server (NTRS)

Maritorena, S.; Siegel, D. A.; Nelson, N. B.

2004-01-01

The goal of the Plumes and Blooms (PnB) project is to develop, validate and apply to imagery state-of-the-art ocean color algorithms for quantifying sediment plumes and phytoplankton blooms for the Case II environment of the Santa Barbara Channel. We conduct monthly to twice-monthly transect observations across the Santa Barbara Channel to develop an algorithm development and product validation data set. A primary goal is the use the PnB field data set to objectively tune semi-analytical models of ocean color for this site and apply them using available satellite imagery (SeaWiFS and MODIS). However, the comparison between PnB field observations and satellite estimates of primary products has been disappointing. We find that field estimates of water-leaving radiance correspond poorly to satellite estimates for both SeaWiFS and MODIS local area coverage imagery. We believe this is due to poor atmospheric correction due to complex mixtures of aerosol types found in these near-coastal regions.

Multi-Mission Remote Sensing of Suspended Particulate Matter and Diffuse Attenuation Coefficient in the Yangtze Estuarine and Coastal Waters

NASA Astrophysics Data System (ADS)

Yu, X.; Salama, S.; Shen, F.

2016-08-01

During the Dragon-3 project (ID: 10555) period, we developed and improved the atmospheric correction algorithms (AC) and retrieval models of suspended sediment concentration ( ) and diffuse attenuation coefficient ( ) for the Yangtze estuarine and coastal waters. The developed models were validated by measurements with consistently stable and fairly accurate estimations, reproducing reasonable distribution maps of and over the study area. Spatial-temporal variations of were presented and the mechanisms of the sediment transport were discussed. We further examined the compatibility of the developed AC algorithms and retrieval model and the consistency of satellite products for multi-sensor such as MODIS/Terra/Aqua, MERIS/Envisat, MERSI/ FY-3 and GOCI. The inter-comparison of multi- sensor suggested that different satellite products can be combined to increase revisit frequency and complement a temporal gap of time series satellites that may exist between on-orbit and off- orbit, facilitating a better monitor on the spatial- temporal dynamics of .

Arctic sea ice albedo - A comparison of two satellite-derived data sets

NASA Technical Reports Server (NTRS)

Schweiger, Axel J.; Serreze, Mark C.; Key, Jeffrey R.

1993-01-01

Spatial patterns of mean monthly surface albedo for May, June, and July, derived from DMSP Operational Line Scan (OLS) satellite imagery are compared with surface albedos derived from the International Satellite Cloud Climatology Program (ISCCP) monthly data set. Spatial patterns obtained by the two techniques are in general agreement, especially for June and July. Nevertheless, systematic differences in albedo of 0.05 - 0.10 are noted which are most likely related to uncertainties in the simple parameterizations used in the DMSP analyses, problems in the ISCCP cloud-clearing algorithm and other modeling simplifications. However, with respect to the eventual goal of developing a reliable automated retrieval algorithm for compiling a long-term albedo data base, these initial comparisons are very encouraging.

The Effect of Shadow Area on Sgm Algorithm and Disparity Map Refinement from High Resolution Satellite Stereo Images

NASA Astrophysics Data System (ADS)

Tatar, N.; Saadatseresht, M.; Arefi, H.

2017-09-01

Semi Global Matching (SGM) algorithm is known as a high performance and reliable stereo matching algorithm in photogrammetry community. However, there are some challenges using this algorithm especially for high resolution satellite stereo images over urban areas and images with shadow areas. As it can be seen, unfortunately the SGM algorithm computes highly noisy disparity values for shadow areas around the tall neighborhood buildings due to mismatching in these lower entropy areas. In this paper, a new method is developed to refine the disparity map in shadow areas. The method is based on the integration of potential of panchromatic and multispectral image data to detect shadow areas in object level. In addition, a RANSAC plane fitting and morphological filtering are employed to refine the disparity map. The results on a stereo pair of GeoEye-1 captured over Qom city in Iran, shows a significant increase in the rate of matched pixels compared to standard SGM algorithm.

Evaluation of Aerosol Pollution Determination From MODIS Satellite Retrievals for Semi-Arid Reno, NV, USA with In-Situ Measurements

NASA Astrophysics Data System (ADS)

Loria-Salazar, S. Marcela

The aim of the present work is to carry out a detailed analysis of ground and columnar aerosol properties obtained by in-situ Photoacoustic and Integrated Nephelometer (PIN), Cimel CE-318 sunphotometer and MODIS instrument onboard Aqua and Terra satellites, for semi-arid Reno, Nevada, USA in the local summer months of 2012. Satellite determination of local aerosol pollution is desirable because of the potential for broad spatial and temporal coverage. However, retrieval of quantitative measures of air pollution such as Aerosol Optical Depth (AOD) from satellite measurements is challenging because of the underlying surface albedo being heterogeneous in space and time. Therefore, comparisons of satellite retrievals with measurements from ground-based sun photometers are crucial for validation, testing, and further development of instruments and retrieval algorithms. Ground-based sunphotometry and in-situ ground observations show that seasonal weather changes and fire plumes have great influence on the atmosphere aerosol optics. The Apparent Optical Height (AOH) follows the shape of the development of the Convective Boundary Layer (CBL) when fire conditions were not present. However, significant fine particle optical depth was inferred beyond the CBL thereby complicating the use of remote sensing measurements for near-ground aerosol pollution measurements. A meteorological analysis was performed to help diagnose the nature of the aerosols above Reno. The calculation of a Zephyr index and back trajectory analysis demonstrated that a local circulation often induces aerosol transport from Northern CA over the Sierra Nevada Mountains that doubles the Aerosol Optical Depth (AOD) at 500 nm. Sunphotometer measurements were used as a `ground truth' for satellite retrievals to evaluate the current state of the science retrievals in this challenging location. Satellite retrieved for AOD showed the presence of wild fires in Northern CA during August. AOD retrieved using the "dark-target algorithm" may be unrealistically high over the Great Basin. Low correlation was found between AERONET AOD and dark-target algorithm AOD retrievals from Aqua and Terra during June and July. During fire conditions the dark-target algorithm AOD values correlated better with AERONET measurements in August. Use of the Deep-blue algorithm for MODIS data to retrieve AOD did not provide enough points to compare with AERONET in June and July. In August, AOD from deep-blue and AERONET retrievals exhibited low correlation. AEE from MODIS products and AERONET exhibited low correlation during every month. Apparently satellite AOD retrievals need much improvement for areas like semi-arid Reno.

Performance of the Falling Snow Retrieval Algorithms for the Global Precipitation Measurement (GPM) Mission

NASA Technical Reports Server (NTRS)

Skofronick-Jackson, Gail; Munchak, Stephen J.; Ringerud, Sarah

2016-01-01

Retrievals of falling snow from space represent an important data set for understanding the Earth's atmospheric, hydrological, and energy cycles, especially during climate change. Estimates of falling snow must be captured to obtain the true global precipitation water cycle, snowfall accumulations are required for hydrological studies, and without knowledge of the frozen particles in clouds one cannot adequately understand the energy and radiation budgets. While satellite-based remote sensing provides global coverage of falling snow events, the science is relatively new and retrievals are still undergoing development with challenges remaining). This work reports on the development and testing of retrieval algorithms for the Global Precipitation Measurement (GPM) mission Core Satellite, launched February 2014.

Double regions growing algorithm for automated satellite image mosaicking

NASA Astrophysics Data System (ADS)

Tan, Yihua; Chen, Chen; Tian, Jinwen

2011-12-01

Feathering is a most widely used method in seamless satellite image mosaicking. A simple but effective algorithm - double regions growing (DRG) algorithm, which utilizes the shape content of images' valid regions, is proposed for generating robust feathering-line before feathering. It works without any human intervention, and experiment on real satellite images shows the advantages of the proposed method.

A strategy for recovering continuous behavioral telemetry data from Pacific walruses

USGS Publications Warehouse

Fischbach, Anthony S.; Jay, Chadwick V.

2016-01-01

Tracking animal behavior and movement with telemetry sensors can offer substantial insights required for conservation. Yet, the value of data collected by animal-borne telemetry systems is limited by bandwidth constraints. To understand the response of Pacific walruses (Odobenus rosmarus divergens) to rapid changes in sea ice availability, we required continuous geospatial chronologies of foraging behavior. Satellite telemetry offered the only practical means to systematically collect such data; however, data transmission constraints of satellite data-collection systems limited the data volume that could be acquired. Although algorithms exist for reducing sensor data volumes for efficient transmission, none could meet our requirements. Consequently, we developed an algorithm for classifying hourly foraging behavior status aboard a tag with limited processing power. We found a 98% correspondence of our algorithm's classification with a test classification based on time–depth data recovered and characterized through multivariate analysis in a separate study. We then applied our algorithm within a telemetry system that relied on remotely deployed satellite tags. Data collected by these tags from Pacific walruses across their range during 2007–2015 demonstrated the consistency of foraging behavior collected by this strategy with data collected by data logging tags; and demonstrated the ability to collect geospatial behavioral chronologies with minimal missing data where recovery of data logging tags is precluded. Our strategy for developing a telemetry system may be applicable to any study requiring intelligent algorithms to continuously monitor behavior, and then compress those data into meaningful information that can be efficiently transmitted.

Statistically Optimized Inversion Algorithm for Enhanced Retrieval of Aerosol Properties from Spectral Multi-Angle Polarimetric Satellite Observations

NASA Technical Reports Server (NTRS)

Dubovik, O; Herman, M.; Holdak, A.; Lapyonok, T.; Taure, D.; Deuze, J. L.; Ducos, F.; Sinyuk, A.

2011-01-01

The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns) that is not common in satellite observations. The POLDER imager on board the PARASOL microsatellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of all available angular observations obtained by the POLDER sensor in the window spectral channels where absorption by gas is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed at retrieval of extended set of parameters affecting measured radiation.

Spheres: from Ground Development to ISS Operations

NASA Technical Reports Server (NTRS)

Katterhagen, A.

2016-01-01

SPHERES (Synchronized Position Hold Engage and Reorient Experimental Satellites) is an internal International Space Station (ISS) Facility that supports multiple investigations for the development of multi-spacecraft and robotic control algorithms. The SPHERES National Lab Facility aboard ISS is managed and operated by NASA Ames Research Center (ARC) at Moffett Field California. The SPHERES Facility on ISS consists of three self-contained eight-inch diameter free-floating satellites which perform the various flight algorithms and serve as a platform to support the integration of experimental hardware. SPHERES has served to mature the adaptability of control algorithms of future formation flight missions in microgravity (6 DOF (Degrees of Freedom) / long duration microgravity), demonstrate key close-proximity formation flight and rendezvous and docking maneuvers, understand fault diagnosis and recovery, improve the field of human telerobotic operation and control, and lessons learned on ISS have significant impact on ground robotics, mapping, localization, and sensing in three-dimensions - among several other areas of study.

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

NASA Astrophysics Data System (ADS)

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. Collaboration with GCOM-W is not only limited to its participation to GPM constellation but also coordination in areas of algorithm development and validation in Japan. Generation of high-temporal and high-accurate global rainfall map is one of targets of the GPM mission. As a proto-type for GPM era, JAXA has developed and operates the Global Precipitation Map algorithm in near-real-time since October 2008, and hourly and 0.1-degree resolution binary data and images available at http://sharaku.eorc.jaxa.jp/GSMaP/ four hours after observation. The algorithms are based on outcomes from the Global Satellite Mapping for Precipitation (GSMaP) project, which was sponsored by the Japan Science and Technology Agency (JST) under the Core Research for Evolutional Science and Technology (CREST) framework between 2002 and 2007 (Okamoto et al., 2005; Aonashi et al., 2009; Ushio et al., 2009). Target of GSMaP project is to produce global rainfall maps that are highly accurate and in high temporal and spatial resolution through the development of rain rate retrieval algorithms based on reliable precipitation physical models by using several microwave radiometer data, and comprehensive use of precipitation radar and geostationary infrared imager data. Near-real-time GSMaP data is distributed via internet and utilized by end users. Purpose of data utilization by each user covers broad areas and in world wide; Science researches (model validation, data assimilation, typhoon study, etc.), weather forecast/service, flood warning and rain analysis over river basin, oceanographic condition forecast, agriculture, and education. Toward the GPM era, operational application should be further emphasized as well as science application. JAXA continues collaboration with hydrological communities to utilize satellite-based precipitation data as inputs to future flood prediction and warning system, as well as with meteorological agencies to proceed further data utilization in numerical weather prediction system and forecasts.

NASA's K/Ka-Band Broadband Aeronautical Terminal for Duplex Satellite Video Communications

NASA Technical Reports Server (NTRS)

Densmore, A.; Agan, M.

1994-01-01

JPL has recently begun the development of a Broadband Aeronautical Terminal (BAT) for duplex video satellite communications on commercial or business class aircraft. The BAT is designed for use with NASA's K/Ka-band Advanced Communications Technology Satellite (ACTS). The BAT system will provide the systems and technology groundwork for an eventual commercial K/Ka-band aeronautical satellite communication system. With industry/government partnerships, three main goals will be addressed by the BAT task: 1) develop, characterize and demonstrate the performance of an ACTS based high data rate aeronautical communications system; 2) assess the performance of current video compression algorithms in an aeronautical satellite communication link; and 3) characterize the propagation effects of the K/Ka-band channel for aeronautical communications.

System engineering approach to GPM retrieval algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rose, C. R.; Chandrasekar, V.

2004-01-01

System engineering principles and methods are very useful in large-scale complex systems for developing the engineering requirements from end-user needs. Integrating research into system engineering is a challenging task. The proposed Global Precipitation Mission (GPM) satellite will use a dual-wavelength precipitation radar to measure and map global precipitation with unprecedented accuracy, resolution and areal coverage. The satellite vehicle, precipitation radars, retrieval algorithms, and ground validation (GV) functions are all critical subsystems of the overall GPM system and each contributes to the success of the mission. Errors in the radar measurements and models can adversely affect the retrieved output values. Groundmore » validation (GV) systems are intended to provide timely feedback to the satellite and retrieval algorithms based on measured data. These GV sites will consist of radars and DSD measurement systems and also have intrinsic constraints. One of the retrieval algorithms being studied for use with GPM is the dual-wavelength DSD algorithm that does not use the surface reference technique (SRT). The underlying microphysics of precipitation structures and drop-size distributions (DSDs) dictate the types of models and retrieval algorithms that can be used to estimate precipitation. Many types of dual-wavelength algorithms have been studied. Meneghini (2002) analyzed the performance of single-pass dual-wavelength surface-reference-technique (SRT) based algorithms. Mardiana (2003) demonstrated that a dual-wavelength retrieval algorithm could be successfully used without the use of the SRT. It uses an iterative approach based on measured reflectivities at both wavelengths and complex microphysical models to estimate both No and Do at each range bin. More recently, Liao (2004) proposed a solution to the Do ambiguity problem in rain within the dual-wavelength algorithm and showed a possible melting layer model based on stratified spheres. With the No and Do calculated at each bin, the rain rate can then be calculated based on a suitable rain-rate model. This paper develops a system engineering interface to the retrieval algorithms while remaining cognizant of system engineering issues so that it can be used to bridge the divide between algorithm physics an d overall mission requirements. Additionally, in line with the systems approach, a methodology is developed such that the measurement requirements pass through the retrieval model and other subsystems and manifest themselves as measurement and other system constraints. A systems model has been developed for the retrieval algorithm that can be evaluated through system-analysis tools such as MATLAB/Simulink.« less

Application of Satellite Data for Early Season Assessment of Fallowed Agricultural Lands for Drought Impact Reporting

NASA Astrophysics Data System (ADS)

Rosevelt, C.; Melton, F. S.; Johnson, L.; Verdin, J. P.; Thenkabail, P. S.; mueller, R.; Zakzeski, A.; Jones, J.

2013-12-01

Rapid assessment of drought impacts can aid water managers in assessing mitigation options, and guide decision making with respect to requests for local water transfers, county drought disaster designations, or state emergency proclamations. Satellite remote sensing offers an efficient way to provide quantitative assessments of drought impacts on agricultural production and land fallowing associated with reductions in water supply. A key advantage of satellite-based assessments is that they can provide a measure of land fallowing that is consistent across both space and time. Here we describe an approach for monthly mapping of land fallowing developed as part of a joint effort by USGS, USDA, and NASA to provide timely assessments of land fallowing during drought events. This effort has used the Central Valley of California as a pilot region for development and testing of an operational approach. To provide quantitative measures of fallowed land from satellite data early in the season, we developed a decision tree algorithm and applied it to timeseries of normalized difference vegetation index (NDVI) data from Landsat TM, ETM+, and MODIS. Our effort has been focused on development of leading indicators of drought impacts in the March - June timeframe based on measures of crop development patterns relative to a reference period with average or above average rainfall. This capability complements ongoing work by USDA to produce and publicly release within-season estimates of fallowed acreage from the USDA Cropland Data Layer. To assess the accuracy of the algorithms, monthly ground validation surveys were conducted along transects across the Central Valley at more than 200 fields per month from March - June, 2013. Here we present the algorithm for mapping fallowed acreage early in the season along with results from the accuracy assessment, and discuss potential applications to other regions.

Remote Sensing Applications to Water Quality Management in Florida

NASA Astrophysics Data System (ADS)

Lehrter, J. C.; Schaeffer, B. A.; Hagy, J.; Spiering, B.; Barnes, B.; Hu, C.; Le, C.; McEachron, L.; Underwood, L. W.; Ellis, C.; Fisher, B.

2013-12-01

Optical datasets from estuarine and coastal systems are increasingly available for remote sensing algorithm development, validation, and application. With validated algorithms, the data streams from satellite sensors can provide unprecedented spatial and temporal data for local and regional coastal water quality management. Our presentation will highlight two recent applications of optical data and remote sensing to water quality decision-making in coastal regions of the state of Florida; (1) informing the development of estuarine and coastal nutrient criteria for the state of Florida and (2) informing the rezoning of the Florida Keys National Marine Sanctuary. These efforts involved building up the underlying science to demonstrate the applicability of satellite data as well as an outreach component to educate decision-makers about the use, utility, and uncertainties of remote sensing data products. Scientific developments included testing existing algorithms and generating new algorithms for water clarity and chlorophylla in case II (CDOM or turbidity dominated) estuarine and coastal waters and demonstrating the accuracy of remote sensing data products in comparison to traditional field based measurements. Including members from decision-making organizations on the research team and interacting with decision-makers early and often in the process were key factors for the success of the outreach efforts and the eventual adoption of satellite data into the data records and analyses used in decision-making. Florida coastal water bodies (black boxes) for which remote sensing imagery were applied to derive numeric nutrient criteria and in situ observations (black dots) used to validate imagery. Florida ocean color applied to development of numeric nutrient criteria

Comparison of four machine learning algorithms for their applicability in satellite-based optical rainfall retrievals

NASA Astrophysics Data System (ADS)

Meyer, Hanna; Kühnlein, Meike; Appelhans, Tim; Nauss, Thomas

2016-03-01

Machine learning (ML) algorithms have successfully been demonstrated to be valuable tools in satellite-based rainfall retrievals which show the practicability of using ML algorithms when faced with high dimensional and complex data. Moreover, recent developments in parallel computing with ML present new possibilities for training and prediction speed and therefore make their usage in real-time systems feasible. This study compares four ML algorithms - random forests (RF), neural networks (NNET), averaged neural networks (AVNNET) and support vector machines (SVM) - for rainfall area detection and rainfall rate assignment using MSG SEVIRI data over Germany. Satellite-based proxies for cloud top height, cloud top temperature, cloud phase and cloud water path serve as predictor variables. The results indicate an overestimation of rainfall area delineation regardless of the ML algorithm (averaged bias = 1.8) but a high probability of detection ranging from 81% (SVM) to 85% (NNET). On a 24-hour basis, the performance of the rainfall rate assignment yielded R2 values between 0.39 (SVM) and 0.44 (AVNNET). Though the differences in the algorithms' performance were rather small, NNET and AVNNET were identified as the most suitable algorithms. On average, they demonstrated the best performance in rainfall area delineation as well as in rainfall rate assignment. NNET's computational speed is an additional advantage in work with large datasets such as in remote sensing based rainfall retrievals. However, since no single algorithm performed considerably better than the others we conclude that further research in providing suitable predictors for rainfall is of greater necessity than an optimization through the choice of the ML algorithm.

Assessment of satellite retrieval algorithms for chlorophyll-a concentration under high solar zenith angle

NASA Astrophysics Data System (ADS)

Li, Hao; He, Xianqiang; Bai, Yan; Chen, Xiaoyan; Gong, Fang; Zhu, Qiankun; Hu, Zifeng

2016-10-01

Numerous empirical algorithms have been operationally used to retrieve the global ocean chlorophyll-a concentration (Chla) from ocean color satellite data, e.g., the OC4V4 algorithm for SeaWiFS and OC3M for MODIS. However, the algorithms have been established and validated based on the in situ data mainly measured under low to moderate solar zenith angle (<70°). Currently, with the development of the geostationary satellite ocean color remote sensing which observes from early morning to later afternoon, it is necessary to know whether the empirical Chla algorithms could be applied to high solar zenith angle. In this study, the performances of seven widely-used Chla algorithms under high solar zenith angles, i.e., OC2, OC3M, OC3V, OC4V4, CLARK, OCI, and YOC algorithms, were evaluated using the NOMAD global in situ ocean color dataset. The results showed that the performances of all the seven algorithms decreased significantly under high solar zenith angles as compared to those under low-moderate solar zenith angles. For instance, for the OC4V4 algorithm, the relative percent difference (RPD) and root-mean-square error (RMSE) were 13.78% and 1.66 μg/l for the whole dataset, and 3.95% and 1.49 μg/l for the solar zenith angles ranged from 30° to 40°, respectively. However, the RPD and RMSE increased to 30.45% and 6.10μg/l for solar zenith angle larger than 70°.

Towards an integrated strategy for monitoring wetland inundation with virtual constellations of optical and radar satellites

NASA Astrophysics Data System (ADS)

DeVries, B.; Huang, W.; Huang, C.; Jones, J. W.; Lang, M. W.; Creed, I. F.; Carroll, M.

2017-12-01

The function of wetlandscapes in hydrological and biogeochemical cycles is largely governed by surface inundation, with small wetlands that experience periodic inundation playing a disproportionately large role in these processes. However, the spatial distribution and temporal dynamics of inundation in these wetland systems are still poorly understood, resulting in large uncertainties in global water, carbon and greenhouse gas budgets. Satellite imagery provides synoptic and repeat views of the Earth's surface and presents opportunities to fill this knowledge gap. Despite the proliferation of Earth Observation satellite missions in the past decade, no single satellite sensor can simultaneously provide the spatial and temporal detail needed to adequately characterize inundation in small, dynamic wetland systems. Surface water data products must therefore integrate observations from multiple satellite sensors in order to address this objective, requiring the development of improved and coordinated algorithms to generate consistent estimates of surface inundation. We present a suite of algorithms designed to detect surface inundation in wetlands using data from a virtual constellation of optical and radar sensors comprising the Landsat and Sentinel missions (DeVries et al., 2017). Both optical and radar algorithms were able to detect inundation in wetlands without the need for external training data, allowing for high-efficiency monitoring of wetland inundation at large spatial and temporal scales. Applying these algorithms across a gradient of wetlands in North America, preliminary findings suggest that while these fully automated algorithms can detect wetland inundation at higher spatial and temporal resolutions than currently available surface water data products, limitations specific to the satellite sensors and their acquisition strategies are responsible for uncertainties in inundation estimates. Further research is needed to investigate strategies for integrating optical and radar data from virtual constellations, with a focus on reducing uncertainties, maximizing spatial and temporal detail, and establishing consistent records of wetland inundation over time. The findings and conclusions in this article do not necessarily represent the views of the U.S. Government.

Clustering of tethered satellite system simulation data by an adaptive neuro-fuzzy algorithm

NASA Technical Reports Server (NTRS)

Mitra, Sunanda; Pemmaraju, Surya

1992-01-01

Recent developments in neuro-fuzzy systems indicate that the concepts of adaptive pattern recognition, when used to identify appropriate control actions corresponding to clusters of patterns representing system states in dynamic nonlinear control systems, may result in innovative designs. A modular, unsupervised neural network architecture, in which fuzzy learning rules have been embedded is used for on-line identification of similar states. The architecture and control rules involved in Adaptive Fuzzy Leader Clustering (AFLC) allow this system to be incorporated in control systems for identification of system states corresponding to specific control actions. We have used this algorithm to cluster the simulation data of Tethered Satellite System (TSS) to estimate the range of delta voltages necessary to maintain the desired length rate of the tether. The AFLC algorithm is capable of on-line estimation of the appropriate control voltages from the corresponding length error and length rate error without a priori knowledge of their membership functions and familarity with the behavior of the Tethered Satellite System.

A prospective approach to coastal geography from satellite. [technological forecasting

NASA Technical Reports Server (NTRS)

Munday, J. C., Jr.

1981-01-01

A forecasting protocol termed the "prospective approach' was used to examine probable futures relative to coastal applications of satellite data. Significant variables include the energy situation, the national economy, national Earth satellite programs, and coastal zone research, commercial activity, and regulatory activity. Alternative scenarios for the period until 1986 are presented. Possible response by state/local remote sensing centers include operational applications for users, input to geo-base information systems (GIS), development of decision-making algorithms using GIS data, and long term research programs for coastal management using merged satellite and traditional data.

Spatial and Temporal Varying Thresholds for Cloud Detection in Satellite Imagery

NASA Technical Reports Server (NTRS)

Jedlovec, Gary; Haines, Stephanie

2007-01-01

A new cloud detection technique has been developed and applied to both geostationary and polar orbiting satellite imagery having channels in the thermal infrared and short wave infrared spectral regions. The bispectral composite threshold (BCT) technique uses only the 11 micron and 3.9 micron channels, and composite imagery generated from these channels, in a four-step cloud detection procedure to produce a binary cloud mask at single pixel resolution. A unique aspect of this algorithm is the use of 20-day composites of the 11 micron and the 11 - 3.9 micron channel difference imagery to represent spatially and temporally varying clear-sky thresholds for the bispectral cloud tests. The BCT cloud detection algorithm has been applied to GOES and MODIS data over the continental United States over the last three years with good success. The resulting products have been validated against "truth" datasets (generated by the manual determination of the sky conditions from available satellite imagery) for various seasons from the 2003-2005 periods. The day and night algorithm has been shown to determine the correct sky conditions 80-90% of the time (on average) over land and ocean areas. Only a small variation in algorithm performance occurs between day-night, land-ocean, and between seasons. The algorithm performs least well. during he winter season with only 80% of the sky conditions determined correctly. The algorithm was found to under-determine clouds at night and during times of low sun angle (in geostationary satellite data) and tends to over-determine the presence of clouds during the day, particularly in the summertime. Since the spectral tests use only the short- and long-wave channels common to most multispectral scanners; the application of the BCT technique to a variety of satellite sensors including SEVERI should be straightforward and produce similar performance results.

Benchmarking In-Flight Icing Detection Products for Future Upgrades

NASA Technical Reports Server (NTRS)

Politovich, M. K.; Minnis, P.; Johnson, D. B.; Wolff, C. A.; Chapman, M.; Heck, P. W.; Haggerty, J. A.

2004-01-01

This paper summarizes the results of a benchmarking exercise conducted as part of the NASA supported Advanced Satellite Aviation-Weather Products (ASAP) Program. The goal of ASAP is to increase and optimize the use of satellite data sets within the existing FAA Aviation Weather Research Program (AWRP) Product Development Team (PDT) structure and to transfer advanced satellite expertise to the PDTs. Currently, ASAP fosters collaborative efforts between NASA Laboratories, the University of Wisconsin Cooperative Institute for Meteorological Satellite Studies (UW-CIMSS), the University of Alabama in Huntsville (UAH), and the AWRP PDTs. This collaboration involves the testing and evaluation of existing satellite algorithms developed or proposed by AWRP teams, the introduction of new techniques and data sets to the PDTs from the satellite community, and enhanced access to new satellite data sets available through CIMSS and NASA Langley Research Center for evaluation and testing.

Bidirectional reflectance correction model for coastal water and its application to minimization of uncertainties in satellite and in-situ water leaving radiances at Long Island Sound Coastal Observatory site

NASA Astrophysics Data System (ADS)

Hlaing, Soe Min

Ocean Color data validation is the absolute requirement to provide the steady and reliable Ocean Color data stream. In the validation of Ocean Color data, water-leaving radiances, retrieved from in situ or satellite measurements, need to be compared in very accurate manner. Both in-situ and satellite data to be used in the comparisons are required to be the representative of the typical water and environmental condition at the site without being affected by the unexpected natural and environmental perturbation. As the result, assessments of the uncertainties in the water leaving radiance data must be carried out in the measurement and the every step of data processing procedure. With the hyper- and multi-spectral water leaving radiance data retrieved for the different viewing geometries of the instruments at the Long Island Sound Coastal Observatory (LISCO), uncertainties in the water leaving radiance data and processing procedures have been assessed and quantified. Recommendations and algorithm improvements have been also made to reduce the uncertainties in the processing and validation of Ocean Color data. Particularly, remote sensing reflectance model to correct the bidirectional angular dependencies in both in-situ and satellite data have been proposed. The proposed model is first validated with a one year time series of in situ above-water measurements acquired by collocated multi- and hyper-spectral radiometers which have different viewing geometries installed at LISCO. Match-ups and inter-comparisons performed on these concurrent measurements show that the proposed algorithm outperforms the algorithm currently in use at all wavelengths, with spectral average improvement of 2.4%. LISCO's time series data has also been used to evaluate improvements in the match-up comparisons of MODIS satellite data when the proposed Bidirectional Reflectance Distribution Function (BRDF) correction is used in lieu of the current algorithm. It has been shown that the discrepancies between coincident in-situ sea-based and satellite data were decreased by 3.15% with the use of the proposed algorithm. Possibility of the application of the developed BRDF algorithm for the open ocean conditions is also considered.

IDMA-Based MAC Protocol for Satellite Networks with Consideration on Channel Quality

PubMed Central

2014-01-01

In order to overcome the shortcomings of existing medium access control (MAC) protocols based on TDMA or CDMA in satellite networks, interleave division multiple access (IDMA) technique is introduced into satellite communication networks. Therefore, a novel wide-band IDMA MAC protocol based on channel quality is proposed in this paper, consisting of a dynamic power allocation algorithm, a rate adaptation algorithm, and a call admission control (CAC) scheme. Firstly, the power allocation algorithm combining the technique of IDMA SINR-evolution and channel quality prediction is developed to guarantee high power efficiency even in terrible channel conditions. Secondly, the effective rate adaptation algorithm, based on accurate channel information per timeslot and by the means of rate degradation, can be realized. What is more, based on channel quality prediction, the CAC scheme, combining the new power allocation algorithm, rate scheduling, and buffering strategies together, is proposed for the emerging IDMA systems, which can support a variety of traffic types, and offering quality of service (QoS) requirements corresponding to different priority levels. Simulation results show that the new wide-band IDMA MAC protocol can make accurate estimation of available resource considering the effect of multiuser detection (MUD) and QoS requirements of multimedia traffic, leading to low outage probability as well as high overall system throughput. PMID:25126592

Guidance and Control System for a Satellite Constellation

NASA Technical Reports Server (NTRS)

Bryson, Jonathan Lamar; Cox, James; Mays, Paul Richard; Neidhoefer, James Christian; Ephrain, Richard

2010-01-01

A distributed guidance and control algorithm was developed for a constellation of satellites. The system repositions satellites as required, regulates satellites to desired orbits, and prevents collisions. 1. Optimal methods are used to compute nominal transfers from orbit to orbit. 2. Satellites are regulated to maintain the desired orbits once the transfers are complete. 3. A simulator is used to predict potential collisions or near-misses. 4. Each satellite computes perturbations to its controls so as to increase any unacceptable distances of nearest approach to other objects. a. The avoidance problem is recast in a distributed and locally-linear form to arrive at a tractable solution. b. Plant matrix values are approximated via simulation at each time step. c. The Linear Quadratic Gaussian (LQG) method is used to compute perturbations to the controls that will result in increased miss distances. 5. Once all danger is passed, the satellites return to their original orbits, all the while avoiding each other as above. 6. The delta-Vs are reasonable. The controller begins maneuvers as soon as practical to minimize delta-V. 7. Despite the inclusion of trajectory simulations within the control loop, the algorithm is sufficiently fast for available satellite computer hardware. 8. The required measurement accuracies are within the capabilities of modern inertial measurement devices and modern positioning devices.

Multisensor satellite data integration for sea surface wind speed and direction determination

NASA Technical Reports Server (NTRS)

Glackin, D. L.; Pihos, G. G.; Wheelock, S. L.

1984-01-01

Techniques to integrate meteorological data from various satellite sensors to yield a global measure of sea surface wind speed and direction for input to the Navy's operational weather forecast models were investigated. The sensors were launched or will be launched, specifically the GOES visible and infrared imaging sensor, the Nimbus-7 SMMR, and the DMSP SSM/I instrument. An algorithm for the extrapolation to the sea surface of wind directions as derived from successive GOES cloud images was developed. This wind veering algorithm is relatively simple, accounts for the major physical variables, and seems to represent the best solution that can be found with existing data. An algorithm for the interpolation of the scattered observed data to a common geographical grid was implemented. The algorithm is based on a combination of inverse distance weighting and trend surface fitting, and is suited to combing wind data from disparate sources.

Predicting ozone profile shape from satellite UV spectra

NASA Astrophysics Data System (ADS)

Xu, Jian; Loyola, Diego; Romahn, Fabian; Doicu, Adrian

2017-04-01

Identifying ozone profile shape is a critical yet challenging job for the accurate reconstruction of vertical distributions of atmospheric ozone that is relevant to climate change and air quality. Motivated by the need to develop an approach to reliably and efficiently estimate vertical information of ozone and inspired by the success of machine learning techniques, this work proposes a new algorithm for deriving ozone profile shapes from ultraviolet (UV) absorption spectra that are recorded by satellite instruments, e.g. GOME series and the future Sentinel missions. The proposed algorithm formulates this particular inverse problem in a classification framework rather than a conventional inversion one and places an emphasis on effectively characterizing various profile shapes based on machine learning techniques. Furthermore, a comparison of the ozone profiles from real GOME-2 data estimated by our algorithm and the classical retrieval algorithm (Optimal Estimation Method) is performed.

GLONASS orbit/clock combination in VNIIFTRI

NASA Astrophysics Data System (ADS)

Bezmenov, I.; Pasynok, S.

2015-08-01

An algorithm and a program for GLONASS satellites orbit/clock combination based on daily precise orbits submitted by several Analytic Centers were developed. Some theoretical estimates for combine orbit positions RMS were derived. It was shown that under condition that RMS of satellite orbits provided by the Analytic Centers during a long time interval are commensurable the RMS of combine orbit positions is no greater than RMS of other satellite positions estimated by any of the Analytic Centers.

A Prototype Hail Detection Algorithm and Hail Climatology Developed with the Advanced Microwave Sounding Unit (AMSU)

NASA Technical Reports Server (NTRS)

Ferraro, Ralph; Beauchamp, James; Cecil, Dan; Heymsfeld, Gerald

2015-01-01

In previous studies published in the open literature, a strong relationship between the occurrence of hail and the microwave brightness temperatures (primarily at 37 and 85 GHz) was documented. These studies were performed with the Nimbus-7 SMMR, the TRMM Microwave Imager (TMI) and most recently, the Aqua AMSR-E sensor. This lead to climatologies of hail frequency from TMI and AMSR-E, however, limitations include geographical domain of the TMI sensor (35 S to 35 N) and the overpass time of the Aqua satellite (130 am/pm local time), both of which reduce an accurate mapping of hail events over the global domain and the full diurnal cycle. Nonetheless, these studies presented exciting, new applications for passive microwave sensors. Since 1998, NOAA and EUMETSAT have been operating the AMSU-A/B and the MHS on several operational satellites: NOAA-15 through NOAA-19; MetOp-A and -B. With multiple satellites in operation since 2000, the AMSU/MHS sensors provide near global coverage every 4 hours, thus, offering a much larger time and temporal sampling than TRMM or AMSR-E. With similar observation frequencies near 30 and 85 GHz and additionally three at the 183 GHz water vapor band, the potential to detect strong convection associated with severe storms on a more comprehensive time and space scale exists. In this study, we develop a prototype AMSU-based hail detection algorithm through the use of collocated satellite and surface hail reports over the continental U.S. for a 12-year period (2000-2011). Compared with the surface observations, the algorithm detects approximately 40 percent of hail occurrences. The simple threshold algorithm is then used to generate a hail climatology that is based on all available AMSU observations during 2000-11 that is stratified in several ways, including total hail occurrence by month (March through September), total annual, and over the diurnal cycle. Independent comparisons are made compared to similar data sets derived from other satellite, ground radar and surface reports. The algorithm was also applied to global land measurements for a single year and showed close agreement with other satellite based hail climatologies. Such a product could serve as a prototype for use with a future geostationary based microwave sensor such as NASA's proposed PATH mission.

Developing Information Services and Tools to Access and Evaluate Data Quality in Global Satellite-based Precipitation Products

NASA Astrophysics Data System (ADS)

Liu, Z.; Shie, C. L.; Meyer, D. J.

2017-12-01

Global satellite-based precipitation products have been widely used in research and applications around the world. Compared to ground-based observations, satellite-based measurements provide precipitation data on a global scale, especially in remote continents and over oceans. Over the years, satellite-based precipitation products have evolved from single sensor and single algorithm to multi-sensors and multi-algorithms. As a result, many satellite-based precipitation products have been enhanced such as spatial and temporal coverages. With inclusion of ground-based measurements, biases of satellite-based precipitation products have been significantly reduced. However, data quality issues still exist and can be caused by many factors such as observations, satellite platform anomaly, algorithms, production, calibration, validation, data services, etc. The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) is home to NASA global precipitation product archives including the Tropical Rainfall Measuring Mission (TRMM), the Global Precipitation Measurement (GPM), as well as other global and regional precipitation products. Precipitation is one of the top downloaded and accessed parameters in the GES DISC data archive. Meanwhile, users want to easily locate and obtain data quality information at regional and global scales to better understand how precipitation products perform and how reliable they are. As data service providers, it is necessary to provide an easy access to data quality information, however, such information normally is not available, and when it is available, it is not in one place and difficult to locate. In this presentation, we will present challenges and activities at the GES DISC to address precipitation data quality issues.

Studies of the net surface radiative flux from satellite radiances during FIFE

NASA Technical Reports Server (NTRS)

Frouin, Robert

1993-01-01

Studies of the net surface radiative flux from satellite radiances during First ISLSCP Field Experiment (FIFE) are presented. Topics covered include: radiative transfer model validation; calibration of VISSR and AVHRR solar channels; development and refinement of algorithms to estimate downward solar and terrestrial irradiances at the surface, including photosynthetically available radiation (PAR) and surface albedo; verification of these algorithms using in situ measurements; production of maps of shortwave irradiance, surface albedo, and related products; analysis of the temporal variability of shortwave irradiance over the FIFE site; development of a spectroscopy technique to estimate atmospheric total water vapor amount; and study of optimum linear combinations of visible and near-infrared reflectances for estimating the fraction of PAR absorbed by plants.

The AMSR2 Satellite-based Microwave Snow Algorithm (SMSA) to estimate regional to global snow depth and snow water equivalent

NASA Astrophysics Data System (ADS)

Kelly, R. E. J.; Saberi, N.; Li, Q.

2017-12-01

With moderate to high spatial resolution (<1 km) regional to global snow water equivalent (SWE) observation approaches yet to be fully scoped and developed, the long-term satellite passive microwave record remains an important tool for cryosphere-climate diagnostics. A new satellite microwave remote sensing approach is described for estimating snow depth (SD) and snow water equivalent (SWE). The algorithm, called the Satellite-based Microwave Snow Algorithm (SMSA), uses Advanced Microwave Scanning Radiometer - 2 (AMSR2) observations aboard the Global Change Observation Mission - Water mission launched by the Japan Aerospace Exploration Agency in 2012. The approach is unique since it leverages observed brightness temperatures (Tb) with static ancillary data to parameterize a physically-based retrieval without requiring parameter constraints from in situ snow depth observations or historical snow depth climatology. After screening snow from non-snow surface targets (water bodies [including freeze/thaw state], rainfall, high altitude plateau regions [e.g. Tibetan plateau]), moderate and shallow snow depths are estimated by minimizing the difference between Dense Media Radiative Transfer model estimates (Tsang et al., 2000; Picard et al., 2011) and AMSR2 Tb observations to retrieve SWE and SD. Parameterization of the model combines a parsimonious snow grain size and density approach originally developed by Kelly et al. (2003). Evaluation of the SMSA performance is achieved using in situ snow depth data from a variety of standard and experiment data sources. Results presented from winter seasons 2012-13 to 2016-17 illustrate the improved performance of the new approach in comparison with the baseline AMSR2 algorithm estimates and approach the performance of the model assimilation-based approach of GlobSnow. Given the variation in estimation power of SWE by different land surface/climate models and selected satellite-derived passive microwave approaches, SMSA provides SWE estimates that are independent of real or near real-time in situ and model data.

The application of generalized, cyclic, and modified numerical integration algorithms to problems of satellite orbit computation

NASA Technical Reports Server (NTRS)

Chesler, L.; Pierce, S.

1971-01-01

Generalized, cyclic, and modified multistep numerical integration methods are developed and evaluated for application to problems of satellite orbit computation. Generalized methods are compared with the presently utilized Cowell methods; new cyclic methods are developed for special second-order differential equations; and several modified methods are developed and applied to orbit computation problems. Special computer programs were written to generate coefficients for these methods, and subroutines were written which allow use of these methods with NASA's GEOSTAR computer program.

A Spectrally Selective Attenuation Mechanism-Based Kpar Algorithm for Biomass Heating Effect Simulation in the Open Ocean

NASA Astrophysics Data System (ADS)

Chen, Jun; Zhang, Xiangguang; Xing, Xiaogang; Ishizaka, Joji; Yu, Zhifeng

2017-12-01

Quantifying the diffuse attenuation coefficient of the photosynthetically available radiation (Kpar) can improve our knowledge of euphotic depth (Zeu) and biomass heating effects in the upper layers of oceans. An algorithm to semianalytically derive Kpar from remote sensing reflectance (Rrs) is developed for the global open oceans. This algorithm includes the following two portions: (1) a neural network model for deriving the diffuse attention coefficients (Kd) that considers the residual error in satellite Rrs, and (2) a three band depth-dependent Kpar algorithm (TDKA) for describing the spectrally selective attenuation mechanism of underwater solar radiation in the open oceans. This algorithm is evaluated with both in situ PAR profile data and satellite images, and the results show that it can produce acceptable PAR profile estimations while clearly removing the impacts of satellite residual errors on Kpar estimations. Furthermore, the performance of the TDKA algorithm is evaluated by its applicability in Zeu derivation and mean temperature within a mixed layer depth (TML) simulation, and the results show that it can significantly decrease the uncertainty in both compared with the classical chlorophyll-a concentration-based Kpar algorithm. Finally, the TDKA algorithm is applied in simulating biomass heating effects in the Sargasso Sea near Bermuda, with new Kpar data it is found that the biomass heating effects can lead to a 3.4°C maximum positive difference in temperature in the upper layers but could result in a 0.67°C maximum negative difference in temperature in the deep layers.

Long-term analysis of aerosol optical depth over Northeast Asia using a satellite-based measurement: MI Yonsei Aerosol Retrieval Algorithm (YAER)

NASA Astrophysics Data System (ADS)

Kim, Mijin; Kim, Jhoon; Yoon, Jongmin; Chung, Chu-Yong; Chung, Sung-Rae

2017-04-01

In 2010, the Korean geostationary earth orbit (GEO) satellite, the Communication, Ocean, and Meteorological Satellite (COMS), was launched including the Meteorological Imager (MI). The MI measures atmospheric condition over Northeast Asia (NEA) using a single visible channel centered at 0.675 μm and four IR channels at 3.75, 6.75, 10.8, 12.0 μm. The visible measurement can also be utilized for the retrieval of aerosol optical properties (AOPs). Since the GEO satellite measurement has an advantage for continuous monitoring of AOPs, we can analyze the spatiotemporal variation of the aerosol using the MI observations over NEA. Therefore, we developed an algorithm to retrieve aerosol optical depth (AOD) using the visible observation of MI, and named as MI Yonsei Aerosol Retrieval Algorithm (YAER). In this study, we investigated the accuracy of MI YAER AOD by comparing the values with the long-term products of AERONET sun-photometer. The result showed that the MI AODs were significantly overestimated than the AERONET values over bright surface in low AOD case. Because the MI visible channel centered at red color range, contribution of aerosol signal to the measured reflectance is relatively lower than the surface contribution. Therefore, the AOD error in low AOD case over bright surface can be a fundamental limitation of the algorithm. Meanwhile, an assumption of background aerosol optical depth (BAOD) could result in the retrieval uncertainty, also. To estimate the surface reflectance by considering polluted air condition over the NEA, we estimated the BAOD from the MODIS dark target (DT) aerosol products by pixel. The satellite-based AOD retrieval, however, largely depends on the accuracy of the surface reflectance estimation especially in low AOD case, and thus, the BAOD could include the uncertainty in surface reflectance estimation of the satellite-based retrieval. Therefore, we re-estimated the BAOD using the ground-based sun-photometer measurement, and investigated the effects of the BAOD assumption. The satellite-based BAOD was significantly higher than the ground-based value over urban area, and thus, resulted in the underestimation of surface reflectance and the overestimation of AOD. The error analysis of the MI AOD also showed sensitivity to cloud contamination, clearly. Therefore, improvements of cloud masking process in the developed single channel MI algorithm as well as the modification of the surface reflectance estimation will be required for the future study.

Encryption protection for communication satellites

NASA Astrophysics Data System (ADS)

Sood, D. R.; Hoernig, O. W., Jr.

In connection with the growing importance of the commercial communication satellite systems and the introduction of new technological developments, users and operators of these systems become increasingly concerned with aspects of security. The user community is concerned with maintaining confidentiality and integrity of the information being transmitted over the satellite links, while the satellite operators are concerned about the safety of their assets in space. In response to these concerns, the commercial satellite operators are now taking steps to protect the communication information and the satellites. Thus, communication information is being protected by end-to-end encryption of the customer communication traffic. Attention is given to the selection of the NBS DES algorithm, the command protection systems, and the communication protection systems.

Algorithms for Processing and Analysis of Ocean Color Satellite Data for Coastal Case 2 Waters. Chapter 16

NASA Technical Reports Server (NTRS)

Stumpf, Richard P.; Arnone, Robert A.; Gould, Richard W., Jr.; Ransibrahmanakul, Varis; Tester, Patricia A.

2003-01-01

SeaWiFS has the ability to enhance our understanding of many oceanographic processes. However, its utility in the coastal zone has been limited by valid bio-optical algorithms and by the determination of accurate water reflectances, particularly in the blue bands (412-490 nm), which have a significant impact on the effectiveness of all bio-optical algorithms. We have made advances in three areas: algorithm development (Table 16.1), field data collection, and data applications.

Derivation and evaluation of land surface temperature from the geostationary operational environmental satellite series

NASA Astrophysics Data System (ADS)

Fang, Li

The Geostationary Operational Environmental Satellites (GOES) have been continuously monitoring the earth surface since 1970, providing valuable and intensive data from a very broad range of wavelengths, day and night. The National Oceanic and Atmospheric Administration's (NOAA's) National Environmental Satellite, Data, and Information Service (NESDIS) is currently operating GOES-15 and GOES-13. The design of the GOES series is now heading to the 4 th generation. GOES-R, as a representative of the new generation of the GOES series, is scheduled to be launched in 2015 with higher spatial and temporal resolution images and full-time soundings. These frequent observations provided by GOES Image make them attractive for deriving information on the diurnal land surface temperature (LST) cycle and diurnal temperature range (DTR). These parameters are of great value for research on the Earth's diurnal variability and climate change. Accurate derivation of satellite-based LSTs from thermal infrared data has long been an interesting and challenging research area. To better support the research on climate change, the generation of consistent GOES LST products for both GOES-East and GOES-West from operational dataset as well as historical archive is in great demand. The derivation of GOES LST products and the evaluation of proposed retrieval methods are two major objectives of this study. Literature relevant to satellite-based LST retrieval techniques was reviewed. Specifically, the evolution of two LST algorithm families and LST retrieval methods for geostationary satellites were summarized in this dissertation. Literature relevant to the evaluation of satellite-based LSTs was also reviewed. All the existing methods are a valuable reference to develop the GOES LST product. The primary objective of this dissertation is the development of models for deriving consistent GOES LSTs with high spatial and high temporal coverage. Proper LST retrieval algorithms were studied according to the characteristics of the imager onboard the GOES series. For the GOES 8-11 and GOES R series with split window (SW) channels, a new temperature and emissivity separation (TES) approach was proposed for deriving LST and LSE simultaneously by using multiple-temporal satellite observations. Two split-window regression formulas were selected for this approach, and two satellite observations over the same geo-location within a certain time interval were utilized. This method is particularly applicable to geostationary satellite missions from which qualified multiple-temporal observations are available. For the GOES M(12)-Q series without SW channels, the dual-window LST algorithm was adopted to derive LST. Instead of using the conventional training method to generate coefficients for the LST regression algorithms, a machine training technique was introduced to automatically select the criteria and the boundary of the sub-ranges for generating algorithm coefficients under different conditions. A software package was developed to produce a brand new GOES LST product from both operational GOES measurements and historical archive. The system layers of the software and related system input and output were illustrated in this work. Comprehensive evaluation of GOES LST products was conducted by validating products against multiple ground-based LST observations, LST products from fine-resolution satellites (e.g. MODIS) and GSIP LST products. The key issues relevant to the cloud diffraction effect were studied as well. GOES measurements as well as ancillary data, including satellite and solar geometry, water vapor, cloud mask, land emissivity etc., were collected to generate GOES LST products. In addition, multiple in situ temperature measurements were collected to test the performance of the proposed GOES LST retrieval algorithms. The ground-based dataset included direct surface temperature measurements from the Atmospheric Radiation Measurement program (ARM), and indirect measurements (surface long-wave radiation observations) from the SURFace RADiation Budget (SURFRAD) Network. A simulated dataset was created to analyse the sensitivity of the proposed retrieval algorithms. In addition, the MODIS LST and GSIP LST products were adopted to cross-evaluate the accuracy of the GOES LST products. Evaluation results demonstrate that the proposed GOES LST system is capable of deriving consistent land surface temperatures with good retrieval precision. Consistent GOES LST products with high spatial/temporal coverage and reliable accuracy will better support detections and observations of meteorological over land surfaces.

Visual attitude propagation for small satellites

NASA Astrophysics Data System (ADS)

Rawashdeh, Samir A.

As electronics become smaller and more capable, it has become possible to conduct meaningful and sophisticated satellite missions in a small form factor. However, the capability of small satellites and the range of possible applications are limited by the capabilities of several technologies, including attitude determination and control systems. This dissertation evaluates the use of image-based visual attitude propagation as a compliment or alternative to other attitude determination technologies that are suitable for miniature satellites. The concept lies in using miniature cameras to track image features across frames and extracting the underlying rotation. The problem of visual attitude propagation as a small satellite attitude determination system is addressed from several aspects: related work, algorithm design, hardware and performance evaluation, possible applications, and on-orbit experimentation. These areas of consideration reflect the organization of this dissertation. A "stellar gyroscope" is developed, which is a visual star-based attitude propagator that uses relative motion of stars in an imager's field of view to infer the attitude changes. The device generates spacecraft relative attitude estimates in three degrees of freedom. Algorithms to perform the star detection, correspondence, and attitude propagation are presented. The Random Sample Consensus (RANSAC) approach is applied to the correspondence problem to successfully pair stars across frames while mitigating falsepositive and false-negative star detections. This approach provides tolerance to the noise levels expected in using miniature optics and no baffling, and the noise caused by radiation dose on orbit. The hardware design and algorithms are validated using test images of the night sky. The application of the stellar gyroscope as part of a CubeSat attitude determination and control system is described. The stellar gyroscope is used to augment a MEMS gyroscope attitude propagation algorithm to minimize drift in the absence of an absolute attitude sensor. The stellar gyroscope is a technology demonstration experiment on KySat-2, a 1-Unit CubeSat being developed in Kentucky that is in line to launch with the NASA ELaNa CubeSat Launch Initiative. It has also been adopted by industry as a sensor for CubeSat Attitude Determination and Control Systems (ADCS). KEYWORDS: Small Satellites, Attitude Determination, Egomotion Estimation, RANSAC, Image Processing.

Assessing and validating RST-FIRES on MSG-SEVIRI data by means a Total Validation Approach (TVA).

NASA Astrophysics Data System (ADS)

Filizzola, Carolina; Corrado, Rosita; Marchese, Francesco; Mazzeo, %Giuseppe; Paciello, Rossana; Pergola, Nicola; Tramutoli, Valerio

2015-04-01

Several fire detection methods have been developed through the years for detecting forest fires from space. These algorithms (which may be grouped in single channel, multichannel and contextual algorithms) are generally based on the use of fixed thresholds that, being intrinsically exposed to false alarm proliferation, are often used in a conservative way. As a consequence, most of satellite-based algorithms for fire detection show low sensitivity resulting not suitable in operational contexts. In this work, the RST-FIRES algorithm, which is based on an original multi-temporal scheme of satellite data analysis (RST-Robust Satellite Techniques), is presented. The implementation of RST-FIRES on data provided by Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard Meteosat Second Generation (MSG) that, offering the best revisit time (i.e. 15 minutes), can be successfully used for detecting fires at early stage, is described here. Moreover, results of a Total Validation Approach (TVA) experimented both in Northern and Southern Italy, in collaboration with local and regional civil protection agencies, are also reported. In particular, TVA allowed us to assess RST-FIRES detections by means of ground check and aerial surveys, demonstrating the good performances offered by RST-FIRES using MSG-SEVIRI data. Indeed, this algorithm was capable of detecting several fires that for their features (e.g., small size, short time duration) would not have appeared in the official reports, highlighting a significant improvement in terms of sensitivity in comparison with other established satellite-based fire detection techniques still preserving a high confidence level of detection.

The EUMETSAT sea ice concentration climate data record

NASA Astrophysics Data System (ADS)

Tonboe, Rasmus T.; Eastwood, Steinar; Lavergne, Thomas; Sørensen, Atle M.; Rathmann, Nicholas; Dybkjær, Gorm; Toudal Pedersen, Leif; Høyer, Jacob L.; Kern, Stefan

2016-09-01

An Arctic and Antarctic sea ice area and extent dataset has been generated by EUMETSAT's Ocean and Sea Ice Satellite Application Facility (OSISAF) using the record of microwave radiometer data from NASA's Nimbus 7 Scanning Multichannel Microwave radiometer (SMMR) and the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I) and Special Sensor Microwave Imager and Sounder (SSMIS) satellite sensors. The dataset covers the period from October 1978 to April 2015 and updates and further developments are planned for the next phase of the project. The methodology for computing the sea ice concentration uses (1) numerical weather prediction (NWP) data input to a radiative transfer model for reduction of the impact of weather conditions on the measured brightness temperatures; (2) dynamical algorithm tie points to mitigate trends in residual atmospheric, sea ice, and water emission characteristics and inter-sensor differences/biases; and (3) a hybrid sea ice concentration algorithm using the Bristol algorithm over ice and the Bootstrap algorithm in frequency mode over open water. A new sea ice concentration uncertainty algorithm has been developed to estimate the spatial and temporal variability in sea ice concentration retrieval accuracy. A comparison to US National Ice Center sea ice charts from the Arctic and the Antarctic shows that ice concentrations are higher in the ice charts than estimated from the radiometer data at intermediate sea ice concentrations between open water and 100 % ice. The sea ice concentration climate data record is available for download at www.osi-saf.org, including documentation.

Machine learning based cloud mask algorithm driven by radiative transfer modeling

NASA Astrophysics Data System (ADS)

Chen, N.; Li, W.; Tanikawa, T.; Hori, M.; Shimada, R.; Stamnes, K. H.

2017-12-01

Cloud detection is a critically important first step required to derive many satellite data products. Traditional threshold based cloud mask algorithms require a complicated design process and fine tuning for each sensor, and have difficulty over snow/ice covered areas. With the advance of computational power and machine learning techniques, we have developed a new algorithm based on a neural network classifier driven by extensive radiative transfer modeling. Statistical validation results obtained by using collocated CALIOP and MODIS data show that its performance is consistent over different ecosystems and significantly better than the MODIS Cloud Mask (MOD35 C6) during the winter seasons over mid-latitude snow covered areas. Simulations using a reduced number of satellite channels also show satisfactory results, indicating its flexibility to be configured for different sensors.

Using Geostationary Communications Satellites as a Sensor: Telemetry Search Algorithms

NASA Astrophysics Data System (ADS)

Cahoy, K.; Carlton, A.; Lohmeyer, W. Q.

2014-12-01

For decades, operators and manufacturers have collected large amounts of telemetry from geostationary (GEO) communications satellites to monitor system health and performance, yet this data is rarely mined for scientific purposes. The goal of this work is to mine data archives acquired from commercial operators using new algorithms that can detect when a space weather (or non-space weather) event of interest has occurred or is in progress. We have developed algorithms to statistically analyze power amplifier current and temperature telemetry and identify deviations from nominal operations or other trends of interest. We then examine space weather data to see what role, if any, it might have played. We also closely examine both long and short periods of time before an anomaly to determine whether or not the anomaly could have been predicted.

Satellite-Derived Bathymetry: Accuracy Assessment on Depths Derivation Algorithm for Shallow Water Area

NASA Astrophysics Data System (ADS)

Said, N. M.; Mahmud, M. R.; Hasan, R. C.

2017-10-01

Over the years, the acquisition technique of bathymetric data has evolved from a shipborne platform to airborne and presently, utilising space-borne acquisition. The extensive development of remote sensing technology has brought in the new revolution to the hydrographic surveying. Satellite-Derived Bathymetry (SDB), a space-borne acquisition technique which derives bathymetric data from high-resolution multispectral satellite imagery for various purposes recently considered as a new promising technology in the hydrographic surveying industry. Inspiring by this latest developments, a comprehensive study was initiated by National Hydrographic Centre (NHC) and Universiti Teknologi Malaysia (UTM) to analyse SDB as a means for shallow water area acquisition. By adopting additional adjustment in calibration stage, a marginal improvement discovered on the outcomes from both Stumpf and Lyzenga algorithms where the RMSE values for the derived (predicted) depths were 1.432 meters and 1.728 meters respectively. This paper would deliberate in detail the findings from the study especially on the accuracy level and practicality of SDB over the tropical environmental setting in Malaysia.

Phase 2 development of Great Lakes algorithms for Nimbus-7 coastal zone color scanner

NASA Technical Reports Server (NTRS)

Tanis, Fred J.

1984-01-01

A series of experiments have been conducted in the Great Lakes designed to evaluate the application of the NIMBUS-7 Coastal Zone Color Scanner (CZCS). Atmospheric and water optical models were used to relate surface and subsurface measurements to satellite measured radiances. Absorption and scattering measurements were reduced to obtain a preliminary optical model for the Great Lakes. Algorithms were developed for geometric correction, correction for Rayleigh and aerosol path radiance, and prediction of chlorophyll-a pigment and suspended mineral concentrations. The atmospheric algorithm developed compared favorably with existing algorithms and was the only algorithm found to adequately predict the radiance variations in the 670 nm band. The atmospheric correction algorithm developed was designed to extract needed algorithm parameters from the CZCS radiance values. The Gordon/NOAA ocean algorithms could not be demonstrated to work for Great Lakes waters. Predicted values of chlorophyll-a concentration compared favorably with expected and measured data for several areas of the Great Lakes.

The Earth Phenomena Observing System: Intelligent Autonomy for Satellite Operations

NASA Technical Reports Server (NTRS)

Ricard, Michael; Abramson, Mark; Carter, David; Kolitz, Stephan

2003-01-01

Earth monitoring systems of the future may include large numbers of inexpensive small satellites, tasked in a coordinated fashion to observe both long term and transient targets. For best performance, a tool which helps operators optimally assign targets to satellites will be required. We present the design of algorithms developed for real-time optimized autonomous planning of large numbers of small single-sensor Earth observation satellites. The algorithms will reduce requirements on the human operators of such a system of satellites, ensure good utilization of system resources, and provide the capability to dynamically respond to temporal terrestrial phenomena. Our initial real-time system model consists of approximately 100 satellites and large number of points of interest on Earth (e.g., hurricanes, volcanoes, and forest fires) with the objective to maximize the total science value of observations over time. Several options for calculating the science value of observations include the following: 1) total observation time, 2) number of observations, and the 3) quality (a function of e.g., sensor type, range, slant angle) of the observations. An integrated approach using integer programming, optimization and astrodynamics is used to calculate optimized observation and sensor tasking plans.

Inter-satellite links for satellite autonomous integrity monitoring

NASA Astrophysics Data System (ADS)

Rodríguez-Pérez, Irma; García-Serrano, Cristina; Catalán Catalán, Carlos; García, Alvaro Mozo; Tavella, Patrizia; Galleani, Lorenzo; Amarillo, Francisco

2011-01-01

A new integrity monitoring mechanisms to be implemented on-board on a GNSS taking advantage of inter-satellite links has been introduced. This is based on accurate range and Doppler measurements not affected neither by atmospheric delays nor ground local degradation (multipath and interference). By a linear combination of the Inter-Satellite Links Observables, appropriate observables for both satellite orbits and clock monitoring are obtained and by the proposed algorithms it is possible to reduce the time-to-alarm and the probability of undetected satellite anomalies.Several test cases have been run to assess the performances of the new orbit and clock monitoring algorithms in front of a complete scenario (satellite-to-satellite and satellite-to-ground links) and in a satellite-only scenario. The results of this experimentation campaign demonstrate that the Orbit Monitoring Algorithm is able to detect orbital feared events when the position error at the worst user location is still under acceptable limits. For instance, an unplanned manoeuvre in the along-track direction is detected (with a probability of false alarm equals to 5 × 10-9) when the position error at the worst user location is 18 cm. The experimentation also reveals that the clock monitoring algorithm is able to detect phase jumps, frequency jumps and instability degradation on the clocks but the latency of detection as well as the detection performances strongly depends on the noise added by the clock measurement system.

On-board attitude determination for the Explorer Platform satellite

NASA Technical Reports Server (NTRS)

Jayaraman, C.; Class, B.

1992-01-01

This paper describes the attitude determination algorithm for the Explorer Platform satellite. The algorithm, which is baselined on the Landsat code, is a six-element linear quadratic state estimation processor, in the form of a Kalman filter augmented by an adaptive filter process. Improvements to the original Landsat algorithm were required to meet mission pointing requirements. These consisted of a more efficient sensor processing algorithm and the addition of an adaptive filter which acts as a check on the Kalman filter during satellite slew maneuvers. A 1750A processor will be flown on board the satellite for the first time as a coprocessor (COP) in addition to the NASA Standard Spacecraft Computer. The attitude determination algorithm, which will be resident in the COP's memory, will make full use of its improved processing capabilities to meet mission requirements. Additional benefits were gained by writing the attitude determination code in Ada.

High Impact Weather Forecasts and Warnings with the GOES-R Geostationary Lightning Mapper (GLM)

NASA Technical Reports Server (NTRS)

Goodman, Steven J.; Blakeslee, Richard J.; Koshak, William; Mach, Douglas M.

2011-01-01

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. A major advancement over the current GOES include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM). The GLM will operate continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency. In parallel with the instrument development, a GOES-R Risk Reduction Science Team and Algorithm Working Group Lightning Applications Team have begun to develop cal/val performance monitoring tools and new applications using the GLM alone, in conjunction with other instruments, and merged or blended integrated observing system products combining satellite, radar, in-situ and numerical models. Proxy total lightning data from the NASA Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional ground-based lightning networks are being used to develop the pre-launch algorithms, test data sets, and applications, as well as improve our knowledge of thunderstorm initiation and evolution. In this presentation we review the planned implementation of the instrument and suite of operational algorithms.

A Web-Based Library and Algorithm System for Satellite and Airborne Image Products

DTIC Science & Technology

2011-06-28

Sequoia Scientific, Inc., and Dr. Paul Bissett at FERI, under other 6.1/6.2 program funding. 2 A Web-Based Library And Algorithm System For...of the spectrum matching approach to inverting hyperspectral imagery created by Drs. C. Mobley ( Sequoia Scientific) and P. Bissett (FERI...algorithms developed by Sequoia Scientific and FERI. Testing and Implementation of Library This project will result in the delivery of a WeoGeo

Next generation communications satellites: multiple access and network studies

NASA Technical Reports Server (NTRS)

Meadows, H. E.; Schwartz, M.; Stern, T. E.; Ganguly, S.; Kraimeche, B.; Matsuo, K.; Gopal, I.

1982-01-01

Efficient resource allocation and network design for satellite systems serving heterogeneous user populations with large numbers of small direct-to-user Earth stations are discussed. Focus is on TDMA systems involving a high degree of frequency reuse by means of satellite-switched multiple beams (SSMB) with varying degrees of onboard processing. Algorithms for the efficient utilization of the satellite resources were developed. The effect of skewed traffic, overlapping beams and batched arrivals in packet-switched SSMB systems, integration of stream and bursty traffic, and optimal circuit scheduling in SSMB systems: performance bounds and computational complexity are discussed.

Combination of GPS and GLONASS IN PPP algorithms and its effect on site coordinates determination

NASA Astrophysics Data System (ADS)

Hefty, J.; Gerhatova, L.; Burgan, J.

2011-10-01

Precise Point Positioning (PPP) approach using the un-differenced code and phase GPS observations, precise orbits and satellite clocks is an important alternative to the analyses based on double differences. We examine the extension of the PPP method by introducing the GLONASS satellites into the processing algorithms. The procedures are demonstrated on the software package ABSOLUTE developed at the Slovak University of Technology. Partial results, like ambiguities and receiver clocks obtained from separate solutions of the two GNSS are mutually compared. Finally, the coordinate time series from combination of GPS and GLONASS observations are compared with GPS-only solutions.

The Role of Combination Techniques in Maximizing the Utility of Precipitation Estimates from Several Multi-Purpose Remote-Sensing Systems

NASA Technical Reports Server (NTRS)

Huffman, George J.; Adler, Robert F.; Bolvin, David T.; Curtis, Scott; Einaudi, Franco (Technical Monitor)

2001-01-01

Multi-purpose remote-sensing products from various satellites have proved crucial in developing global estimates of precipitation. Examples of these products include low-earth-orbit and geosynchronous-orbit infrared (leo- and geo-IR), Outgoing Longwave Radiation (OLR), Television Infrared Operational Satellite (TIROS) Operational Vertical Sounder (TOVS) data, and passive microwave data such as that from the Special Sensor Microwave/ Imager (SSM/I). Each of these datasets has served as the basis for at least one useful quasi-global precipitation estimation algorithm; however, the quality of estimates varies tremendously among the algorithms for the different climatic regions around the globe.

Security Concepts for Satellite Links

NASA Astrophysics Data System (ADS)

Tobehn, C.; Penné, B.; Rathje, R.; Weigl, A.; Gorecki, Ch.; Michalik, H.

2008-08-01

The high costs to develop, launch and maintain a satellite network makes protecting the assets imperative. Attacks may be passive such as eavesdropping on the payload data. More serious threat are active attacks that try to gain control of the satellite, which may lead to the total lost of the satellite asset. To counter these threats, new satellite and ground systems are using cryptographic technologies to provide a range of services: confidentiality, entity & message authentication, and data integrity. Additionally, key management cryptographic services are required to support these services. This paper describes the key points of current satellite control and operations, that are authentication of the access to the satellite TMTC link and encryption of security relevant TM/TC data. For payload data management the key points are multi-user ground station access and high data rates both requiring frequent updates and uploads of keys with the corresponding key management methods. For secure satellite management authentication & key negotiation algorithms as HMAC-RIPEMD160, EC- DSA and EC-DH are used. Encryption of data uses algorithms as IDEA, AES, Triple-DES, or other. A channel coding and encryption unit for payload data provides download data rates up to Nx250 Mbps. The presented concepts are based on our experience and heritage of the security systems for all German MOD satellite projects (SATCOMBw2, SAR-Lupe multi- satellite system and German-French SAR-Lupe-Helios- II systems inter-operability) as well as for further international (KOMPSAT-II Payload data link system) and ESA activities (TMTC security and GMES).

Geographically weighted regression based methods for merging satellite and gauge precipitation

NASA Astrophysics Data System (ADS)

Chao, Lijun; Zhang, Ke; Li, Zhijia; Zhu, Yuelong; Wang, Jingfeng; Yu, Zhongbo

2018-03-01

Real-time precipitation data with high spatiotemporal resolutions are crucial for accurate hydrological forecasting. To improve the spatial resolution and quality of satellite precipitation, a three-step satellite and gauge precipitation merging method was formulated in this study: (1) bilinear interpolation is first applied to downscale coarser satellite precipitation to a finer resolution (PS); (2) the (mixed) geographically weighted regression methods coupled with a weighting function are then used to estimate biases of PS as functions of gauge observations (PO) and PS; and (3) biases of PS are finally corrected to produce a merged precipitation product. Based on the above framework, eight algorithms, a combination of two geographically weighted regression methods and four weighting functions, are developed to merge CMORPH (CPC MORPHing technique) precipitation with station observations on a daily scale in the Ziwuhe Basin of China. The geographical variables (elevation, slope, aspect, surface roughness, and distance to the coastline) and a meteorological variable (wind speed) were used for merging precipitation to avoid the artificial spatial autocorrelation resulting from traditional interpolation methods. The results show that the combination of the MGWR and BI-square function (MGWR-BI) has the best performance (R = 0.863 and RMSE = 7.273 mm/day) among the eight algorithms. The MGWR-BI algorithm was then applied to produce hourly merged precipitation product. Compared to the original CMORPH product (R = 0.208 and RMSE = 1.208 mm/hr), the quality of the merged data is significantly higher (R = 0.724 and RMSE = 0.706 mm/hr). The developed merging method not only improves the spatial resolution and quality of the satellite product but also is easy to implement, which is valuable for hydrological modeling and other applications.

Validity of Five Satellite-Based Latent Heat Flux Algorithms for Semi-arid Ecosystems

DOE PAGES

Feng, Fei; Chen, Jiquan; Li, Xianglan; ...

2015-12-09

Accurate estimation of latent heat flux (LE) is critical in characterizing semiarid ecosystems. Many LE algorithms have been developed during the past few decades. However, the algorithms have not been directly compared, particularly over global semiarid ecosystems. In this paper, we evaluated the performance of five LE models over semiarid ecosystems such as grassland, shrub, and savanna using the Fluxnet dataset of 68 eddy covariance (EC) sites during the period 2000–2009. We also used a modern-era retrospective analysis for research and applications (MERRA) dataset, the Normalized Difference Vegetation Index (NDVI) and Fractional Photosynthetically Active Radiation (FPAR) from the moderate resolutionmore » imaging spectroradiometer (MODIS) products; the leaf area index (LAI) from the global land surface satellite (GLASS) products; and the digital elevation model (DEM) from shuttle radar topography mission (SRTM30) dataset to generate LE at region scale during the period 2003–2006. The models were the moderate resolution imaging spectroradiometer LE (MOD16) algorithm, revised remote sensing based Penman–Monteith LE algorithm (RRS), the Priestley–Taylor LE algorithm of the Jet Propulsion Laboratory (PT-JPL), the modified satellite-based Priestley–Taylor LE algorithm (MS-PT), and the semi-empirical Penman LE algorithm (UMD). Direct comparison with ground measured LE showed the PT-JPL and MS-PT algorithms had relative high performance over semiarid ecosystems with the coefficient of determination (R2) ranging from 0.6 to 0.8 and root mean squared error (RMSE) of approximately 20 W/m 2. Empirical parameters in the structure algorithms of MOD16 and RRS, and calibrated coefficients of the UMD algorithm may be the cause of the reduced performance of these LE algorithms with R2 ranging from 0.5 to 0.7 and RMSE ranging from 20 to 35 W/m 2 for MOD16, RRS and UMD. Sensitivity analysis showed that radiation and vegetation terms were the dominating variables affecting LE Fluxes in global semiarid ecosystem.« less

Validity of Five Satellite-Based Latent Heat Flux Algorithms for Semi-arid Ecosystems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feng, Fei; Chen, Jiquan; Li, Xianglan

Accurate estimation of latent heat flux (LE) is critical in characterizing semiarid ecosystems. Many LE algorithms have been developed during the past few decades. However, the algorithms have not been directly compared, particularly over global semiarid ecosystems. In this paper, we evaluated the performance of five LE models over semiarid ecosystems such as grassland, shrub, and savanna using the Fluxnet dataset of 68 eddy covariance (EC) sites during the period 2000–2009. We also used a modern-era retrospective analysis for research and applications (MERRA) dataset, the Normalized Difference Vegetation Index (NDVI) and Fractional Photosynthetically Active Radiation (FPAR) from the moderate resolutionmore » imaging spectroradiometer (MODIS) products; the leaf area index (LAI) from the global land surface satellite (GLASS) products; and the digital elevation model (DEM) from shuttle radar topography mission (SRTM30) dataset to generate LE at region scale during the period 2003–2006. The models were the moderate resolution imaging spectroradiometer LE (MOD16) algorithm, revised remote sensing based Penman–Monteith LE algorithm (RRS), the Priestley–Taylor LE algorithm of the Jet Propulsion Laboratory (PT-JPL), the modified satellite-based Priestley–Taylor LE algorithm (MS-PT), and the semi-empirical Penman LE algorithm (UMD). Direct comparison with ground measured LE showed the PT-JPL and MS-PT algorithms had relative high performance over semiarid ecosystems with the coefficient of determination (R2) ranging from 0.6 to 0.8 and root mean squared error (RMSE) of approximately 20 W/m 2. Empirical parameters in the structure algorithms of MOD16 and RRS, and calibrated coefficients of the UMD algorithm may be the cause of the reduced performance of these LE algorithms with R2 ranging from 0.5 to 0.7 and RMSE ranging from 20 to 35 W/m 2 for MOD16, RRS and UMD. Sensitivity analysis showed that radiation and vegetation terms were the dominating variables affecting LE Fluxes in global semiarid ecosystem.« less

Soil Moisture Active Passive (SMAP) Project Algorithm Theoretical Basis Document SMAP L1B Radiometer Data Product: L1B_TB

NASA Technical Reports Server (NTRS)

Piepmeier, Jeffrey; Mohammed, Priscilla; De Amici, Giovanni; Kim, Edward; Peng, Jinzheng; Ruf, Christopher; Hanna, Maher; Yueh, Simon; Entekhabi, Dara

2016-01-01

The purpose of the Soil Moisture Active Passive (SMAP) radiometer calibration algorithm is to convert Level 0 (L0) radiometer digital counts data into calibrated estimates of brightness temperatures referenced to the Earth's surface within the main beam. The algorithm theory in most respects is similar to what has been developed and implemented for decades for other satellite radiometers; however, SMAP includes two key features heretofore absent from most satellite borne radiometers: radio frequency interference (RFI) detection and mitigation, and measurement of the third and fourth Stokes parameters using digital correlation. The purpose of this document is to describe the SMAP radiometer and forward model, explain the SMAP calibration algorithm, including approximations, errors, and biases, provide all necessary equations for implementing the calibration algorithm and detail the RFI detection and mitigation process. Section 2 provides a summary of algorithm objectives and driving requirements. Section 3 is a description of the instrument and Section 4 covers the forward models, upon which the algorithm is based. Section 5 gives the retrieval algorithm and theory. Section 6 describes the orbit simulator, which implements the forward model and is the key for deriving antenna pattern correction coefficients and testing the overall algorithm.

Empirical retrieval of sea spray aerosol production using satellite microwave radiometry

NASA Astrophysics Data System (ADS)

Savelyev, I. B.; Yelland, M. J.; Norris, S. J.; Salisbury, D.; Pascal, R. W.; Bettenhausen, M. H.; Prytherch, J.; Anguelova, M. D.; Brooks, I. M.

2017-12-01

This study presents a novel approach to obtaining global sea spray aerosol (SSA) production source term by relying on direct satellite observations of the ocean surface, instead of more traditional approaches driven by surface meteorology. The primary challenge in developing this empirical algorithm is to compile a calibrated, consistent dataset of SSA surface flux collected offshore over a variety of conditions (i.e., regions and seasons), thus representative of the global SSA production variability. Such dataset includes observations from SEASAW, HiWASE, and WAGES field campaigns, during which the SSA flux was measured from the bow of a research vessel using consistent and state-of-the-art eddy covariance methodology. These in situ data are matched to observations of the state of the ocean surface from Windsat polarimetric microwave satellite radiometer. Previous studies demonstrated the ability of WindSat to detect variations in surface waves slopes, roughness and foam, which led to the development of retrieval algorithms for surface wind vector and more recently whitecap fraction. Similarly, in this study, microwave emissions from the ocean surface are matched to and calibrated against in situ observations of the SSA production flux. The resulting calibrated empirical algorithm is applicable for retrieval of SSA source term throughout the duration of Windsat mission, from 2003 to present.

Research of the key technology in satellite communication networks

NASA Astrophysics Data System (ADS)

Zeng, Yuan

2018-02-01

According to the prediction, in the next 10 years the wireless data traffic will be increased by 500-1000 times. Not only the wireless data traffic will be increased exponentially, and the demand for diversified traffic will be increased. Higher requirements for future mobile wireless communication system had brought huge market space for satellite communication system. At the same time, the space information networks had been greatly developed with the depth of human exploration of space activities, the development of space application, the expansion of military and civilian application. The core of spatial information networks is the satellite communication. The dissertation presented the communication system architecture, the communication protocol, the routing strategy, switch scheduling algorithm and the handoff strategy based on the satellite communication system. We built the simulation platform of the LEO satellites networks and simulated the key technology using OPNET.

A Novel Ship-Tracking Method for GF-4 Satellite Sequential Images.

PubMed

Yao, Libo; Liu, Yong; He, You

2018-06-22

The geostationary remote sensing satellite has the capability of wide scanning, persistent observation and operational response, and has tremendous potential for maritime target surveillance. The GF-4 satellite is the first geostationary orbit (GEO) optical remote sensing satellite with medium resolution in China. In this paper, a novel ship-tracking method in GF-4 satellite sequential imagery is proposed. The algorithm has three stages. First, a local visual saliency map based on local peak signal-to-noise ratio (PSNR) is used to detect ships in a single frame of GF-4 satellite sequential images. Second, the accuracy positioning of each potential target is realized by a dynamic correction using the rational polynomial coefficients (RPCs) and automatic identification system (AIS) data of ships. Finally, an improved multiple hypotheses tracking (MHT) algorithm with amplitude information is used to track ships by further removing the false targets, and to estimate ships’ motion parameters. The algorithm has been tested using GF-4 sequential images and AIS data. The results of the experiment demonstrate that the algorithm achieves good tracking performance in GF-4 satellite sequential images and estimates the motion information of ships accurately.

A Portable Ground-Based Atmospheric Monitoring System (PGAMS) for the Calibration and Validation of Atmospheric Correction Algorithms Applied to Aircraft and Satellite Images

NASA Technical Reports Server (NTRS)

Schiller, Stephen; Luvall, Jeffrey C.; Rickman, Doug L.; Arnold, James E. (Technical Monitor)

2000-01-01

Detecting changes in the Earth's environment using satellite images of ocean and land surfaces must take into account atmospheric effects. As a result, major programs are underway to develop algorithms for image retrieval of atmospheric aerosol properties and atmospheric correction. However, because of the temporal and spatial variability of atmospheric transmittance it is very difficult to model atmospheric effects and implement models in an operational mode. For this reason, simultaneous in situ ground measurements of atmospheric optical properties are vital to the development of accurate atmospheric correction techniques. Presented in this paper is a spectroradiometer system that provides an optimized set of surface measurements for the calibration and validation of atmospheric correction algorithms. The Portable Ground-based Atmospheric Monitoring System (PGAMS) obtains a comprehensive series of in situ irradiance, radiance, and reflectance measurements for the calibration of atmospheric correction algorithms applied to multispectral. and hyperspectral images. The observations include: total downwelling irradiance, diffuse sky irradiance, direct solar irradiance, path radiance in the direction of the north celestial pole, path radiance in the direction of the overflying satellite, almucantar scans of path radiance, full sky radiance maps, and surface reflectance. Each of these parameters are recorded over a wavelength range from 350 to 1050 nm in 512 channels. The system is fast, with the potential to acquire the complete set of observations in only 8 to 10 minutes depending on the selected spatial resolution of the sky path radiance measurements

An Overview of the JPSS Ground Project Algorithm Integration Process

NASA Astrophysics Data System (ADS)

Vicente, G. A.; Williams, R.; Dorman, T. J.; Williamson, R. C.; Shaw, F. J.; Thomas, W. M.; Hung, L.; Griffin, A.; Meade, P.; Steadley, R. S.; Cember, R. P.

2015-12-01

The smooth transition, implementation and operationalization of scientific software's from the National Oceanic and Atmospheric Administration (NOAA) development teams to the Join Polar Satellite System (JPSS) Ground Segment requires a variety of experiences and expertise. This task has been accomplished by a dedicated group of scientist and engineers working in close collaboration with the NOAA Satellite and Information Services (NESDIS) Center for Satellite Applications and Research (STAR) science teams for the JPSS/Suomi-NPOES Preparatory Project (S-NPP) Advanced Technology Microwave Sounder (ATMS), Cross-track Infrared Sounder (CrIS), Visible Infrared Imaging Radiometer Suite (VIIRS) and Ozone Mapping and Profiler Suite (OMPS) instruments. The presentation purpose is to describe the JPSS project process for algorithm implementation from the very early delivering stages by the science teams to the full operationalization into the Interface Processing Segment (IDPS), the processing system that provides Environmental Data Records (EDR's) to NOAA. Special focus is given to the NASA Data Products Engineering and Services (DPES) Algorithm Integration Team (AIT) functional and regression test activities. In the functional testing phase, the AIT uses one or a few specific chunks of data (granules) selected by the NOAA STAR Calibration and Validation (cal/val) Teams to demonstrate that a small change in the code performs properly and does not disrupt the rest of the algorithm chain. In the regression testing phase, the modified code is placed into to the Government Resources for Algorithm Verification, Integration, Test and Evaluation (GRAVITE) Algorithm Development Area (ADA), a simulated and smaller version of the operational IDPS. Baseline files are swapped out, not edited and the whole code package runs in one full orbit of Science Data Records (SDR's) using Calibration Look Up Tables (Cal LUT's) for the time of the orbit. The purpose of the regression test is to identify unintended outcomes. Overall the presentation provides a general and easy to follow overview of the JPSS Algorithm Change Process (ACP) and is intended to facility the audience understanding of a very extensive and complex process.

A new tool for supervised classification of satellite images available on web servers: Google Maps as a case study

NASA Astrophysics Data System (ADS)

García-Flores, Agustín.; Paz-Gallardo, Abel; Plaza, Antonio; Li, Jun

2016-10-01

This paper describes a new web platform dedicated to the classification of satellite images called Hypergim. The current implementation of this platform enables users to perform classification of satellite images from any part of the world thanks to the worldwide maps provided by Google Maps. To perform this classification, Hypergim uses unsupervised algorithms like Isodata and K-means. Here, we present an extension of the original platform in which we adapt Hypergim in order to use supervised algorithms to improve the classification results. This involves a significant modification of the user interface, providing the user with a way to obtain samples of classes present in the images to use in the training phase of the classification process. Another main goal of this development is to improve the runtime of the image classification process. To achieve this goal, we use a parallel implementation of the Random Forest classification algorithm. This implementation is a modification of the well-known CURFIL software package. The use of this type of algorithms to perform image classification is widespread today thanks to its precision and ease of training. The actual implementation of Random Forest was developed using CUDA platform, which enables us to exploit the potential of several models of NVIDIA graphics processing units using them to execute general purpose computing tasks as image classification algorithms. As well as CUDA, we use other parallel libraries as Intel Boost, taking advantage of the multithreading capabilities of modern CPUs. To ensure the best possible results, the platform is deployed in a cluster of commodity graphics processing units (GPUs), so that multiple users can use the tool in a concurrent way. The experimental results indicate that this new algorithm widely outperform the previous unsupervised algorithms implemented in Hypergim, both in runtime as well as precision of the actual classification of the images.

Mapping Global Ocean Surface Albedo from Satellite Observations: Models, Algorithms, and Datasets

NASA Astrophysics Data System (ADS)

Li, X.; Fan, X.; Yan, H.; Li, A.; Wang, M.; Qu, Y.

2018-04-01

Ocean surface albedo (OSA) is one of the important parameters in surface radiation budget (SRB). It is usually considered as a controlling factor of the heat exchange among the atmosphere and ocean. The temporal and spatial dynamics of OSA determine the energy absorption of upper level ocean water, and have influences on the oceanic currents, atmospheric circulations, and transportation of material and energy of hydrosphere. Therefore, various parameterizations and models have been developed for describing the dynamics of OSA. However, it has been demonstrated that the currently available OSA datasets cannot full fill the requirement of global climate change studies. In this study, we present a literature review on mapping global OSA from satellite observations. The models (parameterizations, the coupled ocean-atmosphere radiative transfer (COART), and the three component ocean water albedo (TCOWA)), algorithms (the estimation method based on reanalysis data, and the direct-estimation algorithm), and datasets (the cloud, albedo and radiation (CLARA) surface albedo product, dataset derived by the TCOWA model, and the global land surface satellite (GLASS) phase-2 surface broadband albedo product) of OSA have been discussed, separately.

Pre-Launch Tasks Proposed in our Contract of December 1991

NASA Technical Reports Server (NTRS)

1998-01-01

We propose, during the pre-EOS phase to: (1) develop, with other MODIS Team Members, a means of discriminating different major biome types with NDVI and other AVHRR-based data; (2) develop a simple ecosystem process model for each of these biomes, BIOME-BGC; (3) relate the seasonal trend of weekly composite NDVI to vegetation phenology and temperature limits to develop a satellite defined growing season for vegetation; and (4) define physiologically based energy to mass conversion factors for carbon and water for each biome. Our final core at-launch product will be simplified, completely satellite driven biome specific models for net primary production. We will build these biome specific satellite driven algorithms using a family of simple ecosystem process models as calibration models, collectively called BIOME-BGC, and establish coordination with an existing network of ecological study sites in order to test and validate these products. Field datasets will then be available for both BIOME-BGC development and testing, use for algorithm developments of other MODIS Team Members, and ultimately be our first test point for MODIS land vegetation products upon launch. We will use field sites from the National Science Foundation Long-Term Ecological Research network, and develop Glacier National Park as a major site for intensive validation.

Pre-Launch Tasks Proposed in our Contract of December 1991

NASA Technical Reports Server (NTRS)

Running, Steven W.; Nemani, Ramakrishna R.; Glassy, Joseph

1997-01-01

We propose, during the pre-EOS phase to: (1) develop, with other MODIS Team Members, a means of discriminating different major biome types with NDVI and other AVHRR-based data. (2) develop a simple ecosystem process model for each of these biomes, BIOME-BGC (3) relate the seasonal trend of weekly composite NDVI to vegetation phenology and temperature limits to develop a satellite defined growing season for vegetation; and (4) define physiologically based energy to mass conversion factors for carbon and water for each biome. Our final core at-launch product will be simplified, completely satellite driven biome specific models for net primary production. We will build these biome specific satellite driven algorithms using a family of simple ecosystem process models as calibration models, collectively called BIOME-BGC, and establish coordination with an existing network of ecological study sites in order to test and validate these products. Field datasets will then be available for both BIOME-BGC development and testing, use for algorithm developments of other MODIS Team Members, and ultimately be our first test point for MODIS land vegetation products upon launch. We will use field sites from the National Science Foundation Long-Term Ecological Research network, and develop Glacier National Park as a major site for intensive validation.

Application of heuristic satellite plan synthesis algorithms to requirements of the WARC-88 allotment plan

NASA Technical Reports Server (NTRS)

Heyward, Ann O.; Reilly, Charles H.; Walton, Eric K.; Mata, Fernando; Olen, Carl

1990-01-01

Creation of an Allotment Plan for the Fixed Satellite Service at the 1988 Space World Administrative Radio Conference (WARC) represented a complex satellite plan synthesis problem, involving a large number of planned and existing systems. Solutions to this problem at WARC-88 required the use of both automated and manual procedures to develop an acceptable set of system positions. Development of an Allotment Plan may also be attempted through solution of an optimization problem, known as the Satellite Location Problem (SLP). Three automated heuristic procedures, developed specifically to solve SLP, are presented. The heuristics are then applied to two specific WARC-88 scenarios. Solutions resulting from the fully automated heuristics are then compared with solutions obtained at WARC-88 through a combination of both automated and manual planning efforts.

Detection of supercooled liquid water-topped mixed-phase clouds >from shortwave-infrared satellite observations

NASA Astrophysics Data System (ADS)

NOH, Y. J.; Miller, S. D.; Heidinger, A. K.

2015-12-01

Many studies have demonstrated the utility of multispectral information from satellite passive radiometers for detecting and retrieving the properties of cloud globally, which conventionally utilizes shortwave- and thermal-infrared bands. However, the satellite-derived cloud information comes mainly from cloud top or represents a vertically integrated property. This can produce a large bias in determining cloud phase characteristics, in particular for mixed-phase clouds which are often observed to have supercooled liquid water at cloud top but a predominantly ice phase residing below. The current satellite retrieval algorithms may report these clouds simply as supercooled liquid without any further information regarding the presence of a sub-cloud-top ice phase. More accurate characterization of these clouds is very important for climate models and aviation applications. In this study, we present a physical basis and preliminary results for the algorithm development of supercooled liquid-topped mixed-phase cloud detection using satellite radiometer observations. The detection algorithm is based on differential absorption properties between liquid and ice particles in the shortwave-infrared bands. Solar reflectance data in narrow bands at 1.6 μm and 2.25 μm are used to optically probe below clouds for distinction between supercooled liquid-topped clouds with and without an underlying mixed phase component. Varying solar/sensor geometry and cloud optical properties are also considered. The spectral band combination utilized for the algorithm is currently available on Suomi NPP Visible/Infrared Imaging Radiometer Suite (VIIRS), Himawari-8 Advanced Himawari Imager (AHI), and the future GOES-R Advance Baseline Imager (ABI). When tested on simulated cloud fields from WRF model and synthetic ABI data, favorable results were shown with reasonable threat scores (0.6-0.8) and false alarm rates (0.1-0.2). An ARM/NSA case study applied to VIIRS data also indicated promising potential of the algorithm.

An optimization tool for satellite equipment layout

NASA Astrophysics Data System (ADS)

Qin, Zheng; Liang, Yan-gang; Zhou, Jian-ping

2018-01-01

Selection of the satellite equipment layout with performance constraints is a complex task which can be viewed as a constrained multi-objective optimization and a multiple criteria decision making problem. The layout design of a satellite cabin involves the process of locating the required equipment in a limited space, thereby satisfying various behavioral constraints of the interior and exterior environments. The layout optimization of satellite cabin in this paper includes the C.G. offset, the moments of inertia and the space debris impact risk of the system, of which the impact risk index is developed to quantify the risk to a satellite cabin of coming into contact with space debris. In this paper an optimization tool for the integration of CAD software as well as the optimization algorithms is presented, which is developed to automatically find solutions for a three-dimensional layout of equipment in satellite. The effectiveness of the tool is also demonstrated by applying to the layout optimization of a satellite platform.

Mission planning optimization of video satellite for ground multi-object staring imaging

NASA Astrophysics Data System (ADS)

Cui, Kaikai; Xiang, Junhua; Zhang, Yulin

2018-03-01

This study investigates the emergency scheduling problem of ground multi-object staring imaging for a single video satellite. In the proposed mission scenario, the ground objects require a specified duration of staring imaging by the video satellite. The planning horizon is not long, i.e., it is usually shorter than one orbit period. A binary decision variable and the imaging order are used as the design variables, and the total observation revenue combined with the influence of the total attitude maneuvering time is regarded as the optimization objective. Based on the constraints of the observation time windows, satellite attitude adjustment time, and satellite maneuverability, a constraint satisfaction mission planning model is established for ground object staring imaging by a single video satellite. Further, a modified ant colony optimization algorithm with tabu lists (Tabu-ACO) is designed to solve this problem. The proposed algorithm can fully exploit the intelligence and local search ability of ACO. Based on full consideration of the mission characteristics, the design of the tabu lists can reduce the search range of ACO and improve the algorithm efficiency significantly. The simulation results show that the proposed algorithm outperforms the conventional algorithm in terms of optimization performance, and it can obtain satisfactory scheduling results for the mission planning problem.

A Multi-Band Analytical Algorithm for Deriving Absorption and Backscattering Coefficients from Remote-Sensing Reflectance of Optically Deep Waters

NASA Technical Reports Server (NTRS)

Lee, Zhong-Ping; Carder, Kendall L.

2001-01-01

A multi-band analytical (MBA) algorithm is developed to retrieve absorption and backscattering coefficients for optically deep waters, which can be applied to data from past and current satellite sensors, as well as data from hyperspectral sensors. This MBA algorithm applies a remote-sensing reflectance model derived from the Radiative Transfer Equation, and values of absorption and backscattering coefficients are analytically calculated from values of remote-sensing reflectance. There are only limited empirical relationships involved in the algorithm, which implies that this MBA algorithm could be applied to a wide dynamic range of waters. Applying the algorithm to a simulated non-"Case 1" data set, which has no relation to the development of the algorithm, the percentage error for the total absorption coefficient at 440 nm a (sub 440) is approximately 12% for a range of 0.012 - 2.1 per meter (approximately 6% for a (sub 440) less than approximately 0.3 per meter), while a traditional band-ratio approach returns a percentage error of approximately 30%. Applying it to a field data set ranging from 0.025 to 2.0 per meter, the result for a (sub 440) is very close to that using a full spectrum optimization technique (9.6% difference). Compared to the optimization approach, the MBA algorithm cuts the computation time dramatically with only a small sacrifice in accuracy, making it suitable for processing large data sets such as satellite images. Significant improvements over empirical algorithms have also been achieved in retrieving the optical properties of optically deep waters.

Applications of neural network methods to the processing of earth observation satellite data.

PubMed

Loyola, Diego G

2006-03-01

The new generation of earth observation satellites carries advanced sensors that will gather very precise data for studying the Earth system and global climate. This paper shows that neural network methods can be successfully used for solving forward and inverse remote sensing problems, providing both accurate and fast solutions. Two examples of multi-neural network systems for the determination of cloud properties and for the retrieval of total columns of ozone using satellite data are presented. The developed algorithms based on multi-neural network are currently being used for the operational processing of European atmospheric satellite sensors and will play a key role in related satellite missions planed for the near future.

Real-Time PPP Based on the Coupling Estimation of Clock Bias and Orbit Error with Broadcast Ephemeris.

PubMed

Pan, Shuguo; Chen, Weirong; Jin, Xiaodong; Shi, Xiaofei; He, Fan

2015-07-22

Satellite orbit error and clock bias are the keys to precise point positioning (PPP). The traditional PPP algorithm requires precise satellite products based on worldwide permanent reference stations. Such an algorithm requires considerable work and hardly achieves real-time performance. However, real-time positioning service will be the dominant mode in the future. IGS is providing such an operational service (RTS) and there are also commercial systems like Trimble RTX in operation. On the basis of the regional Continuous Operational Reference System (CORS), a real-time PPP algorithm is proposed to apply the coupling estimation of clock bias and orbit error. The projection of orbit error onto the satellite-receiver range has the same effects on positioning accuracy with clock bias. Therefore, in satellite clock estimation, part of the orbit error can be absorbed by the clock bias and the effects of residual orbit error on positioning accuracy can be weakened by the evenly distributed satellite geometry. In consideration of the simple structure of pseudorange equations and the high precision of carrier-phase equations, the clock bias estimation method coupled with orbit error is also improved. Rovers obtain PPP results by receiving broadcast ephemeris and real-time satellite clock bias coupled with orbit error. By applying the proposed algorithm, the precise orbit products provided by GNSS analysis centers are rendered no longer necessary. On the basis of previous theoretical analysis, a real-time PPP system was developed. Some experiments were then designed to verify this algorithm. Experimental results show that the newly proposed approach performs better than the traditional PPP based on International GNSS Service (IGS) real-time products. The positioning accuracies of the rovers inside and outside the network are improved by 38.8% and 36.1%, respectively. The PPP convergence speeds are improved by up to 61.4% and 65.9%. The new approach can change the traditional PPP mode because of its advantages of independence, high positioning precision, and real-time performance. It could be an alternative solution for regional positioning service before global PPP service comes into operation.

Real-Time PPP Based on the Coupling Estimation of Clock Bias and Orbit Error with Broadcast Ephemeris

PubMed Central

Pan, Shuguo; Chen, Weirong; Jin, Xiaodong; Shi, Xiaofei; He, Fan

2015-01-01

Satellite orbit error and clock bias are the keys to precise point positioning (PPP). The traditional PPP algorithm requires precise satellite products based on worldwide permanent reference stations. Such an algorithm requires considerable work and hardly achieves real-time performance. However, real-time positioning service will be the dominant mode in the future. IGS is providing such an operational service (RTS) and there are also commercial systems like Trimble RTX in operation. On the basis of the regional Continuous Operational Reference System (CORS), a real-time PPP algorithm is proposed to apply the coupling estimation of clock bias and orbit error. The projection of orbit error onto the satellite-receiver range has the same effects on positioning accuracy with clock bias. Therefore, in satellite clock estimation, part of the orbit error can be absorbed by the clock bias and the effects of residual orbit error on positioning accuracy can be weakened by the evenly distributed satellite geometry. In consideration of the simple structure of pseudorange equations and the high precision of carrier-phase equations, the clock bias estimation method coupled with orbit error is also improved. Rovers obtain PPP results by receiving broadcast ephemeris and real-time satellite clock bias coupled with orbit error. By applying the proposed algorithm, the precise orbit products provided by GNSS analysis centers are rendered no longer necessary. On the basis of previous theoretical analysis, a real-time PPP system was developed. Some experiments were then designed to verify this algorithm. Experimental results show that the newly proposed approach performs better than the traditional PPP based on International GNSS Service (IGS) real-time products. The positioning accuracies of the rovers inside and outside the network are improved by 38.8% and 36.1%, respectively. The PPP convergence speeds are improved by up to 61.4% and 65.9%. The new approach can change the traditional PPP mode because of its advantages of independence, high positioning precision, and real-time performance. It could be an alternative solution for regional positioning service before global PPP service comes into operation. PMID:26205276

Pre-Launch Algorithms and Risk Reduction in Support of the Geostationary Lightning Mapper for GOES-R and Beyond

NASA Technical Reports Server (NTRS)

Goodman, Steven; Blakeslee, Richard; Koshak, William

2008-01-01

The Geostationary Lightning Mapper (GLM) is a single channel, near-IR optical transient event detector, used to detect, locate and measure total lightning activity over the full-disk as part of a 3-axis stabilized, geostationary weather satellite system. The next generation NOAA Geostationary Operational Environmental Satellite (GOES-R) series with a planned launch in 2014 will carry a GLM that will provide continuous day and night observations of lightning from the west coast of Africa (GOES-E) to New Zealand (GOES-W) when the constellation is fully operational. The mission objectives for the GLM are to 1) provide continuous,full-disk lightning measurements for storm warning and Nowcasting, 2) provide early warning of tornado activity, and 3) accumulate a long-term database to track decadal changes of lightning. The GLM owes its heritage to the NASA Lightning Imaging Sensor (1997-Present) and the Optical Transient Detector (1995-2000), which were developed for the Earth Observing System and have produced a combined 13 year data record of global lightning activity. Instrument formulation studies were completed in March 2007 and the implementation phase to develop a prototype model and up to four flight units is expected to begin in latter part of the year. In parallel with the instrument development, a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2B algorithms and applications. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds (e.g., Lightning Mapping Arrays in North Alabama and the Washington DC Metropolitan area) are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. Real time lightning mapping data provided to selected National Weather Service forecast offices in Southern and Eastern Region are also improving our understanding of the application of these data in the severe storm warning process and help to accelerate the development of the pre-launch algorithms and Nowcasting applications.

Toward an Objective Enhanced-V Detection Algorithm

NASA Technical Reports Server (NTRS)

Brunner, Jason; Feltz, Wayne; Moses, John; Rabin, Robert; Ackerman, Steven

2007-01-01

The area of coldest cloud tops above thunderstorms sometimes has a distinct V or U shape. This pattern, often referred to as an "enhanced-V' signature, has been observed to occur during and preceding severe weather in previous studies. This study describes an algorithmic approach to objectively detect enhanced-V features with observations from the Geostationary Operational Environmental Satellite and Low Earth Orbit data. The methodology consists of cross correlation statistics of pixels and thresholds of enhanced-V quantitative parameters. The effectiveness of the enhanced-V detection method will be examined using Geostationary Operational Environmental Satellite, MODerate-resolution Imaging Spectroradiometer, and Advanced Very High Resolution Radiometer image data from case studies in the 2003-2006 seasons. The main goal of this study is to develop an objective enhanced-V detection algorithm for future implementation into operations with future sensors, such as GOES-R.

Retrieving the Height of Smoke and Dust Aerosols by Synergistic Use of Multiple Satellite Sensors

NASA Technical Reports Server (NTRS)

Lee, Jaehwa; Hsu, N. Christina; Bettenhausen, Corey; Sayer, Andrew M.; Seftor, Colin J.; Jeong, Myeong-Jae

2016-01-01

The Aerosol Single scattering albedo and Height Estimation (ASHE) algorithm was first introduced in Jeong and Hsu (2008) to provide aerosol layer height and single scattering albedo (SSA) for biomass burning smoke aerosols. By using multiple satellite sensors synergistically, ASHE can provide the height information over much broader areas than lidar observations alone. The complete ASHE algorithm uses aerosol data from MODIS or VIIRS, OMI or OMPS, and CALIOP. A simplified algorithm also exists that does not require CALIOP data as long as the SSA of the aerosol layer is provided by another source. Several updates have recently been made: inclusion of dust layers in the retrieval process, better determination of the input aerosol layer height from CALIOP, improvement in aerosol optical depth (AOD) for nonspherical dust, development of quality assurance (QA) procedure, etc.

Next Generation of Air Quality Measurements from Geo Orbits: Breaking The Temporal Barrier

NASA Astrophysics Data System (ADS)

Gupta, P.; Levy, R. C.; Mattoo, S.; Remer, L.; Heidinger, A.

2017-12-01

NASA's dark target (DT) aerosol algorithm provides operational retrieval of atmospheric aerosols from multiple polar orbiting satellites. The DT algorithm, initially developed for MODIS observations, has been continuously improved since the first MODIS launch in early 2000. Now, we are adapting the DT algorithm to retrieve on new-generation geostationary (GEO) sensors, including the Advanced Himawari Imager (AHI) on Japan's Himawari-8 (H8) satellite and Advanced Baseline Imager (ABI) on NOAA's GOES-16 (or GOES-R). H8 is a weather geostationary satellite operating since July 2015, and AHI observes earth-atmosphere system over the Asia-Pacific region at spatial resolutions of 1km or less. GOES-R is launched in Nov 2016 and provides high temporal resolution observations over Americas. With 16 spectral channels, including 7 bands that observe similar wavelengths as the MODIS bands used for DT aerosol retrieval. Most exciting, however, is that both ABI and AHI provides full disk observations every 10-15 minutes and zoom mode observations every 30 second to 2.5 minutes. Therefore, spectral, spatial and temporal resolution observations from these GEO satellites provide opportunity to monitor atmospheric aerosols in the region, plus a new capability to monitor aerosol transport and aerosol/cloud diurnal cycles. In this paper, we will introduce retrieval results from AHI using the DT algorithm during the KORUS-AQ field campaign during summer 2016. These results are evaluated against surface measurements (e.g. AERONET). . We will also discuss, its potential applications in monitoring diurnal cycles of urban pollution, smoke and dust in the region. The same DT algorithm will also be adapted to retrieve aerosol properties using GOES-16 over Americas.

Concept of AHRS Algorithm Designed for Platform Independent Imu Attitude Alignment

NASA Astrophysics Data System (ADS)

Tomaszewski, Dariusz; Rapiński, Jacek; Pelc-Mieczkowska, Renata

2017-12-01

Nowadays, along with the advancement of technology one can notice the rapid development of various types of navigation systems. So far the most popular satellite navigation, is now supported by positioning results calculated with use of other measurement system. The method and manner of integration will depend directly on the destination of system being developed. To increase the frequency of readings and improve the operation of outdoor navigation systems, one will support satellite navigation systems (GPS, GLONASS ect.) with inertial navigation. Such method of navigation consists of several steps. The first stage is the determination of initial orientation of inertial measurement unit, called INS alignment. During this process, on the basis of acceleration and the angular velocity readings, values of Euler angles (pitch, roll, yaw) are calculated allowing for unambiguous orientation of the sensor coordinate system relative to external coordinate system. The following study presents the concept of AHRS (Attitude and heading reference system) algorithm, allowing to define the Euler angles.The study were conducted with the use of readings from low-cost MEMS cell phone sensors. Subsequently the results of the study were analyzed to determine the accuracy of featured algorithm. On the basis of performed experiments the legitimacy of developed algorithm was stated.

Accurate beacon positioning method for satellite-to-ground optical communication.

PubMed

Wang, Qiang; Tong, Ling; Yu, Siyuan; Tan, Liying; Ma, Jing

2017-12-11

In satellite laser communication systems, accurate positioning of the beacon is essential for establishing a steady laser communication link. For satellite-to-ground optical communication, the main influencing factors on the acquisition of the beacon are background noise and atmospheric turbulence. In this paper, we consider the influence of background noise and atmospheric turbulence on the beacon in satellite-to-ground optical communication, and propose a new locating algorithm for the beacon, which takes the correlation coefficient obtained by curve fitting for image data as weights. By performing a long distance laser communication experiment (11.16 km), we verified the feasibility of this method. Both simulation and experiment showed that the new algorithm can accurately obtain the position of the centroid of beacon. Furthermore, for the distortion of the light spot through atmospheric turbulence, the locating accuracy of the new algorithm was 50% higher than that of the conventional gray centroid algorithm. This new approach will be beneficial for the design of satellite-to ground optical communication systems.

Traffic sharing algorithms for hybrid mobile networks

NASA Technical Reports Server (NTRS)

Arcand, S.; Murthy, K. M. S.; Hafez, R.

1995-01-01

In a hybrid (terrestrial + satellite) mobile personal communications networks environment, a large size satellite footprint (supercell) overlays on a large number of smaller size, contiguous terrestrial cells. We assume that the users have either a terrestrial only single mode terminal (SMT) or a terrestrial/satellite dual mode terminal (DMT) and the ratio of DMT to the total terminals is defined gamma. It is assumed that the call assignments to and handovers between terrestrial cells and satellite supercells take place in a dynamic fashion when necessary. The objectives of this paper are twofold, (1) to propose and define a class of traffic sharing algorithms to manage terrestrial and satellite network resources efficiently by handling call handovers dynamically, and (2) to analyze and evaluate the algorithms by maximizing the traffic load handling capability (defined in erl/cell) over a wide range of terminal ratios (gamma) given an acceptable range of blocking probabilities. Two of the algorithms (G & S) in the proposed class perform extremely well for a wide range of gamma.

A Comprehensive Training Data Set for the Development of Satellite-Based Volcanic Ash Detection Algorithms

NASA Astrophysics Data System (ADS)

Schmidl, Marius

2017-04-01

We present a comprehensive training data set covering a large range of atmospheric conditions, including disperse volcanic ash and desert dust layers. These data sets contain all information required for the development of volcanic ash detection algorithms based on artificial neural networks, urgently needed since volcanic ash in the airspace is a major concern of aviation safety authorities. Selected parts of the data are used to train the volcanic ash detection algorithm VADUGS. They contain atmospheric and surface-related quantities as well as the corresponding simulated satellite data for the channels in the infrared spectral range of the SEVIRI instrument on board MSG-2. To get realistic results, ECMWF, IASI-based, and GEOS-Chem data are used to calculate all parameters describing the environment, whereas the software package libRadtran is used to perform radiative transfer simulations returning the brightness temperatures for each atmospheric state. As optical properties are a prerequisite for radiative simulations accounting for aerosol layers, the development also included the computation of optical properties for a set of different aerosol types from different sources. A description of the developed software and the used methods is given, besides an overview of the resulting data sets.

Fast Simulators for Satellite Cloud Optical Centroid Pressure Retrievals, 1. Evaluation of OMI Cloud Retrievals

NASA Technical Reports Server (NTRS)

Joiner, J.; Vasilkov, A. P.; Gupta, Pawan; Bhartia, P. K.; Veefkind, Pepijn; Sneep, Maarten; deHaan, Johan; Polonsky, Igor; Spurr, Robert

2011-01-01

We have developed a relatively simple scheme for simulating retrieved cloud optical centroid pressures (OCP) from satellite solar backscatter observations. We have compared simulator results with those from more detailed retrieval simulators that more fully account for the complex radiative transfer in a cloudy atmosphere. We used this fast simulator to conduct a comprehensive evaluation of cloud OCPs from the two OMI algorithms using collocated data from CloudSat and Aqua MODIS, a unique situation afforded by the A-train formation of satellites. We find that both OMI algorithms perform reasonably well and that the two algorithms agree better with each other than either does with the collocated CloudSat data. This indicates that patchy snow/ice, cloud 3D, and aerosol effects not simulated with the CloudSat data are affecting both algorithms similarly. We note that the collocation with CloudSat occurs mainly on the East side of OMI's swath. Therefore, we are not able to address cross-track biases in OMI cloud OCP retrievals. Our fast simulator may also be used to simulate cloud OCP from output generated by general circulation models (GCM) with appropriate account of cloud overlap. We have implemented such a scheme and plan to compare OMI data with GCM output in the near future.

Spatial Classification of Orchards and Vineyards with High Spatial Resolution Panchromatic Imagery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Warner, Timothy; Steinmaus, Karen L.

2005-02-01

New high resolution single spectral band imagery offers the capability to conduct image classifications based on spatial patterns in imagery. A classification algorithm based on autocorrelation patterns was developed to automatically extract orchards and vineyards from satellite imagery. The algorithm was tested on IKONOS imagery over Granger, WA, which resulted in a classification accuracy of 95%.

Ice surface temperature retrieval from AVHRR, ATSR, and passive microwave satellite data: Algorithm development and application

NASA Technical Reports Server (NTRS)

Key, Jeff; Maslanik, James; Steffen, Konrad

1994-01-01

During the first half of our second project year we have accomplished the following: (1) acquired a new AVHRR data set for the Beaufort Sea area spanning an entire year; (2) acquired additional ATSR data for the Arctic and Antarctic now totaling over seven months; (3) refined our AVHRR Arctic and Antarctic ice surface temperature (IST) retrieval algorithm, including work specific to Greenland; (4) developed ATSR retrieval algorithms for the Arctic and Antarctic, including work specific to Greenland; (5) investigated the effects of clouds and the atmosphere on passive microwave 'surface' temperature retrieval algorithms; (6) generated surface temperatures for the Beaufort Sea data set, both from AVHRR and SSM/I; and (7) continued work on compositing GAC data for coverage of the entire Arctic and Antarctic. During the second half of the year we will continue along these same lines, and will undertake a detailed validation study of the AVHRR and ATSR retrievals using LEADEX and the Beaufort Sea year-long data. Cloud masking methods used for the AVHRR will be modified for use with the ATSR. Methods of blending in situ and satellite-derived surface temperature data sets will be investigated.

Atmospheric Correction Prototype Algorithm for High Spatial Resolution Multispectral Earth Observing Imaging Systems

NASA Technical Reports Server (NTRS)

Pagnutti, Mary

2006-01-01

This viewgraph presentation reviews the creation of a prototype algorithm for atmospheric correction using high spatial resolution earth observing imaging systems. The objective of the work was to evaluate accuracy of a prototype algorithm that uses satellite-derived atmospheric products to generate scene reflectance maps for high spatial resolution (HSR) systems. This presentation focused on preliminary results of only the satellite-based atmospheric correction algorithm.

Proportional fair scheduling algorithm based on traffic in satellite communication system

NASA Astrophysics Data System (ADS)

Pan, Cheng-Sheng; Sui, Shi-Long; Liu, Chun-ling; Shi, Yu-Xin

2018-02-01

In the satellite communication network system, in order to solve the problem of low system capacity and user fairness in multi-user access to satellite communication network in the downlink, combined with the characteristics of user data service, an algorithm study on throughput capacity and user fairness scheduling is proposed - Proportional Fairness Algorithm Based on Traffic(B-PF). The algorithm is improved on the basis of the proportional fairness algorithm in the wireless communication system, taking into account the user channel condition and caching traffic information. The user outgoing traffic is considered as the adjustment factor of the scheduling priority and presents the concept of traffic satisfaction. Firstly,the algorithm calculates the priority of the user according to the scheduling algorithm and dispatches the users with the highest priority. Secondly, when a scheduled user is the business satisfied user, the system dispatches the next priority user. The simulation results show that compared with the PF algorithm, B-PF can improve the system throughput, the business satisfaction and fairness.

SMMR Simulator radiative transfer calibration model. 2: Algorithm development

NASA Technical Reports Server (NTRS)

Link, S.; Calhoon, C.; Krupp, B.

1980-01-01

Passive microwave measurements performed from Earth orbit can be used to provide global data on a wide range of geophysical and meteorological phenomena. A Scanning Multichannel Microwave Radiometer (SMMR) is being flown on the Nimbus-G satellite. The SMMR Simulator duplicates the frequency bands utilized in the spacecraft instruments through an amalgamate of radiometer systems. The algorithm developed utilizes data from the fall 1978 NASA CV-990 Nimbus-G underflight test series and subsequent laboratory testing.

A new bio-optical algorithm for the remote sensing of algal blooms in complex ocean waters

NASA Astrophysics Data System (ADS)

Shanmugam, Palanisamy

2011-04-01

A new bio-optical algorithm has been developed to provide accurate assessments of chlorophyll a (Chl a) concentration for detection and mapping of algal blooms from satellite data in optically complex waters, where the presence of suspended sediments and dissolved substances can interfere with phytoplankton signal and thus confound conventional band ratio algorithms. A global data set of concurrent measurements of pigment concentration and radiometric reflectance was compiled and used to develop this algorithm that uses the normalized water-leaving radiance ratios along with an algal bloom index (ABI) between three visible bands to determine Chl a concentrations. The algorithm is derived using Sea-viewing Wide Field-of-view Sensor bands, and it is subsequently tuned to be applicable to Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua data. When compared with large in situ data sets and satellite matchups in a variety of coastal and ocean waters the present algorithm makes good retrievals of the Chl a concentration and shows statistically significant improvement over current global algorithms (e.g., OC3 and OC4v4). An examination of the performance of these algorithms on several MODIS/Aqua images in complex waters of the Arabian Sea and west Florida shelf shows that the new algorithm provides a better means for detecting and differentiating algal blooms from other turbid features, whereas the OC3 algorithm has significant errors although yielding relatively consistent results in clear waters. These findings imply that, provided that an accurate atmospheric correction scheme is available to deal with complex waters, the current MODIS/Aqua, MERIS and OCM data could be extensively used for quantitative and operational monitoring of algal blooms in various regional and global waters.

Clouds and the Earth's Radiant Energy System (CERES) Visualization Single Satellite Footprint (SSF) Plot Generator

NASA Technical Reports Server (NTRS)

Barsi, Julia A.

1995-01-01

The first Clouds and the Earth's Radiant Energy System (CERES) instrument will be launched in 1997 to collect data on the Earth's radiation budget. The data retrieved from the satellite will be processed through twelve subsystems. The Single Satellite Footprint (SSF) plot generator software was written to assist scientists in the early stages of CERES data analysis, producing two-dimensional plots of the footprint radiation and cloud data generated by one of the subsystems. Until the satellite is launched, however, software developers need verification tools to check their code. This plot generator will aid programmers by geolocating algorithm result on a global map.

An asymptotic method for estimating the vertical ozone distribution in the Earth's atmosphere from satellite measurements of backscattered solar UV-radiation

NASA Technical Reports Server (NTRS)

Ishov, Alexander G.

1994-01-01

An asymptotic approach to solution of the inverse problems of remote sensing is presented. It consists in changing integral operators characteristic of outgoing radiation into their asymptotic analogues. Such approach does not add new principal uncertainties into the problem and significantly reduces computation time that allows to develop the real (or about) time algorithms for interpretation of satellite measurements. The asymptotic approach has been realized for estimating vertical ozone distribution from satellite measurements of backscatter solar UV radiation in the Earth's atmosphere.

Comparison of GOES Cloud Classification Algorithms Employing Explicit and Implicit Physics

NASA Technical Reports Server (NTRS)

Bankert, Richard L.; Mitrescu, Cristian; Miller, Steven D.; Wade, Robert H.

2009-01-01

Cloud-type classification based on multispectral satellite imagery data has been widely researched and demonstrated to be useful for distinguishing a variety of classes using a wide range of methods. The research described here is a comparison of the classifier output from two very different algorithms applied to Geostationary Operational Environmental Satellite (GOES) data over the course of one year. The first algorithm employs spectral channel thresholding and additional physically based tests. The second algorithm was developed through a supervised learning method with characteristic features of expertly labeled image samples used as training data for a 1-nearest-neighbor classification. The latter's ability to identify classes is also based in physics, but those relationships are embedded implicitly within the algorithm. A pixel-to-pixel comparison analysis was done for hourly daytime scenes within a region in the northeastern Pacific Ocean. Considerable agreement was found in this analysis, with many of the mismatches or disagreements providing insight to the strengths and limitations of each classifier. Depending upon user needs, a rule-based or other postprocessing system that combines the output from the two algorithms could provide the most reliable cloud-type classification.

Development of New Research-Quality Low-Resource Magnetometers for Small Satellites

NASA Technical Reports Server (NTRS)

Moldwin, Mark; Hunter, Roger C.; Baker, Christopher

2017-01-01

Researchers from the University of Michigan (UM) and NASA Goddard Spaceflight Center (GSFC) are partnering to develop new types of magnetometers for use on future small satellites. These new instruments not only fulfill stringent requirements for low-amplitude and high-precision measurements, they are also enabling the team to develop a new approach to achieve high-quality magnetic measurements from space, without the need for a boom. Typically, space-based magnetometers are deployed on a boom that extends from the space vehicle to reduce exposure of magnetic noise emanating from the spacecraft, which could potentially contaminate measurements. The UMNASA team has developed algorithms to identify and eliminate spacecraft magnetic noise, which will allow placement of these economical, science-grade instrument magnetometers on and inside the satellite bus, instead of on a boom.

An orbital emulator for pursuit-evasion game theoretic sensor management

NASA Astrophysics Data System (ADS)

Shen, Dan; Wang, Tao; Wang, Gang; Jia, Bin; Wang, Zhonghai; Chen, Genshe; Blasch, Erik; Pham, Khanh

2017-05-01

This paper develops and evaluates an orbital emulator (OE) for space situational awareness (SSA). The OE can produce 3D satellite movements using capabilities generated from omni-wheeled robot and robotic arm motion methods. The 3D motion of a satellite is partitioned into the movements in the equatorial plane and the up-down motions in the vertical plane. The 3D actions are emulated by omni-wheeled robot models while the up-down motions are performed by a stepped-motor-controlled-ball along a rod (robotic arm), which is attached to the robot. For multiple satellites, a fast map-merging algorithm is integrated into the robot operating system (ROS) and simultaneous localization and mapping (SLAM) routines to locate the multiple robots in the scene. The OE is used to demonstrate a pursuit-evasion (PE) game theoretic sensor management algorithm, which models conflicts between a space-based-visible (SBV) satellite (as pursuer) and a geosynchronous (GEO) satellite (as evader). The cost function of the PE game is based on the informational entropy of the SBV-tracking-GEO scenario. GEO can maneuver using a continuous and low thruster. The hard-in-loop space emulator visually illustrates the SSA problem solution based PE game.

Satellite Retrieval of Atmospheric Water Budget over Gulf of Mexico- Caribbean Basin: Seasonal Variability

NASA Technical Reports Server (NTRS)

Smith, Eric A.; Santos, Pablo; Einaudi, Franco (Technical Monitor)

2001-01-01

This study presents results from a multi-satellite/multi-sensor retrieval system designed to obtain the atmospheric water budget over the open ocean. A combination of hourly-sampled monthly datasets derived from the GOES-8 5 Imager and the DMSP 7-channel passive microwave radiometer (SSM/I) have been acquired for the Gulf of Mexico-Caribbean Sea basin. Whereas the methodology is being tested over this basin, the retrieval system is designed for portability to any open-ocean region. Algorithm modules using the different datasets to retrieve individual geophysical parameters needed in the water budget equation are designed in a manner that takes advantage of the high temporal resolution of the GOES-8 measurements, as well as the physical relationships inherent to the SSM/I passive microwave signals in conjunction with water vapor, cloud liquid water, and rainfall. The methodology consists of retrieving the precipitation, surface evaporation, and vapor-cloud water storage terms in the atmospheric water balance equation from satellite techniques, with the water vapor advection term being obtained as the residue needed for balance. Thus, we have sought to develop a purely satellite-based method for obtaining the full set of terms in the atmospheric water budget equation without requiring in situ sounding information on the wind profile. The algorithm is partly validated by first cross-checking all the algorithm components through multiple-algorithm retrieval intercomparisons. More fundamental validation is obtained by directly comparing water vapor transports into the targeted basin diagnosed from the satellite algorithm to those obtained observationally from a network of land-based upper air stations that nearly uniformly surround the basin. Total columnar atmospheric water budget results will be presented for an extended annual cycle consisting of the months of October-97, January-98, April-98, July-98, October-98, and January-1999. These results are used to emphasize the changing relationship in E-P, as well as in the varying roles of storage and advection in balancing E-P both on daily and monthly time scales and on localized and basin space scales. Results from the algorithm-to-algorithm intercomparisons will also be presented in the context of sensitivity testing to help understand the intrinsic uncertainties in the water budget terms.

Sensor Calibration and Ocean Products for TRMM Microwave Radiometer

NASA Technical Reports Server (NTRS)

Wentz, Frank J.; Lawrence, Richard J. (Technical Monitor)

2003-01-01

During the three years of finding, we have carefully corrected for two sensor/platform problems, developed a physically based retrieval algorithm to calculate SST, wind speed, water vapor, cloud liquid water and rain rates, validated these variables, and demonstrated that satellite microwave radiometers can provide very accurate SST retrievals through clouds. Prior to this, there was doubt by some scientists that the technique of microwave SST retrieval from satellites is a viable option. We think we have put these concerns to rest, and look forward to making microwave SSTs a standard component of the Earth science data sets. Our TMI SSTs were featured on several network news broadcasts and were reported in Science magazine. Additionally, we have developed a SST algorithm for VIRS to facilitate IR/MW inter-comparisons and completed research into diurnal cycles and air-sea interactions.

Sensor Calibration and Ocean Products for TRMM Microwave Radiometer

NASA Technical Reports Server (NTRS)

Lawrence, Richard J. (Technical Monitor); Wentz, Frank J.

2003-01-01

During the three years of fundin& we have carefully corrected for two sensor/platform problems, developed a physically based retrieval algorithm to calculate SST, wind speed, water vapor, cloud liquid water and rain rates, validated these variables, and demonstrated that satellite microwave radiometers can provide very accurate SST retrievals through clouds. Prior to this, there was doubt by some scientists that the technique of microwave SST retrieval from satellites is a viable option. We think we have put these concerns to rest, and look forward to making microwave SSTs a standard component of the Earth science data sets. Our TMI SSTs were featured on several network news broadcasts and were reported in Science magazine. Additionally, we have developed a SST algorithm for VIRS to facilitate IR/MW inter-comparisons and completed research into diurnal cycles and air-sea interactions.

SMAP Soil Moisture Disaggregation using Land Surface Temperature and Vegetation Data

NASA Astrophysics Data System (ADS)

Fang, B.; Lakshmi, V.

2016-12-01

Soil moisture (SM) is a key parameter in agriculture, hydrology and ecology studies. The global SM retrievals have been providing by microwave remote sensing technology since late 1970s and many SM retrieval algorithms have been developed, calibrated and applied on satellite sensors such as AMSR-E (Advanced Microwave Scanning Radiometer for the Earth Observing System), AMSR-2 (Advanced Microwave Scanning Radiometer 2) and SMOS (Soil Moisture and Ocean Salinity). Particularly, SMAP (Soil Moisture Active/Passive) satellite, which was developed by NASA, was launched in January 2015. SMAP provides soil moisture products of 9 km and 36 km spatial resolutions which are not capable for research and applications of finer scale. Toward this issue, this study applied a SM disaggregation algorithm to disaggregate SMAP passive microwave soil moisture 36 km product. This algorithm was developed based on the thermal inertial relationship between daily surface temperature variation and daily average soil moisture which is modulated by vegetation condition, by using remote sensing retrievals from AVHRR (Advanced Very High Resolution Radiometer, MODIS (Moderate Resolution Imaging Spectroradiometer), SPOT (Satellite Pour l'Observation de la Terre), as well as Land Surface Model (LSM) output from NLDAS (North American Land Data Assimilation System). The disaggregation model was built at 1/8o spatial resolution on monthly basis and was implemented to calculate and disaggregate SMAP 36 km SM retrievals to 1 km resolution in Oklahoma. The SM disaggregation results were also validated using MESONET (Mesoscale Network) and MICRONET (Microscale Network) ground SM measurements.

Advances in Landslide Hazard Forecasting: Evaluation of Global and Regional Modeling Approach

NASA Technical Reports Server (NTRS)

Kirschbaum, Dalia B.; Adler, Robert; Hone, Yang; Kumar, Sujay; Peters-Lidard, Christa; Lerner-Lam, Arthur

2010-01-01

A prototype global satellite-based landslide hazard algorithm has been developed to identify areas that exhibit a high potential for landslide activity by combining a calculation of landslide susceptibility with satellite-derived rainfall estimates. A recent evaluation of this algorithm framework found that while this tool represents an important first step in larger-scale landslide forecasting efforts, it requires several modifications before it can be fully realized as an operational tool. The evaluation finds that the landslide forecasting may be more feasible at a regional scale. This study draws upon a prior work's recommendations to develop a new approach for considering landslide susceptibility and forecasting at the regional scale. This case study uses a database of landslides triggered by Hurricane Mitch in 1998 over four countries in Central America: Guatemala, Honduras, EI Salvador and Nicaragua. A regional susceptibility map is calculated from satellite and surface datasets using a statistical methodology. The susceptibility map is tested with a regional rainfall intensity-duration triggering relationship and results are compared to global algorithm framework for the Hurricane Mitch event. The statistical results suggest that this regional investigation provides one plausible way to approach some of the data and resolution issues identified in the global assessment, providing more realistic landslide forecasts for this case study. Evaluation of landslide hazards for this extreme event helps to identify several potential improvements of the algorithm framework, but also highlights several remaining challenges for the algorithm assessment, transferability and performance accuracy. Evaluation challenges include representation errors from comparing susceptibility maps of different spatial resolutions, biases in event-based landslide inventory data, and limited nonlandslide event data for more comprehensive evaluation. Additional factors that may improve algorithm performance accuracy include incorporating additional triggering factors such as tectonic activity, anthropogenic impacts and soil moisture into the algorithm calculation. Despite these limitations, the methodology presented in this regional evaluation is both straightforward to calculate and easy to interpret, making results transferable between regions and allowing findings to be placed within an inter-comparison framework. The regional algorithm scenario represents an important step in advancing regional and global-scale landslide hazard assessment and forecasting.

Cloud cover determination in polar regions from satellite imagery

NASA Technical Reports Server (NTRS)

Barry, R. G.; Key, J.

1989-01-01

The objectives are to develop a suitable validation data set for evaluating the effectiveness of the International Satellite Cloud Climatology Project (ISCCP) algorithm for cloud retrieval in polar regions, to identify limitations of current procedures and to explore potential means to remedy them using textural classifiers, and to compare synoptic cloud data from model runs with observations. Toward the first goal, a polar data set consisting of visible, thermal, and passive microwave data was developed. The AVHRR and SMMR data were digitally merged to a polar stereographic projection with an effective pixel size of 5 sq km. With this data set, two unconventional methods of classifying the imagery for the analysis of polar clouds and surfaces were examined: one based on fuzzy sets theory and another based on a trained neural network. An algorithm for cloud detection was developed from an early test version of the ISCCP algorithm. This algorithm includes the identification of surface types with passive microwave, then temporal tests at each pixel location in the cloud detection phase. Cloud maps and clear sky radiance composites for 5 day periods are produced. Algorithm testing and validation was done with both actural AVHRR/SMMR data, and simulated imagery. From this point in the algorithm, groups of cloud pixels are examined for their spectral and textural characteristics, and a procedure is developed for the analysis of cloud patterns utilizing albedo, IR temperature, and texture. In a completion of earlier work, empirical analyses of arctic cloud cover were explored through manual interpretations of DMSP imagery and compared to U.S. Air Force 3D-nephanalysis. Comparisons of observed cloudiness from existing climatologies to patterns computed by the GISS climate model were also made.

Verification of Satellite Rainfall Estimates from the Tropical Rainfall Measuring Mission over Ground Validation Sites

NASA Astrophysics Data System (ADS)

Fisher, B. L.; Wolff, D. B.; Silberstein, D. S.; Marks, D. M.; Pippitt, J. L.

2007-12-01

The Tropical Rainfall Measuring Mission's (TRMM) Ground Validation (GV) Program was originally established with the principal long-term goal of determining the random errors and systematic biases stemming from the application of the TRMM rainfall algorithms. The GV Program has been structured around two validation strategies: 1) determining the quantitative accuracy of the integrated monthly rainfall products at GV regional sites over large areas of about 500 km2 using integrated ground measurements and 2) evaluating the instantaneous satellite and GV rain rate statistics at spatio-temporal scales compatible with the satellite sensor resolution (Simpson et al. 1988, Thiele 1988). The GV Program has continued to evolve since the launch of the TRMM satellite on November 27, 1997. This presentation will discuss current GV methods of validating TRMM operational rain products in conjunction with ongoing research. The challenge facing TRMM GV has been how to best utilize rain information from the GV system to infer the random and systematic error characteristics of the satellite rain estimates. A fundamental problem of validating space-borne rain estimates is that the true mean areal rainfall is an ideal, scale-dependent parameter that cannot be directly measured. Empirical validation uses ground-based rain estimates to determine the error characteristics of the satellite-inferred rain estimates, but ground estimates also incur measurement errors and contribute to the error covariance. Furthermore, sampling errors, associated with the discrete, discontinuous temporal sampling by the rain sensors aboard the TRMM satellite, become statistically entangled in the monthly estimates. Sampling errors complicate the task of linking biases in the rain retrievals to the physics of the satellite algorithms. The TRMM Satellite Validation Office (TSVO) has made key progress towards effective satellite validation. For disentangling the sampling and retrieval errors, TSVO has developed and applied a methodology that statistically separates the two error sources. Using TRMM monthly estimates and high-resolution radar and gauge data, this method has been used to estimate sampling and retrieval error budgets over GV sites. More recently, a multi- year data set of instantaneous rain rates from the TRMM microwave imager (TMI), the precipitation radar (PR), and the combined algorithm was spatio-temporally matched and inter-compared to GV radar rain rates collected during satellite overpasses of select GV sites at the scale of the TMI footprint. The analysis provided a more direct probe of the satellite rain algorithms using ground data as an empirical reference. TSVO has also made significant advances in radar quality control through the development of the Relative Calibration Adjustment (RCA) technique. The RCA is currently being used to provide a long-term record of radar calibration for the radar at Kwajalein, a strategically important GV site in the tropical Pacific. The RCA technique has revealed previously undetected alterations in the radar sensitivity due to engineering changes (e.g., system modifications, antenna offsets, alterations of the receiver, or the data processor), making possible the correction of the radar rainfall measurements and ensuring the integrity of nearly a decade of TRMM GV observations and resources.

Development of algorithms for building inventory compilation through remote sensing and statistical inferencing

NASA Astrophysics Data System (ADS)

Sarabandi, Pooya

Building inventories are one of the core components of disaster vulnerability and loss estimations models, and as such, play a key role in providing decision support for risk assessment, disaster management and emergency response efforts. In may parts of the world inclusive building inventories, suitable for the use in catastrophe models cannot be found. Furthermore, there are serious shortcomings in the existing building inventories that include incomplete or out-dated information on critical attributes as well as missing or erroneous values for attributes. In this dissertation a set of methodologies for updating spatial and geometric information of buildings from single and multiple high-resolution optical satellite images are presented. Basic concepts, terminologies and fundamentals of 3-D terrain modeling from satellite images are first introduced. Different sensor projection models are then presented and sources of optical noise such as lens distortions are discussed. An algorithm for extracting height and creating 3-D building models from a single high-resolution satellite image is formulated. The proposed algorithm is a semi-automated supervised method capable of extracting attributes such as longitude, latitude, height, square footage, perimeter, irregularity index and etc. The associated errors due to the interactive nature of the algorithm are quantified and solutions for minimizing the human-induced errors are proposed. The height extraction algorithm is validated against independent survey data and results are presented. The validation results show that an average height modeling accuracy of 1.5% can be achieved using this algorithm. Furthermore, concept of cross-sensor data fusion for the purpose of 3-D scene reconstruction using quasi-stereo images is developed in this dissertation. The developed algorithm utilizes two or more single satellite images acquired from different sensors and provides the means to construct 3-D building models in a more economical way. A terrain-dependent-search algorithm is formulated to facilitate the search for correspondences in a quasi-stereo pair of images. The calculated heights for sample buildings using cross-sensor data fusion algorithm show an average coefficient of variation 1.03%. In order to infer structural-type and occupancy-type, i.e. engineering attributes, of buildings from spatial and geometric attributes of 3-D models, a statistical data analysis framework is formulated. Applications of "Classification Trees" and "Multinomial Logistic Models" in modeling the marginal probabilities of class-membership of engineering attributes are investigated. Adaptive statistical models to incorporate different spatial and geometric attributes of buildings---while inferring the engineering attributes---are developed in this dissertation. The inferred engineering attributes in conjunction with the spatial and geometric attributes derived from the imagery can be used to augment regional building inventories and therefore enhance the result of catastrophe models. In the last part of the dissertation, a set of empirically-derived motion-damage relationships based on the correlation of observed building performance with measured ground-motion parameters from 1994 Northridge and 1999 Chi-Chi Taiwan earthquakes are developed. Fragility functions in the form of cumulative lognormal distributions and damage probability matrices for several classes of buildings (wood, steel and concrete), as well as number of ground-motion intensity measures are developed and compared to currently-used motion-damage relationships.

Landscape Characterization of Arctic Ecosystems Using Data Mining Algorithms and Large Geospatial Datasets

NASA Astrophysics Data System (ADS)

Langford, Z. L.; Kumar, J.; Hoffman, F. M.

2015-12-01

Observations indicate that over the past several decades, landscape processes in the Arctic have been changing or intensifying. A dynamic Arctic landscape has the potential to alter ecosystems across a broad range of scales. Accurate characterization is useful to understand the properties and organization of the landscape, optimal sampling network design, measurement and process upscaling and to establish a landscape-based framework for multi-scale modeling of ecosystem processes. This study seeks to delineate the landscape at Seward Peninsula of Alaska into ecoregions using large volumes (terabytes) of high spatial resolution satellite remote-sensing data. Defining high-resolution ecoregion boundaries is difficult because many ecosystem processes in Arctic ecosystems occur at small local to regional scales, which are often resolved in by coarse resolution satellites (e.g., MODIS). We seek to use data-fusion techniques and data analytics algorithms applied to Phased Array type L-band Synthetic Aperture Radar (PALSAR), Interferometric Synthetic Aperture Radar (IFSAR), Satellite for Observation of Earth (SPOT), WorldView-2, WorldView-3, and QuickBird-2 to develop high-resolution (˜5m) ecoregion maps for multiple time periods. Traditional analysis methods and algorithms are insufficient for analyzing and synthesizing such large geospatial data sets, and those algorithms rarely scale out onto large distributed- memory parallel computer systems. We seek to develop computationally efficient algorithms and techniques using high-performance computing for characterization of Arctic landscapes. We will apply a variety of data analytics algorithms, such as cluster analysis, complex object-based image analysis (COBIA), and neural networks. We also propose to use representativeness analysis within the Seward Peninsula domain to determine optimal sampling locations for fine-scale measurements. This methodology should provide an initial framework for analyzing dynamic landscape trends in Arctic ecosystems, such as shrubification and disturbances, and integration of ecoregions into multi-scale models.

Comparison of remote sensing algorithms for retrieval of suspended particulate matter concentration from reflectance in coastal waters

NASA Astrophysics Data System (ADS)

Freeman, Lauren A.; Ackleson, Steven G.; Rhea, William Joseph

2017-10-01

Suspended particulate matter (SPM) is a key environmental indicator for rivers, estuaries, and coastal waters, which can be calculated from remote sensing reflectance obtained by an airborne or satellite imager. Here, algorithms from prior studies are applied to a dataset of in-situ at surface hyperspectral remote sensing reflectance, collected in three geographic regions representing different water types. These data show the optically inherent exponential nature of the relationship between reflectance and sediment concentration. However, linear models are also shown to provide a reasonable estimate of sediment concentration when utilized with care in similar conditions to those under which the algorithms were developed, particularly at lower SPM values (0 to 20 mg/L). Fifteen published SPM algorithms are tested, returning strong correlations of R2>0.7, and in most cases, R2>0.8. Very low SPM values show weaker correlation with algorithm calculated SPM that is not wavelength dependent. None of the tested algorithms performs well for high SPM values (>30 mg/L), with most algorithms underestimating SPM. A shift toward a smaller number of simple exponential or linear models relating satellite remote sensing reflectance to suspended sediment concentration with regional consideration will greatly aid larger spatiotemporal studies of suspended sediment trends.

New approaches to removing cloud shadows and evaluating the 380 nm surface reflectance for improved aerosol optical thickness retrievals from the GOSAT/TANSO-Cloud and Aerosol Imager

NASA Astrophysics Data System (ADS)

Fukuda, Satoru; Nakajima, Teruyuki; Takenaka, Hideaki; Higurashi, Akiko; Kikuchi, Nobuyuki; Nakajima, Takashi Y.; Ishida, Haruma

2013-12-01

satellite aerosol retrieval algorithm was developed to utilize a near-ultraviolet band of the Greenhouse gases Observing SATellite/Thermal And Near infrared Sensor for carbon Observation (GOSAT/TANSO)-Cloud and Aerosol Imager (CAI). At near-ultraviolet wavelengths, the surface reflectance over land is smaller than that at visible wavelengths. Therefore, it is thought possible to reduce retrieval error by using the near-ultraviolet spectral region. In the present study, we first developed a cloud shadow detection algorithm that uses first and second minimum reflectances of 380 nm and 680 nm based on the difference in Rayleigh scattering contribution for these two bands. Then, we developed a new surface reflectance correction algorithm, the modified Kaufman method, which uses minimum reflectance data at 680 nm and the NDVI to estimate the surface reflectance at 380 nm. This algorithm was found to be particularly effective at reducing the aerosol effect remaining in the 380 nm minimum reflectance; this effect has previously proven difficult to remove owing to the infrequent sampling rate associated with the three-day recursion period of GOSAT and the narrow CAI swath of 1000 km. Finally, we applied these two algorithms to retrieve aerosol optical thicknesses over a land area. Our results exhibited better agreement with sun-sky radiometer observations than results obtained using a simple surface reflectance correction technique using minimum radiances.

The GOES-R Series Geostationary Lightning Mapper (GLM)

NASA Technical Reports Server (NTRS)

Goodman, Steven J.; Blakeslee, Richard J.; Koshak, William J.; Mach, Douglas M.

2011-01-01

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. Superior spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), which will have just completed Critical Design Review and move forward into the construction phase of instrument development. The GLM will operate continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency. In parallel with the instrument development (an engineering development unit and 4 flight models), a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms, cal/val performance monitoring tools, and new applications. Proxy total lightning data from the NASA Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional ground-based lightning networks are being used to develop the pre-launch algorithms, test data sets, and applications, as well as improve our knowledge of thunderstorm initiation and evolution. In this presentation we review the planned implementation of the instrument and suite of operational algorithms

Monitoring and tracking the trans-Pacific transport of aerosols using multi-satellite aerosol optical depth composites

NASA Astrophysics Data System (ADS)

Naeger, Aaron R.; Gupta, Pawan; Zavodsky, Bradley T.; McGrath, Kevin M.

2016-06-01

The primary goal of this study was to generate a near-real time (NRT) aerosol optical depth (AOD) product capable of providing a comprehensive understanding of the aerosol spatial distribution over the Pacific Ocean, in order to better monitor and track the trans-Pacific transport of aerosols. Therefore, we developed a NRT product that takes advantage of observations from both low-earth orbiting and geostationary satellites. In particular, we utilize AOD products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) satellites. Then, we combine these AOD products with our own retrieval algorithms developed for the NOAA Geostationary Operational Environmental Satellite (GOES-15) and Japan Meteorological Agency (JMA) Multi-functional Transport Satellite (MTSAT-2) to generate a NRT daily AOD composite product. We present examples of the daily AOD composite product for a case study of trans-Pacific transport of Asian pollution and dust aerosols in mid-March 2014. Overall, the new product successfully tracks this aerosol plume during its trans-Pacific transport to the west coast of North America as the frequent geostationary observations lead to a greater coverage of cloud-free AOD retrievals equatorward of about 35° N, while the polar-orbiting satellites provide a greater coverage of AOD poleward of 35° N. However, we note several areas across the domain of interest from Asia to North America where the GOES-15 and MTSAT-2 retrieval algorithms can introduce significant uncertainties into the new product.

Comparing different approaches for an effective monitoring of forest fires based on MSG/SEVIRI images

NASA Astrophysics Data System (ADS)

Laneve, Giovanni

2010-05-01

The remote sensing sensors on board of geostationary satellite, as consequence of the high frequency of the observations, allow, in principle, the monitoring of these phenomena characterized by a fast dynamics. The only condition for is that the events to be monitored should be enough strong to be recognizable notwithstanding the low spatial resolution of the present geostationary systems (MSG/SEVIRI, GOES Imager, MTSAT). Apart from meteorological phenomena other events, like those associated with forest fires and/or volcanic eruption, are characterized by a very fast dynamics. These events are also associated with a very strong signal that make them observable by geostationary satellite in a quasi-continuous way. However, in order to make possible the detection of small fires by using the low resolution multi-spectral imagery provided by geostationary sensor like SEVIRI (3x3 km2 at the equator) new algorithms, capable to exploit it high observation frequency, has been developed. This paper is devoted to show the results obtained by comparing some of these algorithms trying to highlight their advantages and limits. The algorithms herein considered are these developed by CRPSM (SFIDE®), UNIBAS/CNR (RST-FIRES) and ESA-ESRIN (MDIFRM). In general, the new approaches proposed by each one of them are capable to promptly detect small fires making possible an operational utilization of the satellite based fire detection system in the fire fighting phases. In fact, these algorithms are quite different from these introduced in the past and specifically devoted to fire detection using low resolution multi-spectral imagery on LEO (Low Earth Orbit) satellite. Thanks to these differences they are capable of detecting sub-hectare (0.2 ha) forest fires providing an useful instrument for monitoring quasi-continuously forest fires, estimating the FRP (Fire Radiative Power), evaluating the burned biomass, retrieving the emission in the atmosphere.

The Passive Microwave Neural Network Precipitation Retrieval (PNPR) for AMSU/MHS and ATMS cross-track scanning radiometers

NASA Astrophysics Data System (ADS)

Sano', Paolo; Casella, Daniele; Panegrossi, Giulia; Cinzia Marra, Anna; Dietrich, Stefano

2016-04-01

Spaceborne microwave cross-track scanning radiometers, originally developed for temperature and humidity sounding, have shown great capabilities to provide a significant contribution in precipitation monitoring both in terms of measurement quality and spatial/temporal coverage. The Passive microwave Neural network Precipitation Retrieval (PNPR) algorithm for cross-track scanning radiometers, originally developed for the Advanced Microwave Sounding Unit/Microwave Humidity Sounder (AMSU-A/MHS) radiometers (on board the European MetOp and U.S. NOAA satellites), was recently newly designed to exploit the Advanced Technology Microwave Sounder (ATMS) on board the Suomi-NPP satellite and the future JPSS satellites. The PNPR algorithm is based on the Artificial Neural Network (ANN) approach. The main PNPR-ATMS algorithm changes with respect to PNPR-AMSU/MHS are the design and implementation of a new ANN able to manage the information derived from the additional ATMS channels (respect to the AMSU-A/MHS radiometer) and a new screening procedure for not-precipitating pixels. In order to achieve maximum consistency of the retrieved surface precipitation, both PNPR algorithms are based on the same physical foundation. The PNPR is optimized for the European and the African area. The neural network was trained using a cloud-radiation database built upon 94 cloud-resolving simulations over Europe and the Mediterranean and over the African area and radiative transfer model simulations of TB vectors consistent with the AMSU-A/MHS and ATMS channel frequencies, viewing angles, and view-angle dependent IFOV sizes along the scan projections. As opposed to other ANN precipitation retrieval algorithms, PNPR uses a unique ANN that retrieves the surface precipitation rate for all types of surface backgrounds represented in the training database, i.e., land (vegetated or arid), ocean, snow/ice or coast. This approach prevents different precipitation estimates from being inconsistent with one another when an observed precipitation system extends over two or more types of surfaces. As input data, the PNPR algorithm incorporates the TBs from selected channels, and various additional TBs-derived variables. Ancillary geographical/geophysical inputs (i.e., latitude, terrain height, surface type, season) are also considered during the training phase. The PNPR algorithm outputs consist of both the surface precipitation rate (along with the information on precipitation phase: liquid, mixed, solid) and a pixel-based quality index. We will illustrate the main features of the PNPR algorithm and will show results of a verification study over Europe and Africa. The study is based on the available ground-based radar and/or rain gauge network observations over the European area. In addition, results of the comparison with rainfall products available from the NASA/JAXA Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) (over the African area) and Global Precipitation Measurement (GPM) Dual frequency Precipitation Radar (DPR) will be shown. The analysis is built upon a two-years coincidence dataset of AMSU/MHS and ATMS observations with PR (2013-2014) and DPR (2014-2015). The PNPR is developed within the EUMETSAT H/SAF program (Satellite Application Facility for Operational Hydrology and Water Management), where it is used operationally towards the full exploitation of all microwave radiometers available in the GPM era. The algorithm will be tailored to the future European Microwave Sounder (MWS) onboard the MetOp-Second Generation (MetOp-SG) satellites.

CDRD and PNPR passive microwave precipitation retrieval algorithms: verification study over Africa and Southern Atlantic

NASA Astrophysics Data System (ADS)

Panegrossi, Giulia; Casella, Daniele; Cinzia Marra, Anna; Petracca, Marco; Sanò, Paolo; Dietrich, Stefano

2015-04-01

The ongoing NASA/JAXA Global Precipitation Measurement mission (GPM) requires the full exploitation of the complete constellation of passive microwave (PMW) radiometers orbiting around the globe for global precipitation monitoring. In this context the coherence of the estimates of precipitation using different passive microwave radiometers is a crucial need. We have developed two different passive microwave precipitation retrieval algorithms: one is the Cloud Dynamics Radiation Database algorithm (CDRD), a physically ¬based Bayesian algorithm for conically scanning radiometers (i.e., DMSP SSMIS); the other one is the Passive microwave Neural network Precipitation Retrieval (PNPR) algorithm for cross¬-track scanning radiometers (i.e., NOAA and MetOp¬A/B AMSU-¬A/MHS, and NPP Suomi ATMS). The algorithms, originally created for application over Europe and the Mediterranean basin, and used operationally within the EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF, http://hsaf.meteoam.it), have been recently modified and extended to Africa and Southern Atlantic for application to the MSG full disk area. The two algorithms are based on the same physical foundation, i.e., the same cloud-radiation model simulations as a priori information in the Bayesian solver and as training dataset in the neural network approach, and they also use similar procedures for identification of frozen background surface, detection of snowfall, and determination of a pixel based quality index of the surface precipitation retrievals. In addition, similar procedures for the screening of not ¬precipitating pixels are used. A novel algorithm for the detection of precipitation in tropical/sub-tropical areas has been developed. The precipitation detection algorithm shows a small rate of false alarms (also over arid/desert regions), a superior detection capability in comparison with other widely used screening algorithms, and it is applicable to all available PMW radiometers in the GPM constellation of satellites (including NPP Suomi ATMS, and GMI). Three years of SSMIS and AMSU/MHS data have been considered to carry out a verification study over Africa of the retrievals from the CDRD and PNPR algorithms. The precipitation products from the TRMM ¬Precipitation radar (PR) (TRMM product 2A25 and 2A23) have been used as ground truth. The results of this study aimed at assessing the accuracy of the precipitation retrievals in different climatic regions and precipitation regimes will be presented. Particular emphasis will be given to the analysis of the level of coherence of the precipitation estimates and patterns between the two algorithms exploiting different radiometers. Recent developments aimed at the full exploitation of the GPM constellation of satellites for optimal precipitation/drought monitoring will be also presented.

Comparison and testing of extended Kalman filters for attitude estimation of the Earth radiation budget satellite

NASA Technical Reports Server (NTRS)

Deutschmann, Julie; Bar-Itzhack, Itzhack Y.; Rokni, Mohammad

1990-01-01

The testing and comparison of two Extended Kalman Filters (EKFs) developed for the Earth Radiation Budget Satellite (ERBS) is described. One EKF updates the attitude quaternion using a four component additive error quaternion. This technique is compared to that of a second EKF, which uses a multiplicative error quaternion. A brief development of the multiplicative algorithm is included. The mathematical development of the additive EKF was presented in the 1989 Flight Mechanics/Estimation Theory Symposium along with some preliminary testing results using real spacecraft data. A summary of the additive EKF algorithm is included. The convergence properties, singularity problems, and normalization techniques of the two filters are addressed. Both filters are also compared to those from the ERBS operational ground support software, which uses a batch differential correction algorithm to estimate attitude and gyro biases. Sensitivity studies are performed on the estimation of sensor calibration states. The potential application of the EKF for real time and non-real time ground attitude determination and sensor calibration for future missions such as the Gamma Ray Observatory (GRO) and the Small Explorer Mission (SMEX) is also presented.

An orbit determination algorithm for small satellites based on the magnitude of the earth magnetic field

NASA Astrophysics Data System (ADS)

Zagorski, P.; Gallina, A.; Rachucki, J.; Moczala, B.; Zietek, S.; Uhl, T.

2018-06-01

Autonomous attitude determination systems based on simple measurements of vector quantities such as magnetic field and the Sun direction are commonly used in very small satellites. However, those systems always require knowledge of the satellite position. This information can be either propagated from orbital elements periodically uplinked from the ground station or measured onboard by dedicated global positioning system (GPS) receiver. The former solution sacrifices satellite autonomy while the latter requires additional sensors which may represent a significant part of mass, volume, and power budget in case of pico- or nanosatellites. Hence, it is thought that a system for onboard satellite position determination without resorting to GPS receivers would be useful. In this paper, a novel algorithm for determining the satellite orbit semimajor-axis is presented. The methods exploit only the magnitude of the Earth magnetic field recorded onboard by magnetometers. This represents the first step toward an extended algorithm that can determine all orbital elements of the satellite. The method is validated by numerical analysis and real magnetic field measurements.

Drought Impacts on Agricultural Production and Land Fallowing in California's Central Valley in 2015

NASA Technical Reports Server (NTRS)

Rosevelt, Carolyn; Melton, Forrest S.; Johnson, Lee; Guzman, Alberto; Verdin, James P.; Thenkabail, Prasad S.; Mueller, Rick; Jones, Jeanine; Willis, Patrick

2016-01-01

The ongoing drought in California substantially reduced surface water supplies for millions of acres of irrigated farmland in California's Central Valley. Rapid assessment of drought impacts on agricultural production can aid water managers in assessing mitigation options, and guide decision making with respect to mitigation of drought impacts. Satellite remote sensing offers an efficient way to provide quantitative assessments of drought impacts on agricultural production and increases in fallow acreage associated with reductions in water supply. A key advantage of satellite-based assessments is that they can provide a measure of land fallowing that is consistent across both space and time. We describe an approach for monthly and seasonal mapping of uncultivated agricultural acreage developed as part of a joint effort by USGS, USDA, NASA, and the California Department of Water Resources to provide timely assessments of land fallowing during drought events. This effort has used the Central Valley of California as a pilot region for development and testing of an operational approach. To provide quantitative measures of uncultivated agricultural acreage from satellite data early in the season, we developed a decision tree algorithm and applied it to time-series data from Landsat TM (Thematic Mapper), ETM+ (Enhanced Thematic Mapper Plus), OLI (Operational Land Imager), and MODIS (Moderate Resolution Imaging Spectroradiometer). Our effort has been focused on development of indicators of drought impacts in the March-August timeframe based on measures of crop development patterns relative to a reference period with average or above average rainfall. To assess the accuracy of the algorithms, monthly ground validation surveys were conducted across 650 fields from March-September in 2014 and 2015. We present the algorithm along with updated results from the accuracy assessment, and data and maps of land fallowing in the Central Valley in 2015.

Drought Impacts on Agricultural Production and Land Fallowing in California's Central Valley in 2015

NASA Astrophysics Data System (ADS)

Rosevelt, C.; Melton, F. S.; Johnson, L.; Guzman, A.; Verdin, J. P.; Thenkabail, P. S.; Mueller, R.; Jones, J.; Willis, P.

2015-12-01

The ongoing drought in California substantially reduced surface water supplies for millions of acres of irrigated farmland in California's Central Valley. Rapid assessment of drought impacts on agricultural production can aid water managers in assessing mitigation options, and guide decision making with respect to mitigation of drought impacts. Satellite remote sensing offers an efficient way to provide quantitative assessments of drought impacts on agricultural production and increases in fallow acreage associated with reductions in water supply. A key advantage of satellite-based assessments is that they can provide a measure of land fallowing that is consistent across both space and time. We describe an approach for monthly and seasonal mapping of uncultivated agricultural acreage developed as part of a joint effort by USGS, USDA, NASA, and the California Department of Water Resources to provide timely assessments of land fallowing during drought events. This effort has used the Central Valley of California as a pilot region for development and testing of an operational approach. To provide quantitative measures of uncultivated agricultural acreage from satellite data early in the season, we developed a decision tree algorithm and applied it to timeseries of data from Landsat TM, ETM+, OLI, and MODIS. Our effort has been focused on development of indicators of drought impacts in the March - August timeframe based on measures of crop development patterns relative to a reference period with average or above average rainfall. To assess the accuracy of the algorithms, monthly ground validation surveys were conducted across 650 fields from March - September in 2014 and 2015. We present the algorithm along with updated results from the accuracy assessment, and data and maps of land fallowing in the Central Valley in 2015.

Mapping Drought Impacts on Agricultural Production in California's Central Valley

NASA Astrophysics Data System (ADS)

Melton, F. S.; Guzman, A.; Johnson, L.; Rosevelt, C.; Verdin, J. P.; Dwyer, J. L.; Mueller, R.; Zakzeski, A.; Thenkabail, P. S.; Wallace, C.; Jones, J.; Windell, S.; Urness, J.; Teaby, A.; Hamblin, D.; Post, K. M.; Nemani, R. R.

2014-12-01

The ongoing drought in California has substantially reduced surface water supplies for millions of acres of irrigated farmland in California's Central Valley. Rapid assessment of drought impacts on agricultural production can aid water managers in assessing mitigation options, and guide decision making with respect to requests for local water transfers, county drought disaster designations, and allocation of emergency funds to mitigate drought impacts. Satellite remote sensing offers an efficient way to provide quantitative assessments of drought impacts on agricultural production and increases in idle acreage associated with reductions in water supply. A key advantage of satellite-based assessments is that they can provide a measure of land fallowing that is consistent across both space and time. We describe an approach for monthly and seasonal mapping of uncultivated agricultural acreage developed as part of a joint effort by USGS, USDA, NASA, and the California Department of Water Resources to provide timely assessments of land fallowing during drought events. This effort has used the Central Valley of California as a pilot region for development and testing of an operational approach. To provide quantitative measures of uncultivated agricultural acreage from satellite data early in the season, we developed a decision tree algorithm and applied it to timeseries of data from Landsat TM, ETM+, OLI, and MODIS. Our effort has been focused on development of indicators of drought impacts in the March - August timeframe based on measures of crop development patterns relative to a reference period with average or above average rainfall. To assess the accuracy of the algorithms, monthly ground validation surveys were conducted across 640 fields from March - September, 2014. We present the algorithm along with updated results from the accuracy assessment, and discuss potential applications to other regions.

Wind Retrievals under Rain for Passive Satellite Microwave Radiometers and its Applications to Hurricane Tracking

NASA Technical Reports Server (NTRS)

Meissner, Thomas; Wentz, Frank J.

2008-01-01

We have developed an algorithm that retrieves wind speed under rain using C-hand and X-band channels of passive microwave satellite radiometers. The spectral difference of the brightness temperature signals due to wind or rain allows to find channel combinations that are sufficiently sensitive to wind speed but little or not sensitive to rain. We &ve trained a statistical algorithm that applies under hurricane conditions and is able to measure wind speeds in hurricanes to an estimated accuracy of about 2 m/s. We have also developed a global algorithm, that is less accurate but can be applied under all conditions. Its estimated accuracy is between 2 and 5 mls, depending on wind speed and rain rate. We also extend the wind speed region in our model for the wind induced sea surface emissivity from currently 20 m/s to 40 mls. The data indicate that the signal starts to saturate above 30 mls. Finally, we make an assessment of the performance of wind direction retrievals from polarimetric radiometers as function of wind speed and rain rate

Development and validation of a MODIS colored dissolved organic matter (CDOM) algorithm in northwest Florida estuaries

EPA Science Inventory

Satellite remote sensing provides synoptic and frequent monitoring of water quality parameters that aids in determining the health of aquatic ecosystems and the development of effective management strategies. Northwest Florida estuaries are classified as optically-complex, or wat...

Identification of atmospheric fronts over the ocean with microwave measurements of water vapor and rain

NASA Technical Reports Server (NTRS)

Katsaros, Kristina B.; Bhatti, Iftekhar; Mcmurdie, Lynn A.; Patty, Grant W.

1989-01-01

This paper describes some basic research techniques and algorithms developed to diagnose fronts in cyclonic storms over the ocean with data from satellite-borne microwave radiometers. Methods are developed for flagging strong gradients in integrated atmospheric water vapor and the presence of rain by using data from the SSMR on board the polar orbiting Seasat and Nimbus-7 satellites. Examination of 65 frontal systems showed that the water vapor gradient flag correctly identified 86 percent of the fronts, while the precipitation flagged 91 percent. The two types of flags emphasize different portions of the cyclone and are therefore complementary. Ultimately, these techniques are intended for operational use with data from the Special Sensor Microwave Imager which was launched in June 1987 on a satellite in the Defense Meteorological Satellite Program (DMSP).

A 3D Cloud-Construction Algorithm for the EarthCARE Satellite Mission

NASA Technical Reports Server (NTRS)

Barker, H. W.; Jerg, M. P.; Wehr, T.; Kato, S.; Donovan, D. P.; Hogan, R. J.

2011-01-01

This article presents and assesses an algorithm that constructs 3D distributions of cloud from passive satellite imagery and collocated 2D nadir profiles of cloud properties inferred synergistically from lidar, cloud radar and imager data.

Aerosol physical properties from satellite horizon inversion

NASA Technical Reports Server (NTRS)

Gray, C. R.; Malchow, H. L.; Merritt, D. C.; Var, R. E.; Whitney, C. K.

1973-01-01

The feasibility is investigated of determining the physical properties of aerosols globally in the altitude region of 10 to 100 km from a satellite horizon scanning experiment. The investigation utilizes a horizon inversion technique previously developed and extended. Aerosol physical properties such as number density, size distribution, and the real and imaginary components of the index of refraction are demonstrated to be invertible in the aerosol size ranges (0.01-0.1 microns), (0.1-1.0 microns), (1.0-10 microns). Extensions of previously developed radiative transfer models and recursive inversion algorithms are displayed.

An Improved Algorithm for Retrieving Surface Downwelling Longwave Radiation from Satellite Measurements

NASA Technical Reports Server (NTRS)

Zhou, Yaping; Kratz, David P.; Wilber, Anne C.; Gupta, Shashi K.; Cess, Robert D.

2007-01-01

Zhou and Cess [2001] developed an algorithm for retrieving surface downwelling longwave radiation (SDLW) based upon detailed studies using radiative transfer model calculations and surface radiometric measurements. Their algorithm linked clear sky SDLW with surface upwelling longwave flux and column precipitable water vapor. For cloudy sky cases, they used cloud liquid water path as an additional parameter to account for the effects of clouds. Despite the simplicity of their algorithm, it performed very well for most geographical regions except for those regions where the atmospheric conditions near the surface tend to be extremely cold and dry. Systematic errors were also found for scenes that were covered with ice clouds. An improved version of the algorithm prevents the large errors in the SDLW at low water vapor amounts by taking into account that under such conditions the SDLW and water vapor amount are nearly linear in their relationship. The new algorithm also utilizes cloud fraction and cloud liquid and ice water paths available from the Cloud and the Earth's Radiant Energy System (CERES) single scanner footprint (SSF) product to separately compute the clear and cloudy portions of the fluxes. The new algorithm has been validated against surface measurements at 29 stations around the globe for Terra and Aqua satellites. The results show significant improvement over the original version. The revised Zhou-Cess algorithm is also slightly better or comparable to more sophisticated algorithms currently implemented in the CERES processing and will be incorporated as one of the CERES empirical surface radiation algorithms.

Satellite Snow-Cover Mapping: A Brief Review

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.

1995-01-01

Satellite snow mapping has been accomplished since 1966, initially using data from the reflective part of the electromagnetic spectrum, and now also employing data from the microwave part of the spectrum. Visible and near-infrared sensors can provide excellent spatial resolution from space enabling detailed snow mapping. When digital elevation models are also used, snow mapping can provide realistic measurements of snow extent even in mountainous areas. Passive-microwave satellite data permit global snow cover to be mapped on a near-daily basis and estimates of snow depth to be made, but with relatively poor spatial resolution (approximately 25 km). Dense forest cover limits both techniques and optical remote sensing is limited further by cloudcover conditions. Satellite remote sensing of snow cover with imaging radars is still in the early stages of research, but shows promise at least for mapping wet or melting snow using C-band (5.3 GHz) synthetic aperture radar (SAR) data. Observing System (EOS) Moderate Resolution Imaging Spectroradiometer (MODIS) data beginning with the launch of the first EOS platform in 1998. Digital maps will be produced that will provide daily, and maximum weekly global snow, sea ice and lake ice cover at 1-km spatial resolution. Statistics will be generated on the extent and persistence of snow or ice cover in each pixel for each weekly map, cloudcover permitting. It will also be possible to generate snow- and ice-cover maps using MODIS data at 250- and 500-m resolution, and to study and map snow and ice characteristics such as albedo. been under development. Passive-microwave data offer the potential for determining not only snow cover, but snow water equivalent, depth and wetness under all sky conditions. A number of algorithms have been developed to utilize passive-microwave brightness temperatures to provide information on snow cover and water equivalent. The variability of vegetative Algorithms are being developed to map global snow and ice cover using Earth Algorithms to map global snow cover using passive-microwave data have also cover and of snow grain size, globally, limits the utility of a single algorithm to map global snow cover.

An Unsupervised Anomalous Event Detection and Interactive Analysis Framework for Large-scale Satellite Data

NASA Astrophysics Data System (ADS)

LIU, Q.; Lv, Q.; Klucik, R.; Chen, C.; Gallaher, D. W.; Grant, G.; Shang, L.

2016-12-01

Due to the high volume and complexity of satellite data, computer-aided tools for fast quality assessments and scientific discovery are indispensable for scientists in the era of Big Data. In this work, we have developed a framework for automated anomalous event detection in massive satellite data. The framework consists of a clustering-based anomaly detection algorithm and a cloud-based tool for interactive analysis of detected anomalies. The algorithm is unsupervised and requires no prior knowledge of the data (e.g., expected normal pattern or known anomalies). As such, it works for diverse data sets, and performs well even in the presence of missing and noisy data. The cloud-based tool provides an intuitive mapping interface that allows users to interactively analyze anomalies using multiple features. As a whole, our framework can (1) identify outliers in a spatio-temporal context, (2) recognize and distinguish meaningful anomalous events from individual outliers, (3) rank those events based on "interestingness" (e.g., rareness or total number of outliers) defined by users, and (4) enable interactively query, exploration, and analysis of those anomalous events. In this presentation, we will demonstrate the effectiveness and efficiency of our framework in the application of detecting data quality issues and unusual natural events using two satellite datasets. The techniques and tools developed in this project are applicable for a diverse set of satellite data and will be made publicly available for scientists in early 2017.

Development of microwave rainfall retrieval algorithm for climate applications

NASA Astrophysics Data System (ADS)

KIM, J. H.; Shin, D. B.

2014-12-01

With the accumulated satellite datasets for decades, it is possible that satellite-based data could contribute to sustained climate applications. Level-3 products from microwave sensors for climate applications can be obtained from several algorithms. For examples, the Microwave Emission brightness Temperature Histogram (METH) algorithm produces level-3 rainfalls directly, whereas the Goddard profiling (GPROF) algorithm first generates instantaneous rainfalls and then temporal and spatial averaging process leads to level-3 products. The rainfall algorithm developed in this study follows a similar approach to averaging instantaneous rainfalls. However, the algorithm is designed to produce instantaneous rainfalls at an optimal resolution showing reduced non-linearity in brightness temperature (TB)-rain rate(R) relations. It is found that the resolution tends to effectively utilize emission channels whose footprints are relatively larger than those of scattering channels. This algorithm is mainly composed of a-priori databases (DBs) and a Bayesian inversion module. The DB contains massive pairs of simulated microwave TBs and rain rates, obtained by WRF (version 3.4) and RTTOV (version 11.1) simulations. To improve the accuracy and efficiency of retrieval process, data mining technique is additionally considered. The entire DB is classified into eight types based on Köppen climate classification criteria using reanalysis data. Among these sub-DBs, only one sub-DB which presents the most similar physical characteristics is selected by considering the thermodynamics of input data. When the Bayesian inversion is applied to the selected DB, instantaneous rain rate with 6 hours interval is retrieved. The retrieved monthly mean rainfalls are statistically compared with CMAP and GPCP, respectively.

Atmospheric correction using near-infrared bands for satellite ocean color data processing in the turbid western Pacific region.

PubMed

Wang, Menghua; Shi, Wei; Jiang, Lide

2012-01-16

A regional near-infrared (NIR) ocean normalized water-leaving radiance (nL(w)(λ)) model is proposed for atmospheric correction for ocean color data processing in the western Pacific region, including the Bohai Sea, Yellow Sea, and East China Sea. Our motivation for this work is to derive ocean color products in the highly turbid western Pacific region using the Geostationary Ocean Color Imager (GOCI) onboard South Korean Communication, Ocean, and Meteorological Satellite (COMS). GOCI has eight spectral bands from 412 to 865 nm but does not have shortwave infrared (SWIR) bands that are needed for satellite ocean color remote sensing in the turbid ocean region. Based on a regional empirical relationship between the NIR nL(w)(λ) and diffuse attenuation coefficient at 490 nm (K(d)(490)), which is derived from the long-term measurements with the Moderate-resolution Imaging Spectroradiometer (MODIS) on the Aqua satellite, an iterative scheme with the NIR-based atmospheric correction algorithm has been developed. Results from MODIS-Aqua measurements show that ocean color products in the region derived from the new proposed NIR-corrected atmospheric correction algorithm match well with those from the SWIR atmospheric correction algorithm. Thus, the proposed new atmospheric correction method provides an alternative for ocean color data processing for GOCI (and other ocean color satellite sensors without SWIR bands) in the turbid ocean regions of the Bohai Sea, Yellow Sea, and East China Sea, although the SWIR-based atmospheric correction approach is still much preferred. The proposed atmospheric correction methodology can also be applied to other turbid coastal regions.

Real-time estimation of ionospheric delay using GPS measurements

NASA Astrophysics Data System (ADS)

Lin, Lao-Sheng

1997-12-01

When radio waves such as the GPS signals propagate through the ionosphere, they experience an extra time delay. The ionospheric delay can be eliminated (to the first order) through a linear combination of L1 and L2 observations from dual-frequency GPS receivers. Taking advantage of this dispersive principle, one or more dual- frequency GPS receivers can be used to determine a model of the ionospheric delay across a region of interest and, if implemented in real-time, can support single-frequency GPS positioning and navigation applications. The research objectives of this thesis were: (1) to develop algorithms to obtain accurate absolute Total Electron Content (TEC) estimates from dual-frequency GPS observables, and (2) to develop an algorithm to improve the accuracy of real-time ionosphere modelling. In order to fulfil these objectives, four algorithms have been proposed in this thesis. A 'multi-day multipath template technique' is proposed to mitigate the pseudo-range multipath effects at static GPS reference stations. This technique is based on the assumption that the multipath disturbance at a static station will be constant if the physical environment remains unchanged from day to day. The multipath template, either single-day or multi-day, can be generated from the previous days' GPS data. A 'real-time failure detection and repair algorithm' is proposed to detect and repair the GPS carrier phase 'failures', such as the occurrence of cycle slips. The proposed algorithm uses two procedures: (1) application of a statistical test on the state difference estimated from robust and conventional Kalman filters in order to detect and identify the carrier phase failure, and (2) application of a Kalman filter algorithm to repair the 'identified carrier phase failure'. A 'L1/L2 differential delay estimation algorithm' is proposed to estimate GPS satellite transmitter and receiver L1/L2 differential delays. This algorithm, based on the single-site modelling technique, is able to estimate the sum of the satellite and receiver L1/L2 differential delay for each tracked GPS satellite. A 'UNSW grid-based algorithm' is proposed to improve the accuracy of real-time ionosphere modelling. The proposed algorithm is similar to the conventional grid-based algorithm. However, two modifications were made to the algorithm: (1) an 'exponential function' is adopted as the weighting function, and (2) the 'grid-based ionosphere model' estimated from the previous day is used to predict the ionospheric delay ratios between the grid point and reference points. (Abstract shortened by UMI.)

Improvements to the CERES Cloud Detection Algorithm using Himawari 8 Data and Validation using CALIPSO and CATS Lidar Observations

NASA Astrophysics Data System (ADS)

Trepte, Q.; Minnis, P.; Palikonda, R.; Yost, C. R.; Rodier, S. D.; Trepte, C. R.; McGill, M. J.

2016-12-01

Geostationary satellites provide continuous cloud and meteorological observations important for weather forecasting and for understanding climate processes. The Himawari-8 satellite represents a new generation of measurement capabilities with significantly improved resolution and enhanced spectral information. The satellite was launched in October 2014 by the Japanese Meteorological Agency and is centered at 140° E to provide coverage over eastern Asia and the western Pacific region. A cloud detection algorithm was developed as part of the CERES Cloud Mask algorithm using the Advanced Himawari Imager (AHI), a 16 channel multi-spectral imager. The algorithm was originally designed for use with Meteosat Second Generation (MSG) data and has been adapted for Himawari-8 AHI measurements. This paper will describe the improvements in the Himawari cloud mask including daytime ocean low cloud and aerosol discrimination, nighttime thin cirrus detection, and Australian desert and coastal cloud detection. The statistics from matched CERES Himawari cloud mask results with CALIPSO lidar data and with new observations from the CATS lidar will also be presented. A feature of the CATS instrument on board the International Space Station is that it gives information at different solar viewing times to examine the diurnal variation of clouds and this provides an ability to evaluate the performance of the cloud mask for different sun angles.

iss055e008318

NASA Image and Video Library

2018-04-02

iss055e008318 (April 2, 2018) --- Expedition 55 Flight Engineer Drew Feustel works inside the Japanese Kibo laboratory module with tiny internal satellites known as SPHERES, or Synchronized Position Hold, Engage, Reorient, Experimental Satellites. Feustel was operating the SPHERES for the Smoothing-Based Relative Navigation (SmoothNav) experiment which is developing an algorithm to obtain the most probable estimate of the relative positions and velocities between all spacecraft using all available sensor information, including past measurements.

Passive microwave algorithm development and evaluation

NASA Technical Reports Server (NTRS)

Petty, Grant W.

1995-01-01

The scientific objectives of this grant are: (1) thoroughly evaluate, both theoretically and empirically, all available Special Sensor Microwave Imager (SSM/I) retrieval algorithms for column water vapor, column liquid water, and surface wind speed; (2) where both appropriate and feasible, develop, validate, and document satellite passive microwave retrieval algorithms that offer significantly improved performance compared with currently available algorithms; and (3) refine and validate a novel physical inversion scheme for retrieving rain rate over the ocean. This report summarizes work accomplished or in progress during the first year of a three year grant. The emphasis during the first year has been on the validation and refinement of the rain rate algorithm published by Petty and on the analysis of independent data sets that can be used to help evaluate the performance of rain rate algorithms over remote areas of the ocean. Two articles in the area of global oceanic precipitation are attached.

Adaptive re-tracking algorithm for retrieval of water level variations and wave heights from satellite altimetry data for middle-sized inland water bodies

NASA Astrophysics Data System (ADS)

Troitskaya, Yuliya; Lebedev, Sergey; Soustova, Irina; Rybushkina, Galina; Papko, Vladislav; Baidakov, Georgy; Panyutin, Andrey

One of the recent applications of satellite altimetry originally designed for measurements of the sea level [1] is associated with remote investigation of the water level of inland waters: lakes, rivers, reservoirs [2-7]. The altimetry data re-tracking algorithms developed for open ocean conditions (e.g. Ocean-1,2) [1] often cannot be used in these cases, since the radar return is significantly contaminated by reflection from the land. The problem of minimization of errors in the water level retrieval for inland waters from altimetry measurements can be resolved by re-tracking satellite altimetry data. Recently, special re-tracking algorithms have been actively developed for re-processing altimetry data in the coastal zone when reflection from land strongly affects echo shapes: threshold re-tracking, The other methods of re-tracking (threshold re-tracking, beta-re-tracking, improved threshold re-tracking) were developed in [9-11]. The latest development in this field is PISTACH product [12], in which retracking bases on the classification of typical forms of telemetric waveforms in the coastal zones and inland water bodies. In this paper a novel method of regional adaptive re-tracking based on constructing a theoretical model describing the formation of telemetric waveforms by reflection from the piecewise constant model surface corresponding to the geography of the region is considered. It was proposed in [13, 14], where the algorithm for assessing water level in inland water bodies and in the coastal zone of the ocean with an error of about 10-15 cm was constructed. The algorithm includes four consecutive steps: - constructing a local piecewise model of a reflecting surface in the neighbourhood of the reservoir; - solving a direct problem by calculating the reflected waveforms within the framework of the model; - imposing restrictions and validity criteria for the algorithm based on waveform modelling; - solving the inverse problem by retrieving a tracking point by the improved threshold algorithm. The possibility of determination of significant wave height (SWH) in the lakes through a two-step adaptive retracking is also studied. Calculation of the parameter SWH for Gorky Reservoir from May 2010 to March 2014 showed the anomalously high values of SWH, derived from altimetry data [15], which means that the calibration of this SWH for inland waters is required. Calibration ground measurements were performed at Gorky reservoir in 2011-2013, when wave height, wind speed and air temperature were collected by equipment placed on a buoy [15] collocated with Jason-1 and Jason-2 altimetry data acquisition. The results obtained on the basis of standard algorithm and method for adaptive re-tracking at Rybinsk , Gorky , Kuibyshev , Saratov and Volgograd reservoirs and middle-sized lakes of Russia: Chany, Segozero, Hanko, Oneko, Beloye, water areas of which are intersected by the Jason-1,2 tracks, were compared and their correlation with the observed data of hydrological stations in reservoirs and lakes was investigated. It was noted that the Volgograd reservoir regional re-tracking to determine the water level , while the standard GDR data are practically absent. REFERENCES [1] AVISO/Altimetry. User Handbook. Merged TOPEX/ POSEIDON Products. Edition 3.0. AVISO. Toulouse., 1996. [2] C.M. Birkett et al., “Surface water dynamics in the Amazon Basin: Application of satellite radar altimetry,” J. Geophys. Res., vol. 107, pp. 8059, 2002. [3] G. Brown, “The average impulse response of a rough surface and its applications,” IEEE Trans. Antennas Propagat., vol. 25, pp. 67-74, 1977. [4] I.O. Campos et al., “Temporal variations of river basin waters from Topex/Poseidon satellite altimetry. Application to the Amazon basin,” Earth and Planetary Sciences, vol. 333, pp. 633-643, 2001. [5] A.V. Kouraev et al., “Ob’ river discharge from TOPEX/Poseidon satellite altimetry (1992-2002),” Rem. Sens. Environ., vol. 93, pp. 238-245, 2004. [6] S.A. Lebedev, and A.G. Kostianoy, Satellite Altimetry of the Caspian Sea. Moscow : MORE, [in Russian], 2005. [7] P. A. M. Berry et al., “Global inland water monitoring from multi-mission altimetry”, Geophys. Res. Lett., vol. 32, pp. L16401, 2005. [8] S. Calmant, and F. Seyler, “Continental surface waters from satellite altimetry,” Geosciences C.R., vol. 338, pp. 1113-1122, 2006. [9] C. H. Davis, “A robust threshold retracking algorithm for measuring ice sheet surface elevation change from satellite radar altimeters,” IEEE Trans. Geosci. Remote Sens., vol. 35, pp. 974-979, 1997. [10] X. Deng, and W. E. Featherstone, “A coastal retracking system for satellite radar altimeter waveforms: Application to ERS-2 around Australia,” J. Geophys. Res., vol. 111, pp. C06012, 2006. [11] J. Guo et al., “Lake level variations monitored with satellite altimetry waveform retracking,” IEEE J. Sel. Topics Appl. Earth Obs., vol. 2(2), pp. 80-86, 2009. [12] Mercier F., Rosmorduc V., Carrere L., Thibaut P., Coastal and Hydrology Altimetry product (PISTACH) handbook. Version 1.0. 2010. [13] Yu.Troitskaya et al., “Satellite altimetry of inland water bodies,” Water Resources, vol. 39(2), pp.184-199, 2012. [14] Yu.Troitskaya et al., “Adaptive retracking of Jason-1 altimetry data for inland waters: the example of the Gorky Reservoir”, Int. J. Rem. Sens., vol. 33, pp. 7559-7578, 2012. [15] Yu.Troitskaya et al., , "Adaptive retracking of Jason-1,2 satellite altimetry data for the Volga river reservoirs ," IEEE J. Sel. Topics Appl. Earth Obs., issue 99, 2013, doi: 10.1109/JSTARS.2013.2267092.

Modeling and characterization of the Earth Radiation Budget Experiment (ERBE) nonscanner and scanner sensors

NASA Technical Reports Server (NTRS)

Halyo, Nesim; Pandey, Dhirendra K.; Taylor, Deborah B.

1989-01-01

The Earth Radiation Budget Experiment (ERBE) is making high-absolute-accuracy measurements of the reflected solar and Earth-emitted radiation as well as the incoming solar radiation from three satellites: ERBS, NOAA-9, and NOAA-10. Each satellite has four Earth-looking nonscanning radiometers and three scanning radiometers. A fifth nonscanner, the solar monitor, measures the incoming solar radiation. The development of the ERBE sensor characterization procedures are described using the calibration data for each of the Earth-looking nonscanners and scanners. Sensor models for the ERBE radiometers are developed including the radiative exchange, conductive heat flow, and electronics processing for transient and steady state conditions. The steady state models are used to interpret the sensor outputs, resulting in the data reduction algorithms for the ERBE instruments. Both ground calibration and flight calibration procedures are treated and analyzed. The ground and flight calibration coefficients for the data reduction algorithms are presented.

Development of Great Lakes algorithms for the Nimbus-G coastal zone color scanner

NASA Technical Reports Server (NTRS)

Tanis, F. J.; Lyzenga, D. R.

1981-01-01

A series of experiments in the Great Lakes designed to evaluate the application of the Nimbus G satellite Coastal Zone Color Scanner (CZCS) were conducted. Absorption and scattering measurement data were reduced to obtain a preliminary optical model for the Great Lakes. Available optical models were used in turn to calculate subsurface reflectances for expected concentrations of chlorophyll-a pigment and suspended minerals. Multiple nonlinear regression techniques were used to derive CZCS water quality prediction equations from Great Lakes simulation data. An existing atmospheric model was combined with a water model to provide the necessary simulation data for evaluation of the preliminary CZCS algorithms. A CZCS scanner model was developed which accounts for image distorting scanner and satellite motions. This model was used in turn to generate mapping polynomials that define the transformation from the original image to one configured in a polyconic projection. Four computer programs (FORTRAN IV) for image transformation are presented.

Integration of SMAP and SMOS L-Band Observations

NASA Technical Reports Server (NTRS)

Bindlish, Rajat; Jackson, Thomas J.; Chan, Steven; Colliander, Andreas; Kerr, Yaan

2017-01-01

Soil Moisture Active Passive (SMAP) mission and the ESA Soil Moisture and Ocean Salinity (SMOS) missions provide brightness temperature and soil moisture estimates every 2-3 days. SMAP brightness temperature observations were compared with SMOS observations at 40 Degrees incidence angle. The brightness temperatures from the two missions are not consistent and have a bias of about 2.7K over land with respect to each other. SMAP and SMOS missions use different retrieval algorithms and ancillary datasets which result in further inconsistencies between the soil moisture products. The reprocessed constant-angle SMOS brightness temperatures were used in the SMAP soil moisture retrieval algorithm to develop a consistent multi-satellite product. The integrated product will have an increased global revisit frequency (1 day) and period of record that would be unattainable by either one of the satellites alone. Results from the development and validation of the integrated product will be presented.

Oceanography from satellites

NASA Technical Reports Server (NTRS)

Wilson, W. S.

1981-01-01

It is pointed out that oceanographers have benefited from the space program mainly through the increased efficiency it has brought to ship operations. For example, the Transit navigation system has enabled oceanographers to compile detailed maps of sea-floor properties and to more accurately locate moored subsurface instrumentation. General descriptions are given of instruments used in satellite observations (altimeter, color scanner, infrared radiometer, microwave radiometer, scatterometer, synthetic aperture radar). It is pointed out that because of the large volume of data that satellite instruments generate, the development of algorithms for converting the data into a form expressed in geophysical units has become especially important.

Development of a mobile satellite communication unit

NASA Technical Reports Server (NTRS)

Suzuki, Ryutaro; Ikegami, Tetsushi; Hamamoto, Naokazu; Taguchi, Tetsu; Endo, Nobuhiro; Yamamoto, Osamu; Ichiyoshi, Osamu

1988-01-01

A compact 210(W) x 280(H) x 330(D) mm mobile terminal capable of transmitting voice and data through L-band mobile satellites is described. The Voice Codec can convert an analog voice to or from digital codes at rates of 9.6, 8 and 4.8 kb/s by an MPC algorithm. The terminal functions with a single 12 V power supplied vehicle battery. The equipment can operate at any L-band frequency allocated for mobile uses in a full duplex mode and will soon be put into a field test via Japans's ETS-V satellite.

Ocean color measurements

NASA Technical Reports Server (NTRS)

Gordon, H. R.; Austin, R. W.; Clark, D. K.; Hovis, W. A.; Yentsch, C. S.

1985-01-01

Ocean color observations by the Coastal Zone color scanner (CZCS) aboard the Nimbus-7 satellite are discussed, together with the factors contributing to the 'apparent' color of the ocean. The CZCS optical systems and the tecniques for extraction of the phytoplankton pigment concentration and the diffuse attenuation coefficient K from the 'apparent' water color are described in detail. Special consideration is given to the use of biooptical algorithms and the development of the K algorithm for the CZCS imagery. It is shown that under typical atmospheric conditions, the pigment concentration can be extracted from the satellite imagery to within + or - 30 percent over concentration ranges from 0 to 5 mg/cu m for the Morel case 1 water (Morel and Prieur, 1977), to which the oceanic waters belong as a rule.

Autonomous Closed-Loop Tasking, Acquisition, Processing, and Evaluation for Situational Awareness Feedback

NASA Technical Reports Server (NTRS)

Frye, Stuart; Mandl, Dan; Cappelaere, Pat

2016-01-01

This presentation describes the closed loop satellite autonomy methods used to connect users and the assets on Earth Orbiter- 1 (EO-1) and similar satellites. The base layer is a distributed architecture based on Goddard Mission Services Evolution Concept (GMSEC) thus each asset still under independent control. Situational awareness is provided by a middleware layer through common Application Programmer Interface (API) to GMSEC components developed at GSFC. Users setup their own tasking requests, receive views into immediate past acquisitions in their area of interest, and into future feasibilities for acquisition across all assets. Automated notifications via pubsub feeds are returned to users containing published links to image footprints, algorithm results, and full data sets. Theme-based algorithms are available on-demand for processing.

Speech coding at 4800 bps for mobile satellite communications

NASA Technical Reports Server (NTRS)

Gersho, Allen; Chan, Wai-Yip; Davidson, Grant; Chen, Juin-Hwey; Yong, Mei

1988-01-01

A speech compression project has recently been completed to develop a speech coding algorithm suitable for operation in a mobile satellite environment aimed at providing telephone quality natural speech at 4.8 kbps. The work has resulted in two alternative techniques which achieve reasonably good communications quality at 4.8 kbps while tolerating vehicle noise and rather severe channel impairments. The algorithms are embodied in a compact self-contained prototype consisting of two AT and T 32-bit floating-point DSP32 digital signal processors (DSP). A Motorola 68HC11 microcomputer chip serves as the board controller and interface handler. On a wirewrapped card, the prototype's circuit footprint amounts to only 200 sq cm, and consumes about 9 watts of power.

Development of a generalized multi-pixel and multi-parameter satellite remote sensing algorithm for aerosol properties

NASA Astrophysics Data System (ADS)

Hashimoto, M.; Nakajima, T.; Takenaka, H.; Higurashi, A.

2013-12-01

We develop a new satellite remote sensing algorithm to retrieve the properties of aerosol particles in the atmosphere. In late years, high resolution and multi-wavelength, and multiple-angle observation data have been obtained by grand-based spectral radiometers and imaging sensors on board the satellite. With this development, optimized multi-parameter remote sensing methods based on the Bayesian theory have become popularly used (Turchin and Nozik, 1969; Rodgers, 2000; Dubovik et al., 2000). Additionally, a direct use of radiation transfer calculation has been employed for non-linear remote sensing problems taking place of look up table methods supported by the progress of computing technology (Dubovik et al., 2011; Yoshida et al., 2011). We are developing a flexible multi-pixel and multi-parameter remote sensing algorithm for aerosol optical properties. In this algorithm, the inversion method is a combination of the MAP method (Maximum a posteriori method, Rodgers, 2000) and the Phillips-Twomey method (Phillips, 1962; Twomey, 1963) as a smoothing constraint for the state vector. Furthermore, we include a radiation transfer calculation code, Rstar (Nakajima and Tanaka, 1986, 1988), numerically solved each time in iteration for solution search. The Rstar-code has been directly used in the AERONET operational processing system (Dubovik and King, 2000). Retrieved parameters in our algorithm are aerosol optical properties, such as aerosol optical thickness (AOT) of fine mode, sea salt, and dust particles, a volume soot fraction in fine mode particles, and ground surface albedo of each observed wavelength. We simultaneously retrieve all the parameters that characterize pixels in each of horizontal sub-domains consisting the target area. Then we successively apply the retrieval method to all the sub-domains in the target area. We conducted numerical tests for the retrieval of aerosol properties and ground surface albedo for GOSAT/CAI imager data to test the algorithm for the land area. In this test, we simulated satellite-observed radiances for a sub-domain consisting of 5 by 5 pixels by the Rstar code assuming wavelengths of 380, 674, 870 and 1600 [nm], atmospheric condition of the US standard atmosphere, and the several aerosol and ground surface conditions. The result of the experiment showed that AOTs of fine mode and dust particles, soot fraction and ground surface albedo at the wavelength of 674 [nm] are retrieved within absolute value differences of 0.04, 0.01, 0.06 and 0.006 from the true value, respectively, for the case of dark surface, and also, for the case of blight surface, 0.06, 0.03, 0.04 and 0.10 from the true value, respectively. We will conduct more tests to study the information contents of parameters needed for aerosol and land surface remote sensing with different boundary conditions among sub-domains.

Near-Real-Time Detection and Monitoring of Intense Pyroconvection from Geostationary Satellites

NASA Astrophysics Data System (ADS)

Peterson, D. A.; Fromm, M. D.; Hyer, E. J.; Surratt, M. L.; Solbrig, J. E.; Campbell, J. R.

2016-12-01

Intense fire-triggered thunderstorms, known as pyrocumulonimbus (or pyroCb), can alter fire behavior, influence smoke plume trajectories, and hinder fire suppression efforts. PyroCb are also known for injecting a significant quantity of aerosol mass into the upper-troposphere and lower-stratosphere (UTLS). Near-real-time (NRT) detection and monitoring of pyroCb is highly desirable for a variety of forecasting and research applications. The Naval Research Laboratory (NRL) recently developed the first automated NRT pyroCb detection algorithm for geostationary satellite sensors. The algorithm uses multispectral infrared observations to isolate deep convective clouds with the distinct microphysical signal of pyroCb. Application of this algorithm to 88 intense wildfires observed during the 2013 fire season in western North America resulted in detection of individual intense events, pyroCb embedded within traditional convection, and multiple, short-lived pulses of activity. Comparisons with a community inventory indicate that this algorithm captures the majority of pyroCb. The primary limitation of the current system is that pyroCb anvils can be small relative to satellite pixel size, especially in in regions with large viewing angles. The algorithm is also sensitive to some false positives from traditional convection that either ingests smoke or exhibits extreme updraft velocities. This algorithm has been automated using the GeoIPS processing system developed at NRL, which produces a variety of imagery products and statistical output for rapid analysis of potential pyroCb events. NRT application of this algorithm has been extended to the majority of regions worldwide known to have a high frequency of pyroCb occurrence. This involves a constellation comprised of GOES-East, GOES-West, and Himawari-8. Imagery is posted immediately to an NRL-maintained web page. Alerts are generated by the system and disseminated via email. This detection system also has potential to serve as a data source for other NRT environmental monitoring systems. While the current geostationary constellation has several important limitations, the next-generation of geostationary sensors will offer significant advantages for achieving the goal of global NRT pyroCb detection.

Validation of OMPS Ozone Profile Data with Expanded Dataset from Brewer and Automated Dobson Network.

NASA Astrophysics Data System (ADS)

Petropavlovskikh, I.; Weatherhead, E.; Cede, A.; Oltmans, S. J.; Kireev, S.; Maillard, E.; Bhartia, P. K.; Flynn, L. E.

2005-12-01

The first NPOESS satellite is scheduled to be launched in 2010 and will carry the Ozone Mapping and Profiler Suite (OMPS) instruments for ozone monitoring. Prior this, the OMPS instruments and algorithms will be tested by flight on the NPOESS/NPP satellite, scheduled for launch in 2008. Pre-launch planning for validation, post launch data validation and verification of the nadir and limb profile algorithm are key components for insuring that the NPOESS will produce a high quality, reliable ozone profile data set. The heritage of satellite instrument validation (TOMS, SBUV, GOME, SCIAMACHY, SAGE, HALOE, ATMOS, etc) has always relied upon surface-based observations. While the global coverage of satellite observations is appealing for validating another satellite, there is no substitute for the hard reference point of a ground-based system such as the Dobson or Brewer network, whose instruments are routinely calibrated and intercompared to standard references. The standard solar occultation instruments, SAGE II and HALOE are well beyond their planned lifetimes and might be inoperative during the OMPS period. The Umkehr network has been one of the key data sets for stratospheric ozone trend calculations and has earned its place as a benchmark network for stratospheric ozone profile observations. The normalization of measurements at different solar zenith angle (SZAs) to the measurement at the smallest SZA cancels out many calibration parameters, including the extra-terrestrial solar flux and instrumental constant, thus providing a "self-calibrating" technique in the same manner relied upon by the occultation sensors on satellites. Moreover, the ground-based Umkehr measurement is the only technique that provides data with the same altitude resolution and in the same units (DU) as do the UV-nadir instruments (SBUV-2, GOME-2, OMPS-nadir), i.e., as ozone amount in pressure layers, whereas, occultation instruments measure ozone density with height. A new Umkehr algorithm will enhance the information content of the retrieved profiles and extend the applicability of the technique. Automated Dobson and Brewer instruments offer the potential for greatly expanded network of Umkehr observations once the new algorithm is applied. We will discuss the new algorithm development and present results of its performance in comparisons of retrievals between co-located Brewer and Dobson ozone profiles measured at Arosa station in Switzerland.

An Autonomous Navigation Algorithm for High Orbit Satellite Using Star Sensor and Ultraviolet Earth Sensor

PubMed Central

Baohua, Li; Wenjie, Lai; Yun, Chen; Zongming, Liu

2013-01-01

An autonomous navigation algorithm using the sensor that integrated the star sensor (FOV1) and ultraviolet earth sensor (FOV2) is presented. The star images are sampled by FOV1, and the ultraviolet earth images are sampled by the FOV2. The star identification algorithm and star tracking algorithm are executed at FOV1. Then, the optical axis direction of FOV1 at J2000.0 coordinate system is calculated. The ultraviolet image of earth is sampled by FOV2. The center vector of earth at FOV2 coordinate system is calculated with the coordinates of ultraviolet earth. The autonomous navigation data of satellite are calculated by integrated sensor with the optical axis direction of FOV1 and the center vector of earth from FOV2. The position accuracy of the autonomous navigation for satellite is improved from 1000 meters to 300 meters. And the velocity accuracy of the autonomous navigation for satellite is improved from 100 m/s to 20 m/s. At the same time, the period sine errors of the autonomous navigation for satellite are eliminated. The autonomous navigation for satellite with a sensor that integrated ultraviolet earth sensor and star sensor is well robust. PMID:24250261

An autonomous navigation algorithm for high orbit satellite using star sensor and ultraviolet earth sensor.

PubMed

Baohua, Li; Wenjie, Lai; Yun, Chen; Zongming, Liu

2013-01-01

An autonomous navigation algorithm using the sensor that integrated the star sensor (FOV1) and ultraviolet earth sensor (FOV2) is presented. The star images are sampled by FOV1, and the ultraviolet earth images are sampled by the FOV2. The star identification algorithm and star tracking algorithm are executed at FOV1. Then, the optical axis direction of FOV1 at J2000.0 coordinate system is calculated. The ultraviolet image of earth is sampled by FOV2. The center vector of earth at FOV2 coordinate system is calculated with the coordinates of ultraviolet earth. The autonomous navigation data of satellite are calculated by integrated sensor with the optical axis direction of FOV1 and the center vector of earth from FOV2. The position accuracy of the autonomous navigation for satellite is improved from 1000 meters to 300 meters. And the velocity accuracy of the autonomous navigation for satellite is improved from 100 m/s to 20 m/s. At the same time, the period sine errors of the autonomous navigation for satellite are eliminated. The autonomous navigation for satellite with a sensor that integrated ultraviolet earth sensor and star sensor is well robust.

Challenges and Solutions for GNSS Receivers onboard LEO Satellites Traveling through the Ionosphere during Space Weather Events

NASA Astrophysics Data System (ADS)

Morton, Y.; Xu, D.; Yang, R.; Jiao, Y.; Rino, C.; Carrano, C. S.

2017-12-01

This presentation discusses challenges imposed on GNSS receiver carrier-tracking loop for receivers onboard LEO satellites traveling through ionosphere during space weather events and techniques that mitigate the effects. Recent studies show that the ESA's swarm satellites experienced a total loss of GPS signals in areas known for frequent occurrence of ionosphere plasma irregularities. The same phenomena have been observed in other satellite missions. More robust GNSS receiver technologies are needed to improve the navigation capabilities for future LEO satellite missions. A major challenge to characterize GNSS signals traversing ionospheric plasma structures to reach a LEO satellite is the lack of data. To overcome this challenge, we utilized a physics-based GNSS scintillation signal simulator to generate simulated data for analysis and algorithm development. The simulator relies on real scintillation data collected by ground-based receivers as the initializer to generate a realization of ionosphere irregularity structure statistical distribution. A user specifies desired satellite orbit, signal modulation scheme, receiver platform dynamics, and receiver front-end hardware design. These inputs are used to establish the signal propagation geometry to allow interception of the disturbed signal by a realistic GNSS receiver. The simulator results showed that plasma structures lead to strong disturbances on GNSS signals reaching a LEO platform. The disturbances are characterized by simultaneous deep amplitude fades and extremely rapid carrier phase fluctuations. The carrier phase rate is orders of magnitude higher than the ones experienced by receivers on the ground. Such high carrier dynamics far exceeds the range that can be tolerated by the bandwidth of a typical GNSS receiver. The deep amplitude fades further exacerbate the problem. Based on the simulator outputs, we established models of the disturbed signal parameters. These models are used in an adaptive carrier-tracking algorithm that demonstrated improved performances when applied to various simulated scenarios of plasma structures and receiver trajectories. The presentation will discuss the simulator, disturbed signal characterization, and the adaptive algorithm architecture and performances.

Assessment of a Bidirectional Reflectance Distribution Correction of Above-Water and Satellite Water-Leaving Radiance in Coastal Waters

NASA Technical Reports Server (NTRS)

Hlaing, Soe; Gilerson, Alexander; Harmal, Tristan; Tonizzo, Alberto; Weidemann, Alan; Arnone, Robert; Ahmed, Samir

2012-01-01

Water-leaving radiances, retrieved from in situ or satellite measurements, need to be corrected for the bidirectional properties of the measured light in order to standardize the data and make them comparable with each other. The current operational algorithm for the correction of bidirectional effects from the satellite ocean color data is optimized for typical oceanic waters. However, versions of bidirectional reflectance correction algorithms specifically tuned for typical coastal waters and other case 2 conditions are particularly needed to improve the overall quality of those data. In order to analyze the bidirectional reflectance distribution function (BRDF) of case 2 waters, a dataset of typical remote sensing reflectances was generated through radiative transfer simulations for a large range of viewing and illumination geometries. Based on this simulated dataset, a case 2 water focused remote sensing reflectance model is proposed to correct above-water and satellite water-leaving radiance data for bidirectional effects. The proposed model is first validated with a one year time series of in situ above-water measurements acquired by collocated multispectral and hyperspectral radiometers, which have different viewing geometries installed at the Long Island Sound Coastal Observatory (LISCO). Match-ups and intercomparisons performed on these concurrent measurements show that the proposed algorithm outperforms the algorithm currently in use at all wavelengths, with average improvement of 2.4% over the spectral range. LISCO's time series data have also been used to evaluate improvements in match-up comparisons of Moderate Resolution Imaging Spectroradiometer satellite data when the proposed BRDF correction is used in lieu of the current algorithm. It is shown that the discrepancies between coincident in-situ sea-based and satellite data decreased by 3.15% with the use of the proposed algorithm.

Evolvable Hardware for Space Applications

NASA Technical Reports Server (NTRS)

Lohn, Jason; Globus, Al; Hornby, Gregory; Larchev, Gregory; Kraus, William

2004-01-01

This article surveys the research of the Evolvable Systems Group at NASA Ames Research Center. Over the past few years, our group has developed the ability to use evolutionary algorithms in a variety of NASA applications ranging from spacecraft antenna design, fault tolerance for programmable logic chips, atomic force field parameter fitting, analog circuit design, and earth observing satellite scheduling. In some of these applications, evolutionary algorithms match or improve on human performance.

The ESA Cloud CCI project: Generation of Multi Sensor consistent Cloud Properties with an Optimal Estimation Based Retrieval Algorithm

NASA Astrophysics Data System (ADS)

Jerg, M.; Stengel, M.; Hollmann, R.; Poulsen, C.

2012-04-01

The ultimate objective of the ESA Climate Change Initiative (CCI) Cloud project is to provide long-term coherent cloud property data sets exploiting and improving on the synergetic capabilities of past, existing, and upcoming European and American satellite missions. The synergetic approach allows not only for improved accuracy and extended temporal and spatial sampling of retrieved cloud properties better than those provided by single instruments alone but potentially also for improved (inter-)calibration and enhanced homogeneity and stability of the derived time series. Such advances are required by the scientific community to facilitate further progress in satellite-based climate monitoring, which leads to a better understanding of climate. Some of the primary objectives of ESA Cloud CCI Cloud are (1) the development of inter-calibrated radiance data sets, so called Fundamental Climate Data Records - for ESA and non ESA instruments through an international collaboration, (2) the development of an optimal estimation based retrieval framework for cloud related essential climate variables like cloud cover, cloud top height and temperature, liquid and ice water path, and (3) the development of two multi-annual global data sets for the mentioned cloud properties including uncertainty estimates. These two data sets are characterized by different combinations of satellite systems: the AVHRR heritage product comprising (A)ATSR, AVHRR and MODIS and the novel (A)ATSR - MERIS product which is based on a synergetic retrieval using both instruments. Both datasets cover the years 2007-2009 in the first project phase. ESA Cloud CCI will also carry out a comprehensive validation of the cloud property products and provide a common data base as in the framework of the Global Energy and Water Cycle Experiment (GEWEX). The presentation will give an overview of the ESA Cloud CCI project and its goals and approaches and then continue with results from the Round Robin algorithm comparison exercise carried out at the beginning of the project which included three algorithms. The purpose of the exercise was to assess and compare existing cloud retrieval algorithms in order to chose one of them as backbone of the retrieval system and also identify areas of potential improvement and general strengths and weaknesses of the algorithm. Furthermore the presentation will elaborate on the optimal estimation algorithm subsequently chosen to derive the heritage product and which is presently further developed and will be employed for the AVHRR heritage product. The algorithm's capabilities to coherently and simultaneously process all radiative input and yield retrieval parameters together with associated uncertainty estimates will be presented together with first results for the heritage product. In the course of the project the algorithm is being developed into a freely and publicly available community retrieval system for interested scientists.

Operational evapotranspiration based on Earth observation satellites

NASA Astrophysics Data System (ADS)

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 parallel, research has been started to investigate ET downscaling to a finer spatial scale. A first step is focusing on the assimilation into the algorithm of vegetation products derived from polar satellites. MODIS and SPOT-VEG products have been investigated to prepare the exploitation of the new Proba-V derived vegetation products that should become part the Copernicus Land Monitoring Service portfolio. Furthermore, an ongoing specific project is dedicated to the study of ET in wetlands allowing to concentrate research on relationship between ET, vegetation characteristics and ecosystem health. In the future, the launch of the Meteosat Third Generation satellite will motivate new developments in the framework of LSA-SAF. The present contribution will give an overview of above mentioned operational products and related ongoing research activities. LSA-SAF research at RMI is co-funded by EUMETSAT and Belgian Federal Science Policy/ESA through their Prodex funding program (contract C4000110695). Exploratory research on multi-mission EO exploitation has been allowed thanks to grants of Belgian Federal Science Policy (CB/34/18, SR/34/163, SR/00/301).

Minding the gaps: new insights into R&D management and operational transitions of NOAA satellite products

NASA Astrophysics Data System (ADS)

Colton, Marie C.; Powell, Alfred M.; Jordan, Gretchen; Mote, Jonathon; Hage, Jerald; Frank, Donald

2004-10-01

The NESDIS Center for Satellite Applications and Research (STAR), formerly ORA, Office of Research and Applications, consists of three research and applications divisions that encompass satellite meteorology, oceanography, climatology, and cooperative research with academic institutions. With such a wide background of talent, and a charter to develop operational algorithms and applications, STAR scientists develop satellite-derived land, ice, ocean, and atmospheric environmental data products in support of all of NOAA"s mission goals. In addition, in close association with the Joint Center for Satellite Data Assimilation, STAR scientists actively work with the numerical modeling communities of NOAA, NASA, and DOD to support the development of new methods for assimilation of satellite data. In this new era of observations from many new satellite instruments, STAR aims to effectively integrate these data into multi-platform data products for utilization by the forecast and applications communities. Much of our work is conducted in close partnerships with other agencies, academic institutes, and industry. In order to support the nearly 400 current satellite-derived products for various users on a routine basis from our sister operations office, and to evolve to future systems requires an ongoing strategic planning approach that maps research and development activities from NOAA goals to user requirements. Since R&D accomplishments are not necessarily amenable to precise schedules, appropriate motivators and measures of scientific progress must be developed to assure that the product development cycle remains aligned with the other engineering segments of a satellite program. This article presents the status and results of this comprehensive effort to chart a course from the present set of operational satellites to the future.

Fast emission estimates in China and South Africa constrained by satellite observations

NASA Astrophysics Data System (ADS)

Mijling, Bas; van der A, Ronald

2013-04-01

Emission inventories of air pollutants are crucial information for policy makers and form important input data for air quality models. Unfortunately, bottom-up emission inventories, compiled from large quantities of statistical data, are easily outdated for emerging economies such as China and South Africa, where rapid economic growth change emissions accordingly. Alternatively, top-down emission estimates from satellite observations of air constituents have important advantages of being spatial consistent, having high temporal resolution, and enabling emission updates shortly after the satellite data become available. However, constraining emissions from observations of concentrations is computationally challenging. Within the GlobEmission project (part of the Data User Element programme of ESA) a new algorithm has been developed, specifically designed for fast daily emission estimates of short-lived atmospheric species on a mesoscopic scale (0.25 × 0.25 degree) from satellite observations of column concentrations. The algorithm needs only one forward model run from a chemical transport model to calculate the sensitivity of concentration to emission, using trajectory analysis to account for transport away from the source. By using a Kalman filter in the inverse step, optimal use of the a priori knowledge and the newly observed data is made. We apply the algorithm for NOx emission estimates in East China and South Africa, using the CHIMERE chemical transport model together with tropospheric NO2 column retrievals of the OMI and GOME-2 satellite instruments. The observations are used to construct a monthly emission time series, which reveal important emission trends such as the emission reduction measures during the Beijing Olympic Games, and the impact and recovery from the global economic crisis. The algorithm is also able to detect emerging sources (e.g. new power plants) and improve emission information for areas where proxy data are not or badly known (e.g. shipping emissions). The new emission inventories result in a better agreement between observations and simulations of air pollutant concentrations, facilitating improved air quality forecasts.

Mapping Impervious Surface Expansion using Medium-resolution Satellite Image Time Series: A Case Study in the Yangtze River Delta, China

NASA Technical Reports Server (NTRS)

Gao, Feng; DeColstoun, Eric Brown; Ma, Ronghua; Weng, Qihao; Masek, Jeffrey G.; Chen, Jin; Pan, Yaozhong; Song, Conghe

2012-01-01

Cities have been expanding rapidly worldwide, especially over the past few decades. Mapping the dynamic expansion of impervious surface in both space and time is essential for an improved understanding of the urbanization process, land-cover and land-use change, and their impacts on the environment. Landsat and other medium-resolution satellites provide the necessary spatial details and temporal frequency for mapping impervious surface expansion over the past four decades. Since the US Geological Survey opened the historical record of the Landsat image archive for free access in 2008, the decades-old bottleneck of data limitation has gone. Remote-sensing scientists are now rich with data, and the challenge is how to make best use of this precious resource. In this article, we develop an efficient algorithm to map the continuous expansion of impervious surface using a time series of four decades of medium-resolution satellite images. The algorithm is based on a supervised classification of the time-series image stack using a decision tree. Each imerpervious class represents urbanization starting in a different image. The algorithm also allows us to remove inconsistent training samples because impervious expansion is not reversible during the study period. The objective is to extract a time series of complete and consistent impervious surface maps from a corresponding times series of images collected from multiple sensors, and with a minimal amount of image preprocessing effort. The approach was tested in the lower Yangtze River Delta region, one of the fastest urban growth areas in China. Results from nearly four decades of medium-resolution satellite data from the Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper plus (ETM+) and China-Brazil Earth Resources Satellite (CBERS) show a consistent urbanization process that is consistent with economic development plans and policies. The time-series impervious spatial extent maps derived from this study agree well with an existing urban extent polygon data set that was previously developed independently. The overall mapping accuracy was estimated at about 92.5% with 3% commission error and 12% omission error for the impervious type from all images regardless of image quality and initial spatial resolution.

Comparison of atmospheric correction algorithms for the Coastal Zone Color Scanner

NASA Technical Reports Server (NTRS)

Tanis, F. J.; Jain, S. C.

1984-01-01

Before Nimbus-7 Costal Zone Color Scanner (CZC) data can be used to distinguish between coastal water types, methods must be developed for the removal of spatial variations in aerosol path radiance. These can dominate radiance measurements made by the satellite. An assessment is presently made of the ability of four different algorithms to quantitatively remove haze effects; each was adapted for the extraction of the required scene-dependent parameters during an initial pass through the data set The CZCS correction algorithms considered are (1) the Gordon (1981, 1983) algorithm; (2) the Smith and Wilson (1981) iterative algorityhm; (3) the pseudooptical depth method; and (4) the residual component algorithm.

Assessment of a bidirectional reflectance distribution correction of above-water and satellite water-leaving radiance in coastal waters.

PubMed

Hlaing, Soe; Gilerson, Alexander; Harmel, Tristan; Tonizzo, Alberto; Weidemann, Alan; Arnone, Robert; Ahmed, Samir

2012-01-10

Water-leaving radiances, retrieved from in situ or satellite measurements, need to be corrected for the bidirectional properties of the measured light in order to standardize the data and make them comparable with each other. The current operational algorithm for the correction of bidirectional effects from the satellite ocean color data is optimized for typical oceanic waters. However, versions of bidirectional reflectance correction algorithms specifically tuned for typical coastal waters and other case 2 conditions are particularly needed to improve the overall quality of those data. In order to analyze the bidirectional reflectance distribution function (BRDF) of case 2 waters, a dataset of typical remote sensing reflectances was generated through radiative transfer simulations for a large range of viewing and illumination geometries. Based on this simulated dataset, a case 2 water focused remote sensing reflectance model is proposed to correct above-water and satellite water-leaving radiance data for bidirectional effects. The proposed model is first validated with a one year time series of in situ above-water measurements acquired by collocated multispectral and hyperspectral radiometers, which have different viewing geometries installed at the Long Island Sound Coastal Observatory (LISCO). Match-ups and intercomparisons performed on these concurrent measurements show that the proposed algorithm outperforms the algorithm currently in use at all wavelengths, with average improvement of 2.4% over the spectral range. LISCO's time series data have also been used to evaluate improvements in match-up comparisons of Moderate Resolution Imaging Spectroradiometer satellite data when the proposed BRDF correction is used in lieu of the current algorithm. It is shown that the discrepancies between coincident in-situ sea-based and satellite data decreased by 3.15% with the use of the proposed algorithm. This confirms the advantages of the proposed model over the current one, demonstrating the need for a specific case 2 water BRDF correction algorithm as well as the feasibility of enhancing performance of current and future satellite ocean color remote sensing missions for monitoring of typical coastal waters. © 2012 Optical Society of America

Pre-Launch Algorithms and Risk Reduction in Support of the Geostationary Lightning Mapper for GOES-R and Beyond

NASA Technical Reports Server (NTRS)

Goodman, Steven J.; Blakeslee, R. J.; Koshak, W.; Petersen, W.; Buechler, D. E.; Krehbiel, P. R.; Gatlin, P.; Zubrick, S.

2008-01-01

The Geostationary Lightning Mapper (GLM) is a single channel, near-IR imager/optical transient event detector, used to detect, locate and measure total lightning activity over the full-disk as part of a 3-axis stabilized, geostationary weather satellite system. The next generation NOAA Geostationary Operational Environmental Satellite (GOES-R) series with a planned launch in 2014 will carry a GLM that will provide continuous day and night observations of lightning from the west coast of Africa (GOES-E) to New Zealand (GOES-W) when the constellation is fUlly operational. The mission objectives for the GLM are to 1) provide continuous, full-disk lightning measurements for storm warning and nowcasting, 2) provide early warning of tornadic activity, and 3) accumulate a long-term database to track decadal changes of lightning. The GLM owes its heritage to the NASA Lightning Imaging Sensor (1997-Present) and the Optical Transient Detector (1995-2000), which were developed for the Earth Observing System and have produced a combined 13 year data record of global lightning activity. Instrument formulation studies were completed in March 2007 and the implementation phase to develop a prototype model and up to four flight models is expected to be underway in the latter part of 2007. In parallel with the instrument development, a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 ground processing algorithms and applications. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds (e.g., Lightning Mapping Arrays in North Alabama and the Washington DC Metropolitan area)

MODIS water quality algorithms for northwest Florida estuaries

EPA Science Inventory

Synoptic and frequent monitoring of water quality parameters from satellite is useful for determining the health of aquatic ecosystems and development of effective management strategies. Northwest Florida estuaries are classified as optically-complex, or waters influenced by chlo...

Research on Scheduling Algorithm for Multi-satellite and Point Target Task on Swinging Mode

NASA Astrophysics Data System (ADS)

Wang, M.; Dai, G.; Peng, L.; Song, Z.; Chen, G.

2012-12-01

Nowadays, using satellite in space to observe ground is an important and major method to obtain ground information. With the development of the scientific technology in the field of space, many fields such as military and economic and other areas have more and more requirement of space technology because of the benefits of the satellite's widespread, timeliness and unlimited of area and country. And at the same time, because of the wide use of all kinds of satellites, sensors, repeater satellites and ground receiving stations, ground control system are now facing great challenge. Therefore, how to make the best value of satellite resources so as to make full use of them becomes an important problem of ground control system. Satellite scheduling is to distribute the resource to all tasks without conflict to obtain the scheduling result so as to complete as many tasks as possible to meet user's requirement under considering the condition of the requirement of satellites, sensors and ground receiving stations. Considering the size of the task, we can divide tasks into point task and area task. This paper only considers point targets. In this paper, a description of satellite scheduling problem and a chief introduction of the theory of satellite scheduling are firstly made. We also analyze the restriction of resource and task in scheduling satellites. The input and output flow of scheduling process are also chiefly described in the paper. On the basis of these analyses, we put forward a scheduling model named as multi-variable optimization model for multi-satellite and point target task on swinging mode. In the multi-variable optimization model, the scheduling problem is transformed the parametric optimization problem. The parameter we wish to optimize is the swinging angle of every time-window. In the view of the efficiency and accuracy, some important problems relating the satellite scheduling such as the angle relation between satellites and ground targets, positive and negative swinging angle and the computation of time window are analyzed and discussed. And many strategies to improve the efficiency of this model are also put forward. In order to solve the model, we bring forward the conception of activity sequence map. By using the activity sequence map, the activity choice and the start time of the activity can be divided. We also bring forward three neighborhood operators to search the result space. The front movement remaining time and the back movement remaining time are used to analyze the feasibility to generate solution from neighborhood operators. Lastly, the algorithm to solve the problem and model is put forward based genetic algorithm. Population initialization, crossover operator, mutation operator, individual evaluation, collision decrease operator, select operator and collision elimination operator is designed in the paper. Finally, the scheduling result and the simulation for a practical example on 5 satellites and 100 point targets with swinging mode is given, and the scheduling performances are also analyzed while the swinging angle in 0, 5, 10, 15, 25. It can be shown by the result that the model and the algorithm are more effective than those ones without swinging mode.

Fast gradient-based algorithm on extended landscapes for wave-front reconstruction of Earth observation satellite

NASA Astrophysics Data System (ADS)

Thiebaut, C.; Perraud, L.; Delvit, J. M.; Latry, C.

2016-07-01

We present an on-board satellite implementation of a gradient-based (optical flows) algorithm for the shifts estimation between images of a Shack-Hartmann wave-front sensor on extended landscapes. The proposed algorithm has low complexity in comparison with classical correlation methods which is a big advantage for being used on-board a satellite at high instrument data rate and in real-time. The electronic board used for this implementation is designed for space applications and is composed of radiation-hardened software and hardware. Processing times of both shift estimations and pre-processing steps are compatible of on-board real-time computation.

Onboard autonomous mission re-planning for multi-satellite system

NASA Astrophysics Data System (ADS)

Zheng, Zixuan; Guo, Jian; Gill, Eberhard

2018-04-01

This paper presents an onboard autonomous mission re-planning system for Multi-Satellites System (MSS) to perform onboard re-planing in disruptive situations. The proposed re-planning system can deal with different potential emergency situations. This paper uses Multi-Objective Hybrid Dynamic Mutation Genetic Algorithm (MO-HDM GA) combined with re-planning techniques as the core algorithm. The Cyclically Re-planning Method (CRM) and the Near Real-time Re-planning Method (NRRM) are developed to meet different mission requirements. Simulations results show that both methods can provide feasible re-planning sequences under unforeseen situations. The comparisons illustrate that using the CRM is average 20% faster than the NRRM on computation time. However, by using the NRRM more raw data can be observed and transmitted than using the CRM within the same period. The usability of this onboard re-planning system is not limited to multi-satellite system. Other mission planning and re-planning problems related to autonomous multiple vehicles with similar demands are also applicable.

MTI science, data products, and ground-data processing overview

NASA Astrophysics Data System (ADS)

Szymanski, John J.; Atkins, William H.; Balick, Lee K.; Borel, Christoph C.; Clodius, William B.; Christensen, R. Wynn; Davis, Anthony B.; Echohawk, J. C.; Galbraith, Amy E.; Hirsch, Karen L.; Krone, James B.; Little, Cynthia K.; McLachlan, Peter M.; Morrison, Aaron; Pollock, Kimberly A.; Pope, Paul A.; Novak, Curtis; Ramsey, Keri A.; Riddle, Emily E.; Rohde, Charles A.; Roussel-Dupre, Diane C.; Smith, Barham W.; Smith, Kathy; Starkovich, Kim; Theiler, James P.; Weber, Paul G.

2001-08-01

The mission of the Multispectral Thermal Imager (MTI) satellite is to demonstrate the efficacy of highly accurate multispectral imaging for passive characterization of urban and industrial areas, as well as sites of environmental interest. The satellite makes top-of-atmosphere radiance measurements that are subsequently processed into estimates of surface properties such as vegetation health, temperatures, material composition and others. The MTI satellite also provides simultaneous data for atmospheric characterization at high spatial resolution. To utilize these data the MTI science program has several coordinated components, including modeling, comprehensive ground-truth measurements, image acquisition planning, data processing and data interpretation and analysis. Algorithms have been developed to retrieve a multitude of physical quantities and these algorithms are integrated in a processing pipeline architecture that emphasizes automation, flexibility and programmability. In addition, the MTI science team has produced detailed site, system and atmospheric models to aid in system design and data analysis. This paper provides an overview of the MTI research objectives, data products and ground data processing.

GOES-R Geostationary Lightning Mapper Performance Specifications and Algorithms

NASA Technical Reports Server (NTRS)

Mach, Douglas M.; Goodman, Steven J.; Blakeslee, Richard J.; Koshak, William J.; Petersen, William A.; Boldi, Robert A.; Carey, Lawrence D.; Bateman, Monte G.; Buchler, Dennis E.; McCaul, E. William, Jr.

2008-01-01

The Geostationary Lightning Mapper (GLM) is a single channel, near-IR imager/optical transient event detector, used to detect, locate and measure total lightning activity over the full-disk. The next generation NOAA Geostationary Operational Environmental Satellite (GOES-R) series will carry a GLM that will provide continuous day and night observations of lightning. The mission objectives for the GLM are to: (1) Provide continuous, full-disk lightning measurements for storm warning and nowcasting, (2) Provide early warning of tornadic activity, and (2) Accumulate a long-term database to track decadal changes of lightning. The GLM owes its heritage to the NASA Lightning Imaging Sensor (1997- present) and the Optical Transient Detector (1995-2000), which were developed for the Earth Observing System and have produced a combined 13 year data record of global lightning activity. GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms and applications. The science data will consist of lightning "events", "groups", and "flashes". The algorithm is being designed to be an efficient user of the computational resources. This may include parallelization of the code and the concept of sub-dividing the GLM FOV into regions to be processed in parallel. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds (e.g., Lightning Mapping Arrays in North Alabama, Oklahoma, Central Florida, and the Washington DC Metropolitan area) are being used to develop the prelaunch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution.

An automated processing chains for surface temperature monitoring on Earth's most active volcanoes by optical data from multiple satellites

NASA Astrophysics Data System (ADS)

Silvestri, Malvina; Musacchio, Massimo; Fabrizia Buongiorno, Maria

2017-04-01

The Geohazards Exploitation Platform, or GEP is one of six Thematic Exploitation Platforms developed by ESA to serve data user communities. As a new element of the ground segment delivering satellite results to users, these cloud-based platforms provide an online environment to access information, processing tools, computing resources for community collaboration. The aim is to enable the easy extraction of valuable knowledge from vast quantities of satellite-sensed data now being produced by Europe's Copernicus programme and other Earth observation satellites. In this context, the estimation of surface temperature on active volcanoes around the world is considered. E2E processing chains have been developed for different satellite data (ASTER, Landsat8 and Sentinel 3 missions) using thermal infrared (TIR) channels by applying specific algorithms. These chains have been implemented on the GEP platform enabling the use of EO missions and the generation of added value product such as surface temperature map, from not skilled users. This solution will enhance the use of satellite data and improve the dissemination of the results saving valuable time (no manual browsing, downloading or processing is needed) and producing time series data that can be speedily extracted from a single co-registered pixel, to highlight gradual trends within a narrow area. Moreover, thanks to the high-resolution optical imagery of Sentinel 2 (MSI), the detection of lava maps during an eruption can be automatically obtained. The proposed lava detection method is based on a contextual algorithm applied to Sentinel-2 NIR (band 8 - 0.8 micron) and SWIR (band 12 - 2.25 micron) data. Examples derived by last eruptions on active volcanoes are showed.

Aerosol Optical Properties over the Oceans: Summary and Interpretation of Shadow-Band Radiometer Data from Six Cruises. Chapter 19

NASA Technical Reports Server (NTRS)

Miller, Mark A.; Reynolds, R. M.; Bartholomew, Mary Jane

2001-01-01

The aerosol scattering component of the total radiance measured at the detectors of ocean color satellites is determined with atmospheric correction algorithms. These algorithms are based on aerosol optical thickness measurements made in two channels that lie in the near-infrared portion of the electromagnetic spectrum. The aerosol properties in the near-infrared region are used because there is no significant contribution to the satellite-measured radiance from the underlying ocean surface in that spectral region. In the visible wavelength bands, the spectrum of radiation scattered from the turbid atmosphere is convolved with the spectrum of radiation scattered from the surface layers of the ocean. The radiance contribution made by aerosols in the visible bands is determined from the near-infrared measurements through the use of aerosol models and radiation transfer codes. Selection of appropriate aerosol models from the near-infrared measurements is a fundamental challenge. There are several challenges with respect to the development, improvement, and evaluation of satellite ocean-color atmospheric correction algorithms. A common thread among these challenges is the lack of over-ocean aerosol data. Until recently, one of the most important limitations has been the lack of techniques and instruments to make aerosol measurements at sea. There has been steady progress in this area over the past five years, and there are several new and promising devices and techniques for data collection. The development of new instruments and the collection of more aerosol data from over the world's oceans have brought the realization that aerosol measurements that can be directly compared with aerosol measurements from ocean color satellite measurements are difficult to obtain. There are two problems that limit these types of comparisons: the cloudiness of the atmosphere over the world's oceans and the limitations of the techniques and instruments used to collect aerosol data from ships. To address the latter, we have developed a new type of shipboard sun photometer.

Regional thermal-inertia mapping from an experimental satellite ( Powder River basin, Wyoming).

USGS Publications Warehouse

Watson, K.

1982-01-01

A new experimental satellite has provided, for the first time, thermal data that should be useful in reconnaissance geologic exploration. Thermal inertia, a property of geologic materials, can be mapped from these data by applying an algorithm that has been developed using a new thermal model. A simple registration procedure was used on a pair of day and night images of the Powder River basin, Wyoming, to illustrate the method.-from Author

Development of Algorithms and Programs for the Ray Nonlinear Radiotomography of the Ionosphere and Radiotomography Using Middle and High-Orbital Satellites.

DTIC Science & Technology

1995-01-01

satellites is usefull, too. Such radiotomographic systems allow to search the structure of magnetosphere, protonosphere, etc, and to study the influence...of these mediums on navigation and connection systems in details. In connection with the experiments performed the questions arise concerning the...radiotomography is the ray refraction. Ignoration of refraction limits the resolving power of RT systems . Taking the refraction into account, it allows to

Advancing the capabilities of reservoir remote sensing by leveraging multi-source satellite data

NASA Astrophysics Data System (ADS)

Gao, H.; Zhang, S.; Zhao, G.; Li, Y.

2017-12-01

With a total global capacity of more than 6000 km3, reservoirs play a key role in the hydrological cycle and in water resources management. However, essential reservoir data (e.g., elevation, storage, and evaporation loss) are usually not shared at a large scale. While satellite remote sensing offers a unique opportunity for monitoring large reservoirs from space, the commonly used radar altimeters can only detect storage variations of about 15% of global lakes at a repeat period of 10 days or longer. To advance the capabilities of reservoir sensing, we developed a series of algorithms geared towards generating long term reservoir records at improved spatial coverage, and at improved temporal resolution. To this goal, observations are leveraged from multiple satellite sensors, which include radar/laser altimeters, imagers, and passive microwave radiometers. In South Asia, we demonstrate that reservoir storage can be estimated under all-weather conditions at a 4 day time step, with the total capacity of monitored reservoirs increased to 45%. Within the Continuous United States, a first Landsat based evaporation loss dataset was developed (containing 204 reservoirs) from 1984 to 2011. The evaporation trends of these reservoirs are identified and the causes are analyzed. All of these algorithms and products were validated with gauge observations. Future satellite missions, which will make significant contributions to monitoring global reservoirs, are also discussed.

Integrating multisensor satellite data merging and image reconstruction in support of machine learning for better water quality management.

PubMed

Chang, Ni-Bin; Bai, Kaixu; Chen, Chi-Farn

2017-10-01

Monitoring water quality changes in lakes, reservoirs, estuaries, and coastal waters is critical in response to the needs for sustainable development. This study develops a remote sensing-based multiscale modeling system by integrating multi-sensor satellite data merging and image reconstruction algorithms in support of feature extraction with machine learning leading to automate continuous water quality monitoring in environmentally sensitive regions. This new Earth observation platform, termed "cross-mission data merging and image reconstruction with machine learning" (CDMIM), is capable of merging multiple satellite imageries to provide daily water quality monitoring through a series of image processing, enhancement, reconstruction, and data mining/machine learning techniques. Two existing key algorithms, including Spectral Information Adaptation and Synthesis Scheme (SIASS) and SMart Information Reconstruction (SMIR), are highlighted to support feature extraction and content-based mapping. Whereas SIASS can support various data merging efforts to merge images collected from cross-mission satellite sensors, SMIR can overcome data gaps by reconstructing the information of value-missing pixels due to impacts such as cloud obstruction. Practical implementation of CDMIM was assessed by predicting the water quality over seasons in terms of the concentrations of nutrients and chlorophyll-a, as well as water clarity in Lake Nicaragua, providing synergistic efforts to better monitor the aquatic environment and offer insightful lake watershed management strategies. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Goes-R Geostationary Lightning Mapper (GLM): Algorithm and Instrument Status

NASA Technical Reports Server (NTRS)

Goodman, Steven J.; Blakeslee, Richard J.; Koshak, William J.; Mach, Douglas

2010-01-01

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. Superior spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved capability for the Advanced Baseline Imager (ABI). The Geostationary Lighting Mapper (GLM) will map total lightning activity (in-cloud and cloud-to-ground lighting flashes) continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency. In parallel with the instrument development (a prototype and 4 flight models), a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms, cal/val performance monitoring tools, and new applications. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. A joint field campaign with Brazilian researchers in 2010-2011 will produce concurrent observations from a VHF lightning mapping array, Meteosat multi-band imagery, Tropical Rainfall Measuring Mission (TRMM) Lightning Imaging Sensor (LIS) overpasses, and related ground and in-situ lightning and meteorological measurements in the vicinity of Sao Paulo. These data will provide a new comprehensive proxy data set for algorithm and application development.

Satellite image analysis using neural networks

NASA Technical Reports Server (NTRS)

Sheldon, Roger A.

1990-01-01

The tremendous backlog of unanalyzed satellite data necessitates the development of improved methods for data cataloging and analysis. Ford Aerospace has developed an image analysis system, SIANN (Satellite Image Analysis using Neural Networks) that integrates the technologies necessary to satisfy NASA's science data analysis requirements for the next generation of satellites. SIANN will enable scientists to train a neural network to recognize image data containing scenes of interest and then rapidly search data archives for all such images. The approach combines conventional image processing technology with recent advances in neural networks to provide improved classification capabilities. SIANN allows users to proceed through a four step process of image classification: filtering and enhancement, creation of neural network training data via application of feature extraction algorithms, configuring and training a neural network model, and classification of images by application of the trained neural network. A prototype experimentation testbed was completed and applied to climatological data.

Australian Soil Moisture Field Experiments in Support of Soil Moisture Satellite Observations

NASA Technical Reports Server (NTRS)

Kim, Edward; Walker, Jeff; Rudiger, Christopher; Panciera, Rocco

2010-01-01

Large-scale field campaigns provide the critical fink between our understanding retrieval algorithms developed at the point scale, and algorithms suitable for satellite applications at vastly larger pixel scales. Retrievals of land parameters must deal with the substantial sub-pixel heterogeneity that is present in most regions. This is particularly the case for soil moisture remote sensing, because of the long microwave wavelengths (L-band) that are optimal. Yet, airborne L-band imagers have generally been large, heavy, and required heavy-lift aircraft resources that are expensive and difficult to schedule. Indeed, US soil moisture campaigns, have been constrained by these factors, and European campaigns have used non-imagers due to instrument and aircraft size constraints. Despite these factors, these campaigns established that large-scale soil moisture remote sensing was possible, laying the groundwork for satellite missions. Starting in 2005, a series of airborne field campaigns have been conducted in Australia: to improve our understanding of soil moisture remote sensing at large scales over heterogeneous areas. These field data have been used to test and refine retrieval algorithms for soil moisture satellite missions, and most recently with the launch of the European Space Agency's Soil Moisture Ocean Salinity (SMOS) mission, to provide validation measurements over a multi-pixel area. The campaigns to date have included a preparatory campaign in 2005, two National Airborne Field Experiments (NAFE), (2005 and 2006), two campaigns to the Simpson Desert (2008 and 2009), and one Australian Airborne Cal/val Experiment for SMOS (AACES), just concluded in the austral spring of 2010. The primary airborne sensor for each campaign has been the Polarimetric L-band Microwave Radiometer (PLMR), a 6-beam pushbroom imager that is small enough to be compatible with light aircraft, greatly facilitating the execution of the series of campaigns, and a key to their success. An L-band imaging radar is being added to the complement to provide simultaneous active-passive L-band observations, for algorithm development activities in support of NASA's upcoming Soil Moisture Active Passive (.S"M) mission. This paper will describe the campaigns, their objectives, their datasets, and some of the unique advantages of working with small/light sensors and aircraft. We will also review the main scientific findings, including improvements to the SMOS retrieval algorithm enabled by NAFE observations and the evaluation of the Simpson Desert as a calibration target for L-band satellite missions. Plans for upcoming campaigns will also be discussed.

Filtering and Gridding Satellite Observations of Cloud Variables to Compare with Climate Model Output

NASA Astrophysics Data System (ADS)

Pitts, K.; Nasiri, S. L.; Smith, N.

2013-12-01

Global climate models have improved considerably over the years, yet clouds still represent a large factor of uncertainty for these models. Comparisons of model-simulated cloud variables with equivalent satellite cloud products are the best way to start diagnosing the differences between model output and observations. Gridded (level 3) cloud products from many different satellites and instruments are required for a full analysis, but these products are created by different science teams using different algorithms and filtering criteria to create similar, but not directly comparable, cloud products. This study makes use of a recently developed uniform space-time gridding algorithm to create a new set of gridded cloud products from each satellite instrument's level 2 data of interest which are each filtered using the same criteria, allowing for a more direct comparison between satellite products. The filtering is done via several variables such as cloud top pressure/height, thermodynamic phase, optical properties, satellite viewing angle, and sun zenith angle. The filtering criteria are determined based on the variable being analyzed and the science question at hand. Each comparison of different variables may require different filtering strategies as no single approach is appropriate for all problems. Beyond inter-satellite data comparison, these new sets of uniformly gridded satellite products can also be used for comparison with model-simulated cloud variables. Of particular interest to this study are the differences in the vertical distributions of ice and liquid water content between the satellite retrievals and model simulations, especially in the mid-troposphere where there are mixed-phase clouds to consider. This presentation will demonstrate the proof of concept through comparisons of cloud water path from Aqua MODIS retrievals and NASA GISS-E2-[R/H] model simulations archived in the CMIP5 data portal.

JPSS Science Data Services for the Direct Readout Community

NASA Technical Reports Server (NTRS)

Chander, Gyanesh; Lutz, Bob

2014-01-01

The Suomi National Polar-orbiting Partnership (S-NPP) and Joint Polar Satellite System (JPSS) High Rate Data (HRD) link provides Direct Broadcast data to users in real-time, utilizing their own remote field terminals. The Field Terminal Support (FTS) provides the resources needed to support the Direct Readout communities by providing software, documentation, and periodic updates to enable them to produce data products from SNPP and JPSS. The FTS distribution server will also provide the necessary ancillary and auxiliary data needed for processing the broadcasts, as well as making orbital data available to assist in locating the satellites of interest. In addition, the FTS provides development support for the algorithm and software through GSFC Direct Readout Laboratory (DRL) International Polar Orbiter Processing Package (IPOPP) and University of Wisconsin (UWISC) Community Satellite Processing Package (CSPP), to enable users to integrate the algorithms into their remote terminals. The support the JPSS Program provides to the institutions developing and maintaining these two software packages, will demonstrate the ability to produce ready-to-use products from the HRD link and provide risk reduction effort at a minimal cost. This paper discusses the key functions and system architecture of FTS.

Asian dust aerosol: Optical effect on satellite ocean color signal and a scheme of its correction

NASA Astrophysics Data System (ADS)

Fukushima, H.; Toratani, M.

1997-07-01

The paper first exhibits the influence of the Asian dust aerosol (KOSA) on a coastal zone color scanner (CZCS) image which records erroneously low or negative satellite-derived water-leaving radiance especially in a shorter wavelength region. This suggests the presence of spectrally dependent absorption which was disregarded in the past atmospheric correction algorithms. On the basis of the analysis of the scene, a semiempirical optical model of the Asian dust aerosol that relates aerosol single scattering albedo (ωA) to the spectral ratio of aerosol optical thickness between 550 nm and 670 nm is developed. Then, as a modification to a standard CZCS atmospheric correction algorithm (NASA standard algorithm), a scheme which estimates pixel-wise aerosol optical thickness, and in turn ωA, is proposed. The assumption of constant normalized water-leaving radiance at 550 nm is adopted together with a model of aerosol scattering phase function. The scheme is combined to the standard algorithm, performing atmospheric correction just the same as the standard version with a fixed Angstrom coefficient except in the case where the presence of Asian dust aerosol is detected by the lowered satellite-derived Angstrom exponent. Some of the model parameter values are determined so that the scheme does not produce any spatial discontinuity with the standard scheme. The algorithm was tested against the Japanese Asian dust CZCS scene with parameter values of the spectral dependency of ωA, first statistically determined and second optimized for selected pixels. Analysis suggests that the parameter values depend on the assumed Angstrom coefficient for standard algorithm, at the same time defining the spatial extent of the area to apply the Asian dust scheme. The algorithm was also tested for a Saharan dust scene, showing the relevance of the scheme but with different parameter setting. Finally, the algorithm was applied to a data set of 25 CZCS scenes to produce a monthly composite of pigment concentration for April 1981. Through these analyses, the modified algorithm is considered robust in the sense that it operates most compatibly with the standard algorithm yet performs adaptively in response to the magnitude of the dust effect.

Theoretical and Observational Determination of Global and Regional Radiation Budget, Forcing and Feedbacks at the Top-of-Atmosphere and Surface

NASA Technical Reports Server (NTRS)

Loeb, Norman G.

2004-01-01

Report consists of: 1. List of accomplishments 2. List of publications 3. Abstracts of published or submitted papers and 4. Subject invention disclosure. The accomplishments of the grant listed are: 1. Improved the third-order turbulence closure in cloud resolving models to remove the liquid water oscillation. 2. Used the University of California-Los Angeles (UCLA) large-eddy simulation (LES) model to provide data for radiation transfer testing. 3. Revised shortwave k-distribution models based on HITRAN 2000. 4. Developed a gamma-weighted two-stream radiative transfer model for radiation budget estimate applications. 5. Estimated the effect of spherical geometry to the earth radiation budget. 6. Estimated top-of-atmosphere irradiance over snow and sea ice surfaces. 7. Estimated the aerosol direct radiative effect at the top of the atmosphere. 8. Estimated the top-of-atmosphere reflectance of the clear-sky molecular atmosphere over ocean. 9. Developed and validated new set of Angular Distribution Models for the CERES TRMM satellite instrument (tropical) 10. Developed and validated new set of Angular Distribution Models for the CERES Terra satellite instrument (global) 11. Quantified the top-of-atmosphere direct radiative effect of aerosols over global oceans from merged CERES and MODIS observations 12 Clarified the definition of TOA flux reference level for radiation budget studies 13. Developed new algorithm for unfaltering CERES measured radiances 14. Used multiangle POLDER measurements to produce narrowband angular distribution models and examine the effect of scene identification errors on TOA albedo estimates 15. Developed and validated a novel algorithm called the Multidirectional Reflectance Matching (MRM) model for inferring TOA albedos from ice clouds using multi-angle satellite measurements. 16. Developed and validated a novel algorithm called the Multidirectional Polarized Reflectance Matching (MPRM) model for inferring particle shapes from ice clouds using multi-angle polarized satellite measurements. 17. Developed 4 advanced light scattering models including the three-dimensional (3D) uniaxial perfectly matched layer (UPML) finite-difference time-domain (FDTD) model. 18. Develop sunglint in situ measurement and study reflectance distribution in the sunglint area. 19. Lead a balloon-borne radiometer TOA albedo validation effort. 20. Developed a CERES surface UVB, UVA, and UV index product.

An Automated Method for Navigation Assessment for Earth Survey Sensors Using Island Targets

NASA Technical Reports Server (NTRS)

Patt, F. S.; Woodward, R. H.; Gregg, W. W.

1997-01-01

An automated method has been developed for performing navigation assessment on satellite-based Earth sensor data. The method utilizes islands as targets which can be readily located in the sensor data and identified with reference locations. The essential elements are an algorithm for classifying the sensor data according to source, a reference catalogue of island locations, and a robust pattern-matching algorithm for island identification. The algorithms were developed and tested for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), an ocean colour sensor. This method will allow navigation error statistics to be automatically generated for large numbers of points, supporting analysis over large spatial and temporal ranges.

Automated navigation assessment for earth survey sensors using island targets

NASA Technical Reports Server (NTRS)

Patt, Frederick S.; Woodward, Robert H.; Gregg, Watson W.

1997-01-01

An automated method has been developed for performing navigation assessment on satellite-based Earth sensor data. The method utilizes islands as targets which can be readily located in the sensor data and identified with reference locations. The essential elements are an algorithm for classifying the sensor data according to source, a reference catalog of island locations, and a robust pattern-matching algorithm for island identification. The algorithms were developed and tested for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), an ocean color sensor. This method will allow navigation error statistics to be automatically generated for large numbers of points, supporting analysis over large spatial and temporal ranges.

A Novel Strategy Using Factor Graphs and the Sum-Product Algorithm for Satellite Broadcast Scheduling Problems

NASA Astrophysics Data System (ADS)

Chen, Jung-Chieh

This paper presents a low complexity algorithmic framework for finding a broadcasting schedule in a low-altitude satellite system, i. e., the satellite broadcast scheduling (SBS) problem, based on the recent modeling and computational methodology of factor graphs. Inspired by the huge success of the low density parity check (LDPC) codes in the field of error control coding, in this paper, we transform the SBS problem into an LDPC-like problem through a factor graph instead of using the conventional neural network approaches to solve the SBS problem. Based on a factor graph framework, the soft-information, describing the probability that each satellite will broadcast information to a terminal at a specific time slot, is exchanged among the local processing in the proposed framework via the sum-product algorithm to iteratively optimize the satellite broadcasting schedule. Numerical results show that the proposed approach not only can obtain optimal solution but also enjoys the low complexity suitable for integral-circuit implementation.

Reinforcement learning for resource allocation in LEO satellite networks.

PubMed

Usaha, Wipawee; Barria, Javier A

2007-06-01

In this paper, we develop and assess online decision-making algorithms for call admission and routing for low Earth orbit (LEO) satellite networks. It has been shown in a recent paper that, in a LEO satellite system, a semi-Markov decision process formulation of the call admission and routing problem can achieve better performance in terms of an average revenue function than existing routing methods. However, the conventional dynamic programming (DP) numerical solution becomes prohibited as the problem size increases. In this paper, two solution methods based on reinforcement learning (RL) are proposed in order to circumvent the computational burden of DP. The first method is based on an actor-critic method with temporal-difference (TD) learning. The second method is based on a critic-only method, called optimistic TD learning. The algorithms enhance performance in terms of requirements in storage, computational complexity and computational time, and in terms of an overall long-term average revenue function that penalizes blocked calls. Numerical studies are carried out, and the results obtained show that the RL framework can achieve up to 56% higher average revenue over existing routing methods used in LEO satellite networks with reasonable storage and computational requirements.

Advances in Landslide Nowcasting: Evaluation of a Global and Regional Modeling Approach

NASA Technical Reports Server (NTRS)

Kirschbaum, Dalia Bach; Peters-Lidard, Christa; Adler, Robert; Hong, Yang; Kumar, Sujay; Lerner-Lam, Arthur

2011-01-01

The increasing availability of remotely sensed data offers a new opportunity to address landslide hazard assessment at larger spatial scales. A prototype global satellite-based landslide hazard algorithm has been developed to identify areas that may experience landslide activity. This system combines a calculation of static landslide susceptibility with satellite-derived rainfall estimates and uses a threshold approach to generate a set of nowcasts that classify potentially hazardous areas. A recent evaluation of this algorithm framework found that while this tool represents an important first step in larger-scale near real-time landslide hazard assessment efforts, it requires several modifications before it can be fully realized as an operational tool. This study draws upon a prior work s recommendations to develop a new approach for considering landslide susceptibility and hazard at the regional scale. This case study calculates a regional susceptibility map using remotely sensed and in situ information and a database of landslides triggered by Hurricane Mitch in 1998 over four countries in Central America. The susceptibility map is evaluated with a regional rainfall intensity duration triggering threshold and results are compared with the global algorithm framework for the same event. Evaluation of this regional system suggests that this empirically based approach provides one plausible way to approach some of the data and resolution issues identified in the global assessment. The presented methodology is straightforward to implement, improves upon the global approach, and allows for results to be transferable between regions. The results also highlight several remaining challenges, including the empirical nature of the algorithm framework and adequate information for algorithm validation. Conclusions suggest that integrating additional triggering factors such as soil moisture may help to improve algorithm performance accuracy. The regional algorithm scenario represents an important step forward in advancing regional and global-scale landslide hazard assessment.

Building high-performance system for processing a daily large volume of Chinese satellites imagery

NASA Astrophysics Data System (ADS)

Deng, Huawu; Huang, Shicun; Wang, Qi; Pan, Zhiqiang; Xin, Yubin

2014-10-01

The number of Earth observation satellites from China increases dramatically recently and those satellites are acquiring a large volume of imagery daily. As the main portal of image processing and distribution from those Chinese satellites, the China Centre for Resources Satellite Data and Application (CRESDA) has been working with PCI Geomatics during the last three years to solve two issues in this regard: processing the large volume of data (about 1,500 scenes or 1 TB per day) in a timely manner and generating geometrically accurate orthorectified products. After three-year research and development, a high performance system has been built and successfully delivered. The high performance system has a service oriented architecture and can be deployed to a cluster of computers that may be configured with high end computing power. The high performance is gained through, first, making image processing algorithms into parallel computing by using high performance graphic processing unit (GPU) cards and multiple cores from multiple CPUs, and, second, distributing processing tasks to a cluster of computing nodes. While achieving up to thirty (and even more) times faster in performance compared with the traditional practice, a particular methodology was developed to improve the geometric accuracy of images acquired from Chinese satellites (including HJ-1 A/B, ZY-1-02C, ZY-3, GF-1, etc.). The methodology consists of fully automatic collection of dense ground control points (GCP) from various resources and then application of those points to improve the photogrammetric model of the images. The delivered system is up running at CRESDA for pre-operational production and has been and is generating good return on investment by eliminating a great amount of manual labor and increasing more than ten times of data throughput daily with fewer operators. Future work, such as development of more performance-optimized algorithms, robust image matching methods and application workflows, is identified to improve the system in the coming years.

Heading Toward Launch with the Integrated Multi-Satellite Retrievals for GPM (IMERG)

NASA Technical Reports Server (NTRS)

Huffman, George J.; Bolvin, David T.; Nelkin, Eric J.; Adler, Robert F.

2012-01-01

The Day-l algorithm for computing combined precipitation estimates in GPM is the Integrated Multi-satellitE Retrievals for GPM (IMERG). We plan for the period of record to encompass both the TRMM and GPM eras, and the coverage to extend to fully global as experience is gained in the difficult high-latitude environment. IMERG is being developed as a unified U.S. algorithm that takes advantage of strengths in the three groups that are contributing expertise: 1) the TRMM Multi-satellite Precipitation Analysis (TMPA), which addresses inter-satellite calibration of precipitation estimates and monthly scale combination of satellite and gauge analyses; 2) the CPC Morphing algorithm with Kalman Filtering (KF-CMORPH), which provides quality-weighted time interpolation of precipitation patterns following cloud motion; and 3) the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS), which provides a neural-network-based scheme for generating microwave-calibrated precipitation estimates from geosynchronous infrared brightness temperatures. In this talk we summarize the major building blocks and important design issues driven by user needs and practical data issues. One concept being pioneered by the IMERG team is that the code system should produce estimates for the same time period but at different latencies to support the requirements of different groups of users. Another user requirement is that all these runs must be reprocessed as new IMERG versions are introduced. IMERG's status at meeting time will be summarized, and the processing scenario in the transition from TRMM to GPM will be laid out. Initially, IMERG will be run with TRMM-based calibration, and then a conversion to a GPM-based calibration will be employed after the GPM sensor products are validated. A complete reprocessing will be computed, which will complete the transition from TMPA.

Improving Satellite Quantitative Precipitation Estimation Using GOES-Retrieved Cloud Optical Depth

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stenz, Ronald; Dong, Xiquan; Xi, Baike

To address significant gaps in ground-based radar coverage and rain gauge networks in the U.S., geostationary satellite quantitative precipitation estimates (QPEs) such as the Self-Calibrating Multivariate Precipitation Retrievals (SCaMPR) can be used to fill in both the spatial and temporal gaps of ground-based measurements. Additionally, with the launch of GOES-R, the temporal resolution of satellite QPEs may be comparable to that of Weather Service Radar-1988 Doppler (WSR-88D) volume scans as GOES images will be available every five minutes. However, while satellite QPEs have strengths in spatial coverage and temporal resolution, they face limitations particularly during convective events. Deep Convective Systemsmore » (DCSs) have large cloud shields with similar brightness temperatures (BTs) over nearly the entire system, but widely varying precipitation rates beneath these clouds. Geostationary satellite QPEs relying on the indirect relationship between BTs and precipitation rates often suffer from large errors because anvil regions (little/no precipitation) cannot be distinguished from rain-cores (heavy precipitation) using only BTs. However, a combination of BTs and optical depth (τ) has been found to reduce overestimates of precipitation in anvil regions (Stenz et al. 2014). A new rain mask algorithm incorporating both τ and BTs has been developed, and its application to the existing SCaMPR algorithm was evaluated. The performance of the modified SCaMPR was evaluated using traditional skill scores and a more detailed analysis of performance in individual DCS components by utilizing the Feng et al. (2012) classification algorithm. SCaMPR estimates with the new rain mask applied benefited from significantly reduced overestimates of precipitation in anvil regions and overall improvements in skill scores.« less

OMPS Sensor Performance and Algorithm Description

NASA Astrophysics Data System (ADS)

Branham, M. S.; Farrow, S. V.; Novicki, M.; Bhaswar, S.; Baker, B.

2009-12-01

The Ozone Mapping and Profiler Suite (OMPS), built by Ball Aerospace, is the next-generation U.S. ozone monitoring sensor suite, designed and built for the National Polar-orbiting Operational Environmental Satellite System (NPOESS), under contract to the Integrated Program Office, administered by the Air Force, National Oceanic and Atmospheric Administration (NOAA), and National Aeronautics and Space Administration (NASA) under contract to Northrop Grumman. The first flight of an OMPS is scheduled for early 2011 on the NPOESS Preparatory Project (NPP) satellite. The OMPS sensor data will be used to generate the ozone calibrated sensor data and environmental data record (EDR) products. The final OMPS sensor performance and algorithms for NPP will be presented, now that the FM1 flight sensor suite has completed sell off and is integrated on the NPP spacecraft. Challenges requiring future development, and during intensive calibration/validation on orbit will be described. Also, an overview of the sensor suite, the FM1 measurement performance, and details of the retrieval algorithms will be provided in this presentation.

Nowcast and Short-Term Forecast of Solar Radiation for Photovoltaic power and Solar thermal using 3rd generation geostationary satellite.

NASA Astrophysics Data System (ADS)

Takenaka, H.; Teruyuki, N.; Nakajima, T. Y.; Higurashi, A.; Hashimoto, M.; Suzuki, K.; Uchida, J.; Nagao, T. M.; Shi, C.; Inoue, T.

2017-12-01

It is important to estimate the earth's radiation budget accurately for understanding of climate. Clouds can cool the Earth by reflecting solar radiation but also maintain warmth by absorbing and emitting terrestrial radiation. similarly aerosols also have an effect on radiation budget by absorption and scattering of Solar radiation. In this study, we developed the high speed and accurate algorithm for shortwave (SW) radiation budget and it's applied to geostationary satellite for rapid analysis. It enabled highly accurate monitoring of solar radiation and photo voltaic (PV) power generation. Next step, we try to update the algorithm for retrieval of Aerosols and Clouds. It indicates the accurate atmospheric parameters for estimation of solar radiation. (This research was supported in part by CREST/EMS).

The Satellite based Monitoring Initiative for Regional Air quality (SAMIRA): Project summary and first results

NASA Astrophysics Data System (ADS)

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-resolution satellite products of air quality with the help of high-resolution model information. This will add value to existing earth observation products of air quality by bringing them to spatial scales that are more in line with what is generally required for studying urban and regional scale air quality. In a fifth activity, we implement robust and independent validation schemes for evaluating the quality of the generated products. Finally, in a sixth activity the consortium is working towards a pre-operational system for improved PM forecasts using observational (in situ and satellite) data assimilation. SAMIRA aims to maximize project benefits by liaison with national and regional environmental protection agencies and health institutions, as well as related ESA and European initiatives such as the Copernicus Atmosphere Monitoring Service (CAMS).

Least Square Approach for Estimating of Land Surface Temperature from LANDSAT-8 Satellite Data Using Radiative Transfer Equation

NASA Astrophysics Data System (ADS)

Jouybari-Moghaddam, Y.; Saradjian, M. R.; Forati, A. M.

2017-09-01

Land Surface Temperature (LST) is one of the significant variables measured by remotely sensed data, and it is applied in many environmental and Geoscience studies. The main aim of this study is to develop an algorithm to retrieve the LST from Landsat-8 satellite data using Radiative Transfer Equation (RTE). However, LST can be retrieved from RTE, but, since the RTE has two unknown parameters including LST and surface emissivity, estimating LST from RTE is an under the determined problem. In this study, in order to solve this problem, an approach is proposed an equation set includes two RTE based on Landsat-8 thermal bands (i.e.: band 10 and 11) and two additional equations based on the relation between the Normalized Difference Vegetation Index (NDVI) and emissivity of Landsat-8 thermal bands by using simulated data for Landsat-8 bands. The iterative least square approach was used for solving the equation set. The LST derived from proposed algorithm is evaluated by the simulated dataset, built up by MODTRAN. The result shows the Root Mean Squared Error (RMSE) is less than 1.18°K. Therefore; the proposed algorithm can be a suitable and robust method to retrieve the LST from Landsat-8 satellite data.

True colour classification of natural waters with medium-spectral resolution satellites: SeaWiFS, MODIS, MERIS and OLCI.

PubMed

Woerd, Hendrik J van der; Wernand, Marcel R

2015-10-09

The colours from natural waters differ markedly over the globe, depending on the water composition and illumination conditions. The space-borne "ocean colour" instruments are operational instruments designed to retrieve important water-quality indicators, based on the measurement of water leaving radiance in a limited number (5 to 10) of narrow (≈10 nm) bands. Surprisingly, the analysis of the satellite data has not yet paid attention to colour as an integral optical property that can also be retrieved from multispectral satellite data. In this paper we re-introduce colour as a valuable parameter that can be expressed mainly by the hue angle (α). Based on a set of 500 synthetic spectra covering a broad range of natural waters a simple algorithm is developed to derive the hue angle from SeaWiFS, MODIS, MERIS and OLCI data. The algorithm consists of a weighted linear sum of the remote sensing reflectance in all visual bands plus a correction term for the specific band-setting of each instrument. The algorithm is validated by a set of 603 hyperspectral measurements from inland-, coastal- and near-ocean waters. We conclude that the hue angle is a simple objective parameter of natural waters that can be retrieved uniformly for all space-borne ocean colour instruments.

Hail detection algorithm for the Global Precipitation Measuring mission core satellite sensors

NASA Astrophysics Data System (ADS)

Mroz, Kamil; Battaglia, Alessandro; Lang, Timothy J.; Tanelli, Simone; Cecil, Daniel J.; Tridon, Frederic

2017-04-01

By exploiting an abundant number of extreme storms observed simultaneously by the Global Precipitation Measurement (GPM) mission core satellite's suite of sensors and by the ground-based S-band Next-Generation Radar (NEXRAD) network over continental US, proxies for the identification of hail are developed based on the GPM core satellite observables. The full capabilities of the GPM observatory are tested by analyzing more than twenty observables and adopting the hydrometeor classification based on ground-based polarimetric measurements as truth. The proxies have been tested using the Critical Success Index (CSI) as a verification measure. The hail detection algorithm based on the mean Ku reflectivity in the mixed-phase layer performs the best, out of all considered proxies (CSI of 45%). Outside the Dual frequency Precipitation Radar (DPR) swath, the Polarization Corrected Temperature at 18.7 GHz shows the greatest potential for hail detection among all GMI channels (CSI of 26% at a threshold value of 261 K). When dual variable proxies are considered, the combination involving the mixed-phase reflectivity values at both Ku and Ka-bands outperforms all the other proxies, with a CSI of 49%. The best-performing radar-radiometer algorithm is based on the mixed-phase reflectivity at Ku-band and on the brightness temperature (TB) at 10.7 GHz (CSI of 46%). When only radiometric data are available, the algorithm based on the TBs at 36.6 and 166 GHz is the most efficient, with a CSI of 27.5%.

A climatology of fine absorbing biomass burning, urban and industrial aerosols detected from satellites

NASA Astrophysics Data System (ADS)

Kalaitzi, Nikoleta; Hatzianastassiou, Nikos; Gkikas, Antonis; Papadimas, Christos D.; Torres, Omar; Mihalopoulos, Nikos

2017-04-01

Natural biomass burning (BB) along with anthropogenic urban and industrial aerosol particles, altogether labeled here as BU aerosols, contain black and brown carbon which both absorb strongly the solar radiation. Thus, BU aerosols warm significantly the atmosphere also causing adjustments to cloud properties, which traditionally are known as cloud indirect and semi-direct effects. Given the role of the effects of BU aerosols for contemporary and future climate change, and the uncertainty associated with BU, both ascertained by the latest IPCC reports, there is an urgent need for improving our knowledge on the spatial and temporal variability of BU aerosols all over the globe. Over the last few decades, thanks to the rapid development of satellite observational techniques and retrieval algorithms it is now possible to detect BU aerosols based on satellite measurements. However, care must be taken in order to ensure the ability to distinguish BU from other aerosol types usually co-existing in the Earth's atmosphere. In the present study, an algorithm is presented, based on a synergy of different satellite measurements, aiming to identify and quantify BU aerosols over the entire globe and during multiple years. The objective is to build a satellite-based climatology of BU aerosols intended for use for various purposes. The produced regime, namely the spatial and temporal variability of BU aerosols, emphasizes the BU frequency of occurrence and their intensity, in terms of aerosol optical depth (AOD). The algorithm is using the following aerosol optical properties describing the size and atmospheric loading of BU aerosols: (i) spectral AOD, (ii) Ångström Exponent (AE), (iii) Fine Fraction (FF) and (iv) Aerosol Index (AI). The relevant data are taken from Collection 006 MODIS-Aqua, except for AI which is taken from OMI-Aura. The identification of BU aerosols by the algorithm is based on a specific thresholding technique, with AI≥1.5, AE≥1.2 and FF≥0.6 threshold values. The study spans the 11-year period 2005-2015, which enables to examine the inter-annual variability and possible changes of BU aerosols. Emphasis is given on specific world areas known to be sources of BU emissions. An effort is also made to separate with the algorithm the BB from BU aerosols, aiming to create a satellite database of biomass burning aerosols. The results of the algorithm, as to BB aerosols and the ability to separate them, are evaluated through comparisons against the global satellite databases of MODIS active fire counts as well as AIRS carbon monoxide (CO), which is a key indicator of presence of biomass burning activities. The algorithm estimates frequencies of occurrence of BU aerosols reaching up to 10 days/year and AOD values up to 1.5 or even larger. The results indicate the existence of seasonal cycles of biomass burning in south and central Africa as well as in South America (Amazonia), with highest BU frequencies during June-September, December-February and August-October, respectively, whereas they successfully reproduce features like the export of African BB aerosols into the Atlantic Ocean.

Strategy for Developing Expert-System-Based Internet Protocols (TCP/IP)

NASA Technical Reports Server (NTRS)

Ivancic, William D.

1997-01-01

The Satellite Networks and Architectures Branch of NASA's Lewis Research is addressing the issue of seamless interoperability of satellite networks with terrestrial networks. One of the major issues is improving reliable transmission protocols such as TCP over long latency and error-prone links. Many tuning parameters are available to enhance the performance of TCP including segment size, timers and window sizes. There are also numerous congestion avoidance algorithms such as slow start, selective retransmission and selective acknowledgment that are utilized to improve performance. This paper provides a strategy to characterize the performance of TCP relative to various parameter settings in a variety of network environments (i.e. LAN, WAN, wireless, satellite, and IP over ATM). This information can then be utilized to develop expert-system-based Internet protocols.

Development of a Real Time Internal Charging Tool for Geosynchronous Orbit

NASA Technical Reports Server (NTRS)

Posey, Nathaniel A.; Minow, Joesph I.

2013-01-01

The high-energy electron fluxes encountered by satellites in geosynchronous orbit pose a serious threat to onboard instrumentation and other circuitry. A substantial build-up of charge within a satellite's insulators can lead to electric fields in excess of the breakdown strength, which can result in destructive electrostatic discharges. The software tool we've developed uses data on the plasma environment taken from NOAA's GOES-13 satellite to track the resulting electric field strength within a material of arbitrary depth and conductivity and allows us to monitor the risk of material failure in real time. The tool also utilizes a transport algorithm to simulate the effects of shielding on the dielectric. Data on the plasma environment and the resulting electric fields are logged to allow for playback at a variable frame rate.

A Leo Satellite Navigation Algorithm Based on GPS and Magnetometer Data

NASA Technical Reports Server (NTRS)

Deutschmann, Julie; Harman, Rick; Bar-Itzhack, Itzhack

2001-01-01

The Global Positioning System (GPS) has become a standard method for low cost onboard satellite orbit determination. The use of a GPS receiver as an attitude and rate sensor has also been developed in the recent past. Additionally, focus has been given to attitude and orbit estimation using the magnetometer, a low cost, reliable sensor. Combining measurements from both GPS and a magnetometer can provide a robust navigation system that takes advantage of the estimation qualities of both measurements. Ultimately, a low cost, accurate navigation system can result, potentially eliminating the need for more costly sensors, including gyroscopes. This work presents the development of a technique to eliminate numerical differentiation of the GPS phase measurements and also compares the use of one versus two GPS satellites.

Evaluation of Integrated Multi-satellitE Retrievals for GPM with All Weather Gauge Observations over CONUS

NASA Astrophysics Data System (ADS)

Chen, S.; Qi, Y.; Hu, B.; Hu, J.; Hong, Y.

2015-12-01

The Global Precipitation Measurement (GPM) mission is composed of an international network of satellites that provide the next-generation global observations of rain and snow. Integrated Multi-satellitE Retrievals for GPM (IMERG) is the state-of-art precipitation products with high spatio-temporal resolution of 0.1°/30min. IMERG unifies precipitation measurements from a constellation of research and operational satellites with the core sensors dual-frequency precipitation radar (DPR) and microwave imager (GMI) on board a "Core" satellite. Additionally, IMERG blends the advantages of currently most popular satellite-based quantitative precipitation estimates (QPE) algorithms, i.e. TRMM Multi-satellite Precipitation Analysis (TMPA), Climate Prediction Center morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS). The real-time and post real-time IMERG products are now available online at https://stormpps.gsfc.nasa.gov/storm. In this study, the final run post real-time IMERG is evaluated with all-weather manual gauge observations over CONUS from June 2014 through May 2015. Relative Bias (RB), Root-Mean-Squared Error (RMSE), Correlation Coefficient (CC), Probability Of Detection (POD), False Alarm Ratio (FAR), and Critical Success Index (CSI) are used to quantify the performance of IMERG. The performance of IMERG in estimating snowfall precipitation is highlighted in the study. This timely evaluation with all-weather gauge observations is expected to offer insights into performance of IMERG and thus provide useful feedback to the algorithm developers as well as the GPM data users.

An Evolutionary Algorithm for Fast Intensity Based Image Matching Between Optical and SAR Satellite Imagery

NASA Astrophysics Data System (ADS)

Fischer, Peter; Schuegraf, Philipp; Merkle, Nina; Storch, Tobias

2018-04-01

This paper presents a hybrid evolutionary algorithm for fast intensity based matching between satellite imagery from SAR and very high-resolution (VHR) optical sensor systems. The precise and accurate co-registration of image time series and images of different sensors is a key task in multi-sensor image processing scenarios. The necessary preprocessing step of image matching and tie-point detection is divided into a search problem and a similarity measurement. Within this paper we evaluate the use of an evolutionary search strategy for establishing the spatial correspondence between satellite imagery of optical and radar sensors. The aim of the proposed algorithm is to decrease the computational costs during the search process by formulating the search as an optimization problem. Based upon the canonical evolutionary algorithm, the proposed algorithm is adapted for SAR/optical imagery intensity based matching. Extensions are drawn using techniques like hybridization (e.g. local search) and others to lower the number of objective function calls and refine the result. The algorithm significantely decreases the computational costs whilst finding the optimal solution in a reliable way.

Bio-Optical Measurement and Modeling of the California Current and Southern Oceans

NASA Technical Reports Server (NTRS)

Mitchell, B. Gregg; Mitchell, B. Greg

2003-01-01

The SIMBIOS project's principal goals are to validate standard or experimental ocean color products through detailed bio-optical and biogeochemical measurements, and to combine Ocean optical observations with modeling to contribute to satellite vicarious radiometric calibration and algorithm development.

Autonomous subpixel satellite track end point determination for space-based images.

PubMed

Simms, Lance M

2011-08-01

An algorithm for determining satellite track end points with subpixel 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 end point 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.

Sampling Errors in Monthly Rainfall Totals for TRMM and SSM/I, Based on Statistics of Retrieved Rain Rates and Simple Models

NASA Technical Reports Server (NTRS)

Bell, Thomas L.; Kundu, Prasun K.; Einaudi, Franco (Technical Monitor)

2000-01-01

Estimates from TRMM satellite data of monthly total rainfall over an area are subject to substantial sampling errors due to the limited number of visits to the area by the satellite during the month. Quantitative comparisons of TRMM averages with data collected by other satellites and by ground-based systems require some estimate of the size of this sampling error. A method of estimating this sampling error based on the actual statistics of the TRMM observations and on some modeling work has been developed. "Sampling error" in TRMM monthly averages is defined here relative to the monthly total a hypothetical satellite permanently stationed above the area would have reported. "Sampling error" therefore includes contributions from the random and systematic errors introduced by the satellite remote sensing system. As part of our long-term goal of providing error estimates for each grid point accessible to the TRMM instruments, sampling error estimates for TRMM based on rain retrievals from TRMM microwave (TMI) data are compared for different times of the year and different oceanic areas (to minimize changes in the statistics due to algorithmic differences over land and ocean). Changes in sampling error estimates due to changes in rain statistics due 1) to evolution of the official algorithms used to process the data, and 2) differences from other remote sensing systems such as the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I), are analyzed.

Using Information From Prior Satellite Scans to Improve Cloud Detection Near the Day-Night Terminator

NASA Technical Reports Server (NTRS)

Yost, Christopher R.; Minnis, Patrick; Trepte, Qing Z.; Palikonda, Rabindra; Ayers, Jeffrey K.; Spangenberg, Doulas A.

2012-01-01

With geostationary satellite data it is possible to have a continuous record of diurnal cycles of cloud properties for a large portion of the globe. Daytime cloud property retrieval algorithms are typically superior to nighttime algorithms because daytime methods utilize measurements of reflected solar radiation. However, reflected solar radiation is difficult to accurately model for high solar zenith angles where the amount of incident radiation is small. Clear and cloudy scenes can exhibit very small differences in reflected radiation and threshold-based cloud detection methods have more difficulty setting the proper thresholds for accurate cloud detection. Because top-of-atmosphere radiances are typically more accurately modeled outside the terminator region, information from previous scans can help guide cloud detection near the terminator. This paper presents an algorithm that uses cloud fraction and clear and cloudy infrared brightness temperatures from previous satellite scan times to improve the performance of a threshold-based cloud mask near the terminator. Comparisons of daytime, nighttime, and terminator cloud fraction derived from Geostationary Operational Environmental Satellite (GOES) radiance measurements show that the algorithm greatly reduces the number of false cloud detections and smoothes the transition from the daytime to the nighttime clod detection algorithm. Comparisons with the Geoscience Laser Altimeter System (GLAS) data show that using this algorithm decreases the number of false detections by approximately 20 percentage points.

The Langley Parameterized Shortwave Algorithm (LPSA) for Surface Radiation Budget Studies. 1.0

NASA Technical Reports Server (NTRS)

Gupta, Shashi K.; Kratz, David P.; Stackhouse, Paul W., Jr.; Wilber, Anne C.

2001-01-01

An efficient algorithm was developed during the late 1980's and early 1990's by W. F. Staylor at NASA/LaRC for the purpose of deriving shortwave surface radiation budget parameters on a global scale. While the algorithm produced results in good agreement with observations, the lack of proper documentation resulted in a weak acceptance by the science community. The primary purpose of this report is to develop detailed documentation of the algorithm. In the process, the algorithm was modified whenever discrepancies were found between the algorithm and its referenced literature sources. In some instances, assumptions made in the algorithm could not be justified and were replaced with those that were justifiable. The algorithm uses satellite and operational meteorological data for inputs. Most of the original data sources have been replaced by more recent, higher quality data sources, and fluxes are now computed on a higher spatial resolution. Many more changes to the basic radiation scheme and meteorological inputs have been proposed to improve the algorithm and make the product more useful for new research projects. Because of the many changes already in place and more planned for the future, the algorithm has been renamed the Langley Parameterized Shortwave Algorithm (LPSA).

Investigation and Development of Data-Driven D-Region Model for HF Systems Impacts

NASA Technical Reports Server (NTRS)

Eccles, J. V.; Rice, D.; Sojka, J. J.; Hunsucker, R. D.

2002-01-01

Space Environment Corporation (SEC) and RP Consultants (RPC) are to develop and validate a weather-capable D region model for making High Frequency (HF) absorption predictions in support of the HF communications and radar communities. The weather-capable model will assimilate solar and earth space observations from NASA satellites. The model will account for solar-induced impacts on HF absorption, including X-rays, Solar Proton Events (SPE's), and auroral precipitation. The work plan includes: I . Optimize D-region model to quickly obtain ion and electron densities for proper HF absorption calculations. 2. Develop indices-driven modules for D-region ionization sources for low, mid, & high latitudes including X-rays, cosmic rays, auroral precipitation, & solar protons. (Note: solar spectrum & auroral modules already exist). 3. Setup low-cost monitors of existing HF beacons and add one single-frequency beacon. 4. Use PENEX HF-link database with HF monitor data to validate D-region/HF absorption model using climatological ionization drivers. 5. Develop algorithms to assimilate NASA satellite data of solar, interplanetary, and auroral observations into ionization source modules. 6. Use PENEX HF-link & HF-beacon data for skill score comparison of assimilation versus climatological D-region/HF absorption model. Only some satellites are available for the PENEX time period, thus, HF-beacon data is necessary. 7. Use HF beacon monitors to develop HF-link data assimilation algorithms for regional improvement to the D-region/HF absorption model.

Integrated approach using multi-platform sensors for enhanced high-resolution daily ice cover product

NASA Astrophysics Data System (ADS)

Bonev, George; Gladkova, Irina; Grossberg, Michael; Romanov, Peter; Helfrich, Sean

2016-09-01

The ultimate objective of this work is to improve characterization of the ice cover distribution in the polar areas, to improve sea ice mapping and to develop a new automated real-time high spatial resolution multi-sensor ice extent and ice edge product for use in operational applications. Despite a large number of currently available automated satellite-based sea ice extent datasets, analysts at the National Ice Center tend to rely on original satellite imagery (provided by satellite optical, passive microwave and active microwave sensors) mainly because the automated products derived from satellite optical data have gaps in the area coverage due to clouds and darkness, passive microwave products have poor spatial resolution, automated ice identifications based on radar data are not quite reliable due to a considerable difficulty in discriminating between the ice cover and rough ice-free ocean surface due to winds. We have developed a multisensor algorithm that first extracts maximum information on the sea ice cover from imaging instruments VIIRS and MODIS, including regions covered by thin, semitransparent clouds, then supplements the output by the microwave measurements and finally aggregates the results into a cloud gap free daily product. This ability to identify ice cover underneath thin clouds, which is usually masked out by traditional cloud detection algorithms, allows for expansion of the effective coverage of the sea ice maps and thus more accurate and detailed delineation of the ice edge. We have also developed a web-based monitoring system that allows comparison of our daily ice extent product with the several other independent operational daily products.

Adaptive topographic mass correction for satellite gravity and gravity gradient data

NASA Astrophysics Data System (ADS)

Holzrichter, Nils; Szwillus, Wolfgang; Götze, Hans-Jürgen

2014-05-01

Subsurface modelling with gravity data includes a reliable topographic mass correction. Since decades, this mandatory step is a standard procedure. However, originally methods were developed for local terrestrial surveys. Therefore, these methods often include defaults like a limited correction area of 167 km around an observation point, resampling topography depending on the distance to the station or disregard the curvature of the earth. New satellite gravity data (e.g. GOCE) can be used for large scale lithospheric modelling with gravity data. The investigation areas can include thousands of kilometres. In addition, measurements are located in the flight height of the satellite (e.g. ~250 km for GOCE). The standard definition of the correction area and the specific grid spacing around an observation point was not developed for stations located in these heights and areas of these dimensions. This asks for a revaluation of the defaults used for topographic correction. We developed an algorithm which resamples the topography based on an adaptive approach. Instead of resampling topography depending on the distance to the station, the grids will be resampled depending on its influence at the station. Therefore, the only value the user has to define is the desired accuracy of the topographic correction. It is not necessary to define the grid spacing and a limited correction area. Furthermore, the algorithm calculates the topographic mass response with a spherical shaped polyhedral body. We show examples for local and global gravity datasets and compare the results of the topographic mass correction to existing approaches. We provide suggestions how satellite gravity and gradient data should be corrected.

Algorithms for the Computation of Debris Risk

NASA Technical Reports Server (NTRS)

Matney, Mark J.

2017-01-01

Determining the risks from space debris involve a number of statistical calculations. These calculations inevitably involve assumptions about geometry - including the physical geometry of orbits and the geometry of satellites. A number of tools have been developed in NASA’s Orbital Debris Program Office to handle these calculations; many of which have never been published before. These include algorithms that are used in NASA’s Orbital Debris Engineering Model ORDEM 3.0, as well as other tools useful for computing orbital collision rates and ground casualty risks. This paper presents an introduction to these algorithms and the assumptions upon which they are based.

Algorithms for the Computation of Debris Risks

NASA Technical Reports Server (NTRS)

Matney, Mark

2017-01-01

Determining the risks from space debris involve a number of statistical calculations. These calculations inevitably involve assumptions about geometry - including the physical geometry of orbits and the geometry of non-spherical satellites. A number of tools have been developed in NASA's Orbital Debris Program Office to handle these calculations; many of which have never been published before. These include algorithms that are used in NASA's Orbital Debris Engineering Model ORDEM 3.0, as well as other tools useful for computing orbital collision rates and ground casualty risks. This paper will present an introduction to these algorithms and the assumptions upon which they are based.

Algorithms for computing the geopotential using a simple density layer

NASA Technical Reports Server (NTRS)

Morrison, F.

1976-01-01

Several algorithms have been developed for computing the potential and attraction of a simple density layer. These are numerical cubature, Taylor series, and a mixed analytic and numerical integration using a singularity-matching technique. A computer program has been written to combine these techniques for computing the disturbing acceleration on an artificial earth satellite. A total of 1640 equal-area, constant surface density blocks on an oblate spheroid are used. The singularity-matching algorithm is used in the subsatellite region, Taylor series in the surrounding zone, and numerical cubature on the rest of the earth.

Monitoring Rainfall by Combining Ground-based Observed Precipitation and PERSIANN Satellite Product (Case Study Area: Lake Urmia Basin)

NASA Astrophysics Data System (ADS)

Abrishamchi, A.; Mirshahi, A.

2015-12-01

The global coverage, quick access, and appropriate spatial-temporal resolution of satellite precipitation data renders the data appropriate for hydrologic studies, especially in regions with no sufficient rain-gauge network. On the other hand, satellite precipitation products may have major errors. The present study aims at reduction of estimation error of the PERSIANN satellite precipitation product. Bayesian logic employed to develop a statistical relationship between historical ground-based and satellite precipitation data. This relationship can then be used to reduce satellite precipitation product error in near real time, when there is no ground-based precipitation observation. The method was evaluated in the Lake Urmia basin with a monthly time scale; November to May of 2000- 2008 for the purpose of model development and two years of 2009 and 2010 for the validation of the established relationships. Moreover, Kriging interpolation method was employed to estimate the average rainfall in the basin. Furthermore, to downscale the satellite precipitation product from 0.25o to 0.05o, data-location downscaling algorithm was used. In 76 percent of months, the final product, compared with the satellite precipitation, had less error during the validation period. Additionally, its performance was marginally better than adjusted PERSIANN product.

New-Generation BeiDou (BDS-3) Experimental Satellite Precise Orbit Determination with an Improved Cycle-Slip Detection and Repair Algorithm

PubMed Central

Hu, Chao; Wang, Qianxin; Wang, Zhongyuan; Hernández Moraleda, Alberto

2018-01-01

Currently, five new-generation BeiDou (BDS-3) experimental satellites are working in orbit and broadcast B1I, B3I, and other new signals. Precise satellite orbit determination of the BDS-3 is essential for the future global services of the BeiDou system. However, BDS-3 experimental satellites are mainly tracked by the international GNSS Monitoring and Assessment Service (iGMAS) network. Under the current constraints of the limited data sources and poor data quality of iGMAS, this study proposes an improved cycle-slip detection and repair algorithm, which is based on a polynomial prediction of ionospheric delays. The improved algorithm takes the correlation of ionospheric delays into consideration to accurately estimate and repair cycle slips in the iGMAS data. Moreover, two methods of BDS-3 experimental satellite orbit determination, namely, normal equation stacking (NES) and step-by-step (SS), are designed to strengthen orbit estimations and to make full use of the BeiDou observations in different tracking networks. In addition, a method to improve computational efficiency based on a matrix eigenvalue decomposition algorithm is derived in the NES. Then, one-year of BDS-3 experimental satellite precise orbit determinations were conducted based on iGMAS and Multi-GNSS Experiment (MGEX) networks. Furthermore, the orbit accuracies were analyzed from the discrepancy of overlapping arcs and satellite laser range (SLR) residuals. The results showed that the average three-dimensional root-mean-square error (3D RMS) of one-day overlapping arcs for BDS-3 experimental satellites (C31, C32, C33, and C34) acquired by NES and SS are 31.0, 36.0, 40.3, and 50.1 cm, and 34.6, 39.4, 43.4, and 55.5 cm, respectively; the RMS of SLR residuals are 55.1, 49.6, 61.5, and 70.9 cm and 60.5, 53.6, 65.8, and 73.9 cm, respectively. Finally, one month of observations were used in four schemes of BDS-3 experimental satellite orbit determination to further investigate the reliability and advantages of the improved methods. It was suggested that the scheme with improved cycle-slip detection and repair algorithm based on NES was optimal, which improved the accuracy of BDS-3 experimental satellite orbits by 34.07%, 41.05%, 72.29%, and 74.33%, respectively, compared with the widely-used strategy. Therefore, improved methods for the BDS-3 experimental satellites proposed in this study are very beneficial for the determination of new-generation BeiDou satellite precise orbits. PMID:29724062

Moon Search Algorithms for NASA's Dawn Mission to Asteroid Vesta

NASA Technical Reports Server (NTRS)

Memarsadeghi, Nargess; Mcfadden, Lucy A.; Skillman, David R.; McLean, Brian; Mutchler, Max; Carsenty, Uri; Palmer, Eric E.

2012-01-01

A moon or natural satellite is a celestial body that orbits a planetary body such as a planet, dwarf planet, or an asteroid. Scientists seek understanding the origin and evolution of our solar system by studying moons of these bodies. Additionally, searches for satellites of planetary bodies can be important to protect the safety of a spacecraft as it approaches or orbits a planetary body. If a satellite of a celestial body is found, the mass of that body can also be calculated once its orbit is determined. Ensuring the Dawn spacecraft's safety on its mission to the asteroid Vesta primarily motivated the work of Dawn's Satellite Working Group (SWG) in summer of 2011. Dawn mission scientists and engineers utilized various computational tools and techniques for Vesta's satellite search. The objectives of this paper are to 1) introduce the natural satellite search problem, 2) present the computational challenges, approaches, and tools used when addressing this problem, and 3) describe applications of various image processing and computational algorithms for performing satellite searches to the electronic imaging and computer science community. Furthermore, we hope that this communication would enable Dawn mission scientists to improve their satellite search algorithms and tools and be better prepared for performing the same investigation in 2015, when the spacecraft is scheduled to approach and orbit the dwarf planet Ceres.

Fine-tuning satellite-based rainfall estimates

NASA Astrophysics Data System (ADS)

Harsa, Hastuadi; Buono, Agus; Hidayat, Rahmat; Achyar, Jaumil; Noviati, Sri; Kurniawan, Roni; Praja, Alfan S.

2018-05-01

Rainfall datasets are available from various sources, including satellite estimates and ground observation. The locations of ground observation scatter sparsely. Therefore, the use of satellite estimates is advantageous, because satellite estimates can provide data on places where the ground observations do not present. However, in general, the satellite estimates data contain bias, since they are product of algorithms that transform the sensors response into rainfall values. Another cause may come from the number of ground observations used by the algorithms as the reference in determining the rainfall values. This paper describe the application of bias correction method to modify the satellite-based dataset by adding a number of ground observation locations that have not been used before by the algorithm. The bias correction was performed by utilizing Quantile Mapping procedure between ground observation data and satellite estimates data. Since Quantile Mapping required mean and standard deviation of both the reference and the being-corrected data, thus the Inverse Distance Weighting scheme was applied beforehand to the mean and standard deviation of the observation data in order to provide a spatial composition of them, which were originally scattered. Therefore, it was possible to provide a reference data point at the same location with that of the satellite estimates. The results show that the new dataset have statistically better representation of the rainfall values recorded by the ground observation than the previous dataset.

Optical and Ancillary Measurements at High Latitudes in Support of the MODIS Ocean Validation Program

NASA Technical Reports Server (NTRS)

Stramski, Dariusz; Stramska, Malgorzata; Starr, David OC. (Technical Monitor)

2002-01-01

The overall goal of this project was to validate and refine ocean color algorithms at high latitudes in the north polar region of the Atlantic. The specific objectives were defined as follows: (1) to identify and quantify errors in the satellite-derived water-leaving radiances and chlorophyll concentration; (2) to develop understanding of these errors; and (3) to improve in-water ocean color algorithms for retrieving chlorophyll concentration in the investigated region.

Determination of water depth with high-resolution satellite imagery over variable bottom types

USGS Publications Warehouse

Stumpf, Richard P.; Holderied, Kristine; Sinclair, Mark

2003-01-01

A standard algorithm for determining depth in clear water from passive sensors exists; but it requires tuning of five parameters and does not retrieve depths where the bottom has an extremely low albedo. To address these issues, we developed an empirical solution using a ratio of reflectances that has only two tunable parameters and can be applied to low-albedo features. The two algorithms--the standard linear transform and the new ratio transform--were compared through analysis of IKONOS satellite imagery against lidar bathymetry. The coefficients for the ratio algorithm were tuned manually to a few depths from a nautical chart, yet performed as well as the linear algorithm tuned using multiple linear regression against the lidar. Both algorithms compensate for variable bottom type and albedo (sand, pavement, algae, coral) and retrieve bathymetry in water depths of less than 10-15 m. However, the linear transform does not distinguish depths >15 m and is more subject to variability across the studied atolls. The ratio transform can, in clear water, retrieve depths in >25 m of water and shows greater stability between different areas. It also performs slightly better in scattering turbidity than the linear transform. The ratio algorithm is somewhat noisier and cannot always adequately resolve fine morphology (structures smaller than 4-5 pixels) in water depths >15-20 m. In general, the ratio transform is more robust than the linear transform.

Multi-source Geospatial Data Analysis with Google Earth Engine

NASA Astrophysics Data System (ADS)

Erickson, T.

2014-12-01

The Google Earth Engine platform is a cloud computing environment for data analysis that combines a public data catalog with a large-scale computational facility optimized for parallel processing of geospatial data. The data catalog is a multi-petabyte archive of georeferenced datasets that include images from Earth observing satellite and airborne sensors (examples: USGS Landsat, NASA MODIS, USDA NAIP), weather and climate datasets, and digital elevation models. Earth Engine supports both a just-in-time computation model that enables real-time preview and debugging during algorithm development for open-ended data exploration, and a batch computation mode for applying algorithms over large spatial and temporal extents. The platform automatically handles many traditionally-onerous data management tasks, such as data format conversion, reprojection, and resampling, which facilitates writing algorithms that combine data from multiple sensors and/or models. Although the primary use of Earth Engine, to date, has been the analysis of large Earth observing satellite datasets, the computational platform is generally applicable to a wide variety of use cases that require large-scale geospatial data analyses. This presentation will focus on how Earth Engine facilitates the analysis of geospatial data streams that originate from multiple separate sources (and often communities) and how it enables collaboration during algorithm development and data exploration. The talk will highlight current projects/analyses that are enabled by this functionality.https://earthengine.google.org

Satellite-map position estimation for the Mars rover

NASA Technical Reports Server (NTRS)

Hayashi, Akira; Dean, Thomas

1989-01-01

A method for locating the Mars rover using an elevation map generated from satellite data is described. In exploring its environment, the rover is assumed to generate a local rover-centered elevation map that can be used to extract information about the relative position and orientation of landmarks corresponding to local maxima. These landmarks are integrated into a stochastic map which is then matched with the satellite map to obtain an estimate of the robot's current location. The landmarks are not explicitly represented in the satellite map. The results of the matching algorithm correspond to a probabilistic assessment of whether or not the robot is located within a given region of the satellite map. By assigning a probabilistic interpretation to the information stored in the satellite map, researchers are able to provide a precise characterization of the results computed by the matching algorithm.

Surface reflectance retrieval from satellite and aircraft sensors - Results of sensors and algorithm comparisons during FIFE

NASA Technical Reports Server (NTRS)

Markham, B. L.; Halthore, R. N.; Goetz, S. J.

1992-01-01

Visible to shortwave infrared radiometric data collected by a number of remote sensing instruments on aircraft and satellite platforms were compared over common areas in the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) site on August 4, 1989, to assess their radiometric consistency and the adequacy of atmospheric correction algorithms. The instruments in the study included the Landsat 5 Thematic Mapper (TM), the SPOT 1 high-resolution visible (HRV) 1 sensor, the NS001 Thematic Mapper simulator, and the modular multispectral radiometers (MMRs). Atmospheric correction routines analyzed were an algorithm developed for FIFE, LOWTRAN 7, and 5S. A comparison between corresponding bands of the SPOT 1 HRV 1 and the Landsat 5 TM sensors indicated that the two instruments were radiometrically consistent to within about 5 percent. Retrieved surface reflectance factors using the FIFE algorithm over one site under clear atmospheric conditions indicated a capability to determine near-nadir surface reflectance factors to within about 0.01 at a reflectance of 0.06 in the visible (0.4-0.7 microns) and about 0.30 in the near infrared (0.7-1.2 microns) for all but the NS001 sensor. All three atmospheric correction procedures produced absolute reflectances to within 0.005 in the visible and near infrared. In the shortwave infrared (1.2-2.5 microns) region the three algorithms differed in the retrieved surface reflectances primarily owing to differences in predicted gaseous absorption. Although uncertainties in the measured surface reflectance in the shortwave infrared precluded definitive results, the 5S code appeared to predict gaseous transmission marginally more accurately than LOWTRAN 7.

High Resolution Monthly Oceanic Rainfall Based on Microwave Brightness Temperature Histograms

NASA Astrophysics Data System (ADS)

Shin, D.; Chiu, L. S.

2005-12-01

A statistical emission-based passive microwave retrieval algorithm has been developed by Wilheit, Chang and Chiu (1991) to estimate space/time oceanic rainfall. The algorithm has been applied to Special Sensor Microwave Imager (SSM/I) data taken on board the Defense Meteorological Satellite Program (DMSP) satellites to provide monthly oceanic rainfall over 2.5ox2.5o and 5ox5o latitude-longitude boxes by the Global Precipitation Climatology Project-Polar Satellite Precipitation Data Center (GPCP-PSPDC, URL: http://gpcp-pspdc.gmu.edu/) as part of NASA's contribution to the GPCP. The algorithm has been modified and applied to the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) data to produce a TRMM Level 3 standard product (3A11) over 5ox5o latitude/longitude boxes. In this study, the algorithm code is modified to retrieve rain rates at 2.5ox2.5o and 1ox1o resolutions for TMI. Two months of TMI data have been tested and the results compared with the monthly mean rain rates derived from TRMM Level 2 TMI rain profile algorithm (2A12) and the original 5ox5o data from 3A11. The rainfall pattern is very similar to the monthly average of 2A12, although the intensity is slightly higher. Details in the rain pattern, such as rain shadow due to island blocking, which were not discernible from the low resolution products, are now easily discernible. The spatial average of the higher resolution rain rates are in general slightly higher than lower resolution rain rates, although a Student-t test shows no significant difference. This high resolution product will be useful for the calibration of IR rain estimates for the production of the GPCP merge rain product.

A hybrid online scheduling mechanism with revision and progressive techniques for autonomous Earth observation satellite

NASA Astrophysics Data System (ADS)

Li, Guoliang; Xing, Lining; Chen, Yingwu

2017-11-01

The autonomicity of self-scheduling on Earth observation satellite and the increasing scale of satellite network attract much attention from researchers in the last decades. In reality, the limited onboard computational resource presents challenge for the online scheduling algorithm. This study considered online scheduling problem for a single autonomous Earth observation satellite within satellite network environment. It especially addressed that the urgent tasks arrive stochastically during the scheduling horizon. We described the problem and proposed a hybrid online scheduling mechanism with revision and progressive techniques to solve this problem. The mechanism includes two decision policies, a when-to-schedule policy combining periodic scheduling and critical cumulative number-based event-driven rescheduling, and a how-to-schedule policy combining progressive and revision approaches to accommodate two categories of task: normal tasks and urgent tasks. Thus, we developed two heuristic (re)scheduling algorithms and compared them with other generally used techniques. Computational experiments indicated that the into-scheduling percentage of urgent tasks in the proposed mechanism is much higher than that in periodic scheduling mechanism, and the specific performance is highly dependent on some mechanism-relevant and task-relevant factors. For the online scheduling, the modified weighted shortest imaging time first and dynamic profit system benefit heuristics outperformed the others on total profit and the percentage of successfully scheduled urgent tasks.

Automated Construction of Coverage Catalogues of Aster Satellite Image for Urban Areas of the World

NASA Astrophysics Data System (ADS)

Miyazaki, H.; Iwao, K.; Shibasaki, R.

2012-07-01

We developed an algorithm to determine a combination of satellite images according to observation extent and image quality. The algorithm was for testing necessity for completing coverage of the search extent. The tests excluded unnecessary images with low quality and preserve necessary images with good quality. The search conditions of the satellite images could be extended, indicating the catalogue could be constructed with specified periods required for time series analysis. We applied the method to a database of metadata of ASTER satellite images archived in GEO Grid of National Institute of Advanced Industrial Science and Technology (AIST), Japan. As indexes of populated places with geographical coordinates, we used a database of 3372 populated place of more than 0.1 million populations retrieved from GRUMP Settlement Points, a global gazetteer of cities, which has geographical names of populated places associated with geographical coordinates and population data. From the coordinates of populated places, 3372 extents were generated with radiuses of 30 km, a half of swath of ASTER satellite images. By merging extents overlapping each other, they were assembled into 2214 extents. As a result, we acquired combinations of good quality for 1244 extents, those of low quality for 96 extents, incomplete combinations for 611 extents. Further improvements would be expected by introducing pixel-based cloud assessment and pixel value correction over seasonal variations.

Ice surface temperature retrieval from AVHRR, ATSR, and passive microwave satellite data: Algorithm development and application

NASA Technical Reports Server (NTRS)

Key, Jeff; Maslanik, James; Steffen, Konrad

1995-01-01

During the second phase project year we have made progress in the development and refinement of surface temperature retrieval algorithms and in product generation. More specifically, we have accomplished the following: (1) acquired a new advanced very high resolution radiometer (AVHRR) data set for the Beaufort Sea area spanning an entire year; (2) acquired additional along-track scanning radiometer(ATSR) data for the Arctic and Antarctic now totalling over eight months; (3) refined our AVHRR Arctic and Antarctic ice surface temperature (IST) retrieval algorithm, including work specific to Greenland; (4) developed ATSR retrieval algorithms for the Arctic and Antarctic, including work specific to Greenland; (5) developed cloud masking procedures for both AVHRR and ATSR; (6) generated a two-week bi-polar global area coverage (GAC) set of composite images from which IST is being estimated; (7) investigated the effects of clouds and the atmosphere on passive microwave 'surface' temperature retrieval algorithms; and (8) generated surface temperatures for the Beaufort Sea data set, both from AVHRR and special sensor microwave imager (SSM/I).

SPHERES: Design of a Formation Flying Testbed for ISS

NASA Astrophysics Data System (ADS)

Sell, S. W.; Chen, S. E.

2002-01-01

The SPHERES (Synchronized Position Hold Engage and Reorient Experimental Satellites) payload is an innovative formation-flying spacecraft testbed currently being developed for use internally aboard the International Space Station (ISS). The purpose of the testbed is to provide a cost-effective, long duration, replenishable, and easily reconfigurable platform with representative dynamics for the development and validation of metrology, formation flying, and autonomy algorithms. The testbed components consist of three 8-inch diameter free-flying "satellites," five ultrasound beacons, and an ISS laptop workstation. Each satellite is self-contained with on-board battery power, cold-gas propulsion (CO2), and processing systems. Satellites use two packs of eight standard AA batteries for approximately 90 minutes of lifetime while beacons last the duration of the mission powered by a single AA battery. The propulsion system uses pressurized carbon dioxide gas, stored in replaceable tanks, distributed through an adjustable regulator and associated tubing to twelve thrusters located on the faces of the satellites. A Texas Instruments C6701 DSP handles control algorithm data while an FPGA manages all sensor data, timing, and communication processes on the satellite. All three satellites communicate with each other and with the controlling laptop via a wireless RF link. Five ultrasound beacons, located around a predetermined work area, transmit ultrasound signals that are received by each satellite. The system effectively acts as a pseudo-GPS system, allowing the satellites to determine position and attitude and to navigate within the test arena. The payload hardware are predominantly Commercial Off The Shelf (COTS) products with the exception of custom electronics boards, selected propulsion system adaptors, and beacon and satellite structural elements. Operationally, SPHERES will run in short duration test sessions with approximately two weeks between each session. During operations, satellites will autonomously perform various maneuvers with one to three satellites operating simultaneously, involving a crew member only to upload protocols and replace satellite consumables (gas and power) during the test session. Once completed, data will be downlinked to the ground for analysis by the SPHERES team, facilitating the iterative process of new and/or modified protocols being uplinked for use in the next test session. SPHERES has prior flight experience on the NASA KC-135 Reduced Gravity aircraft and has also been in constant use in laboratory air table testing for almost two years. Slated for launch to the International Space Station on ISS12A.1, SPHERES will use its six-month flight to conduct risk-reduction investigations involving the coordinated motion of multiple satellites in a micro-gravity environment.

Spectrum and power allocation in cognitive multi-beam satellite communications with flexible satellite payloads

NASA Astrophysics Data System (ADS)

Liu, Zhihui; Wang, Haitao; Dong, Tao; Yin, Jie; Zhang, Tingting; Guo, Hui; Li, Dequan

2018-02-01

In this paper, the cognitive multi-beam satellite system, i.e., two satellite networks coexist through underlay spectrum sharing, is studied, and the power and spectrum allocation method is employed for interference control and throughput maximization. Specifically, the multi-beam satellite with flexible payload reuses the authorized spectrum of the primary satellite, adjusting its transmission band as well as power for each beam to limit its interference on the primary satellite below the prescribed threshold and maximize its own achievable rate. This power and spectrum allocation problem is formulated as a mixed nonconvex programming. For effective solving, we first introduce the concept of signal to leakage plus noise ratio (SLNR) to decouple multiple transmit power variables in the both objective and constraint, and then propose a heuristic algorithm to assign spectrum sub-bands. After that, a stepwise plus slice-wise algorithm is proposed to implement the discrete power allocation. Finally, simulation results show that adopting cognitive technology can improve spectrum efficiency of the satellite communication.

On orbital allotments for geostationary satellites

NASA Technical Reports Server (NTRS)

Gonsalvez, David J. A.; Reilly, Charles H.; Mount-Campbell, Clark A.

1986-01-01

The following satellite synthesis problem is addressed: communication satellites are to be allotted positions on the geostationary arc so that interference does not exceed a given acceptable level by enforcing conservative pairwise satellite separation. A desired location is specified for each satellite, and the objective is to minimize the sum of the deviations between the satellites' prescribed and desired locations. Two mixed integer programming models for the satellite synthesis problem are presented. Four solution strategies, branch-and-bound, Benders' decomposition, linear programming with restricted basis entry, and a switching heuristic, are used to find solutions to example synthesis problems. Computational results indicate the switching algorithm yields solutions of good quality in reasonable execution times when compared to the other solution methods. It is demonstrated that the switching algorithm can be applied to synthesis problems with the objective of minimizing the largest deviation between a prescribed location and the corresponding desired location. Furthermore, it is shown that the switching heuristic can use no conservative, location-dependent satellite separations in order to satisfy interference criteria.

Assessment of the improvements in accuracy of aerosol characterization resulted from additions of polarimetric measurements to intensity-only observations using GRASP algorithm (Invited)

NASA Astrophysics Data System (ADS)

Dubovik, O.; Litvinov, P.; Lapyonok, T.; Herman, M.; Fedorenko, A.; Lopatin, A.; Goloub, P.; Ducos, F.; Aspetsberger, M.; Planer, W.; Federspiel, C.

2013-12-01

During last few years we were developing GRASP (Generalized Retrieval of Aerosol and Surface Properties) algorithm designed for the enhanced characterization of aerosol properties from spectral, multi-angular polarimetric remote sensing observations. The concept of GRASP essentially relies on the accumulated positive research heritage from previous remote sensing aerosol retrieval developments, in particular those from the AERONET and POLDER retrieval activities. The details of the algorithm are described by Dubovik et al. (Atmos. Meas. Tech., 4, 975-1018, 2011). The GRASP retrieves properties of both aerosol and land surface reflectance in cloud-free environments. It is based on highly advanced statistically optimized fitting and deduces nearly 50 unknowns for each observed site. The algorithm derives a similar set of aerosol parameters as AERONET including detailed particle size distribution, the spectrally dependent the complex index of refraction and the fraction of non-spherical particles. The algorithm uses detailed aerosol and surface models and fully accounts for all multiple interactions of scattered solar light with aerosol, gases and the underlying surface. All calculations are done on-line without using traditional look-up tables. In addition, the algorithm uses the new multi-pixel retrieval concept - a simultaneous fitting of a large group of pixels with additional constraints limiting the time variability of surface properties and spatial variability of aerosol properties. This principle is expected to result in higher consistency and accuracy of aerosol products compare to conventional approaches especially over bright surfaces where information content of satellite observations in respect to aerosol properties is limited. The GRASP is a highly versatile algorithm that allows input from both satellite and ground-based measurements. It also has essential flexibility in measurement processing. For example, if observation data set includes spectral measurements of both total intensity and polarization, the algorithm can be easily set to use either total intensity or polarization, as well as both of them in the same retrieval. Using this feature of the algorithm design we have studied the relative importance of total intensity and polarization measurements for retrieving different parameters of aerosol. In this presentation, we present the quantitative assessment of the improvements in aerosol retrievals associated with additions of polarimetric measurements to the intensity-only observations. The study has been performed using satellite measurements by POLDER/PARASOL polarimeter and ground-based measurements by new generation AERONET sun/sky-radiometers implementing measurements of polarization at each spectral channel.

Characterization of Properties of Earth Atmosphere from Multi-Angular Polarimetric Observations of Polder/Parasol Using GRASP Algorithm

NASA Astrophysics Data System (ADS)

Dubovik, O.; Litvinov, P.; Lapyonok, T.; Ducos, F.; Fuertes, D.; Huang, X.; Torres, B.; Aspetsberger, M.; Federspiel, C.

2014-12-01

The POLDER imager on board of the PARASOL micro-satellite is the only satellite polarimeter provided ~ 9 years extensive record of detailed polarmertic observations of Earth atmosphere from space. POLDER / PARASOL registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. Such observations have very high sensitivity to the variability of the properties of atmosphere and underlying surface and can not be adequately interpreted using look-up-table retrieval algorithms developed for analyzing mono-viewing intensity only observations traditionally used in atmospheric remote sensing. Therefore, a new enhanced retrieval algorithm GRASP (Generalized Retrieval of Aerosol and Surface Properties) has been developed and applied for processing of PARASOL data. GRASP relies on highly optimized statistical fitting of observations and derives large number of unknowns for each observed pixel. The algorithm uses elaborated model of the atmosphere and fully accounts for all multiple interactions of scattered solar light with aerosol, gases and the underlying surface. All calculations are implemented during inversion and no look-up tables are used. The algorithm is very flexible in utilization of various types of a priori constraints on the retrieved characteristics and in parameterization of surface - atmosphere system. It is also optimized for high performance calculations. The results of the PARASOL data processing will be presented with the emphasis on the discussion of transferability and adaptability of the developed retrieval concept for processing polarimetric observations of other planets. For example, flexibility and possible alternative in modeling properties of aerosol polydisperse mixtures, particle composition and shape, reflectance of surface, etc. will be discussed.

Assessment, Validation, and Refinement of the Atmospheric Correction Algorithm for the Ocean Color Sensors. Chapter 19

NASA Technical Reports Server (NTRS)

Wang, Menghua

2003-01-01

The primary focus of this proposed research is for the atmospheric correction algorithm evaluation and development and satellite sensor calibration and characterization. It is well known that the atmospheric correction, which removes more than 90% of sensor-measured signals contributed from atmosphere in the visible, is the key procedure in the ocean color remote sensing (Gordon and Wang, 1994). The accuracy and effectiveness of the atmospheric correction directly affect the remotely retrieved ocean bio-optical products. On the other hand, for ocean color remote sensing, in order to obtain the required accuracy in the derived water-leaving signals from satellite measurements, an on-orbit vicarious calibration of the whole system, i.e., sensor and algorithms, is necessary. In addition, it is important to address issues of (i) cross-calibration of two or more sensors and (ii) in-orbit vicarious calibration of the sensor-atmosphere system. The goal of these researches is to develop methods for meaningful comparison and possible merging of data products from multiple ocean color missions. In the past year, much efforts have been on (a) understanding and correcting the artifacts appeared in the SeaWiFS-derived ocean and atmospheric produces; (b) developing an efficient method in generating the SeaWiFS aerosol lookup tables, (c) evaluating the effects of calibration error in the near-infrared (NIR) band to the atmospheric correction of the ocean color remote sensors, (d) comparing the aerosol correction algorithm using the singlescattering epsilon (the current SeaWiFS algorithm) vs. the multiple-scattering epsilon method, and (e) continuing on activities for the International Ocean-Color Coordinating Group (IOCCG) atmospheric correction working group. In this report, I will briefly present and discuss these and some other research activities.

Precise locating approach of the beacon based on gray gradient segmentation interpolation in satellite optical communications.

PubMed

Wang, Qiang; Liu, Yuefei; Chen, Yiqiang; Ma, Jing; Tan, Liying; Yu, Siyuan

2017-03-01

Accurate location computation for a beacon is an important factor of the reliability of satellite optical communications. However, location precision is generally limited by the resolution of CCD. How to improve the location precision of a beacon is an important and urgent issue. In this paper, we present two precise centroid computation methods for locating a beacon in satellite optical communications. First, in terms of its characteristics, the beacon is divided into several parts according to the gray gradients. Afterward, different numbers of interpolation points and different interpolation methods are applied in the interpolation area; we calculate the centroid position after interpolation and choose the best strategy according to the algorithm. The method is called a "gradient segmentation interpolation approach," or simply, a GSI (gradient segmentation interpolation) algorithm. To take full advantage of the pixels of the beacon's central portion, we also present an improved segmentation square weighting (SSW) algorithm, whose effectiveness is verified by the simulation experiment. Finally, an experiment is established to verify GSI and SSW algorithms. The results indicate that GSI and SSW algorithms can improve locating accuracy over that calculated by a traditional gray centroid method. These approaches help to greatly improve the location precision for a beacon in satellite optical communications.

Downscaled soil moisture from SMAP evaluated using high density observations

USDA-ARS?s Scientific Manuscript database

Recently, a soil moisture downscaling algorithm based on a regression relationship between daily temperature changes and daily average soil moisture was developed to produce an enhanced spatial resolution on soil moisture product for the Advanced Microwave Scanning Radiometer–EOS (AMSR-E) satellite ...

Spatiotemporal chlorophyll-a dynamics on the Louisiana continental shelf derived from a dual satellite imagery algorithm

EPA Science Inventory

A monthly time series of remotely sensed chlorophyll-a (Chlars) over the Louisiana continental shelf (LCS) was developed and examined for its relationship to river discharge, nitrate concentration, total phosphorus concentration, photosynthetically available radiation (PAR), wind...

Ground Simulation of an Autonomous Satellite Rendezvous and Tracking System Using Dual Robotic Systems

NASA Technical Reports Server (NTRS)

Trube, Matthew J.; Hyslop, Andrew M.; Carignan, Craig R.; Easley, Joseph W.

2012-01-01

A hardware-in-the-loop ground system was developed for simulating a robotic servicer spacecraft tracking a target satellite at short range. A relative navigation sensor package "Argon" is mounted on the end-effector of a Fanuc 430 manipulator, which functions as the base platform of the robotic spacecraft servicer. Machine vision algorithms estimate the pose of the target spacecraft, mounted on a Rotopod R-2000 platform, relay the solution to a simulation of the servicer spacecraft running in "Freespace", which performs guidance, navigation and control functions, integrates dynamics, and issues motion commands to a Fanuc platform controller so that it tracks the simulated servicer spacecraft. Results will be reviewed for several satellite motion scenarios at different ranges. Key words: robotics, satellite, servicing, guidance, navigation, tracking, control, docking.

Processing of DMSP magnetic data: Handbook of programs, tapes, and datasets

NASA Technical Reports Server (NTRS)

Langel, R. A.; Sabaka, T. J.; Ridgway, J. R.

1990-01-01

The DMSP F-7 satellite was an operational Air Force meteorological satellite which carried a magnetometer for geophysical measurements. The magnetometer was located within the body of the spacecraft in the presence of large spacecraft fields. In addition to stray magnetic fields, the data have inherent position and time inaccuracies. Algorithms were developed to identify and remove time varying magnetic field noise from the data. These algorithms are embodied in an automated procedure which fits a smooth curve through the data and then identifies outliers and which filters the predominant Fourier component of noise from the data. Techniques developed for Magsat were then modified and used to attempt determination of the spacecraft fields, of any rotation between the magnetometer axes and the spacecraft axes, and of any scale changes within the magnetometer itself. Software setup and usage are documented and program listings are included in the Appendix. The initial and resulting data are archived on magnetic cartridge and the formats are documented.

Satellite servicing mission preliminary cost estimation model

NASA Technical Reports Server (NTRS)

1987-01-01

The cost model presented is a preliminary methodology for determining a rough order-of-magnitude cost for implementing a satellite servicing mission. Mission implementation, in this context, encompassess all activities associated with mission design and planning, including both flight and ground crew training and systems integration (payload processing) of servicing hardward with the Shuttle. A basic assumption made in developing this cost model is that a generic set of servicing hardware was developed and flight tested, is inventoried, and is maintained by NASA. This implies that all hardware physical and functional interfaces are well known and therefore recurring CITE testing is not required. The development of the cost model algorithms and examples of their use are discussed.

GPS navigation algorithms for Autonomous Airborne Refueling of Unmanned Air Vehicles

NASA Astrophysics Data System (ADS)

Khanafseh, Samer Mahmoud

Unmanned Air Vehicles (UAVs) have recently generated great interest because of their potential to perform hazardous missions without risking loss of life. If autonomous airborne refueling is possible for UAVs, mission range and endurance will be greatly enhanced. However, concerns about UAV-tanker proximity, dynamic mobility and safety demand that the relative navigation system meets stringent requirements on accuracy, integrity, and continuity. In response, this research focuses on developing high-performance GPS-based navigation architectures for Autonomous Airborne Refueling (AAR) of UAVs. The AAR mission is unique because of the potentially severe sky blockage introduced by the tanker. To address this issue, a high-fidelity dynamic sky blockage model was developed and experimentally validated. In addition, robust carrier phase differential GPS navigation algorithms were derived, including a new method for high-integrity reacquisition of carrier cycle ambiguities for recently-blocked satellites. In order to evaluate navigation performance, world-wide global availability and sensitivity covariance analyses were conducted. The new navigation algorithms were shown to be sufficient for turn-free scenarios, but improvement in performance was necessary to meet the difficult requirements for a general refueling mission with banked turns. Therefore, several innovative methods were pursued to enhance navigation performance. First, a new theoretical approach was developed to quantify the position-domain integrity risk in cycle ambiguity resolution problems. A mechanism to implement this method with partially-fixed cycle ambiguity vectors was derived, and it was used to define tight upper bounds on AAR navigation integrity risk. A second method, where a new algorithm for optimal fusion of measurements from multiple antennas was developed, was used to improve satellite coverage in poor visibility environments such as in AAR. Finally, methods for using data-link extracted measurements as an additional inter-vehicle ranging measurement were also introduced. The algorithms and methods developed in this work are generally applicable to realize high-performance GPS-based navigation in partially obstructed environments. Navigation performance for AAR was quantified through covariance analysis, and it was shown that the stringent navigation requirements for this application are achievable. Finally, a real-time implementation of the algorithms was developed and successfully validated in autopiloted flight tests.

Geostationary Lightning Mapper for GOES-R and Beyond

NASA Technical Reports Server (NTRS)

Goodman, Steven J.; Blakeslee, R. J.; Koshak, W.

2008-01-01

The Geostationary Lightning Mapper (GLM) is a single channel, near-IR imager/optical transient event detector, used to detect, locate and measure total lightning activity over the full-disk as part of a 3-axis stabilized, geostationary weather satellite system. The next generation NOAA Geostationary Operational Environmental Satellite (GOES-R) series with a planned launch readiness in December 2014 will carry a GLM that will provide continuous day and night observations of lightning from the west coast of Africa (GOES-E) to New Zealand (GOES-W) when the constellation is fUlly operational. The mission objectives for the GLM are to 1) provide continuous, full-disk lightning measurements for storm warning and nowcasting, 2) provide early warning of tornadic activity, and 3) accumulate a long-term database to track decadal changes of lightning. The GLM owes its heritage to the NASA Lightning Imaging Sensor (1997-Present) and the Optical Transient Detector (1995-2000), which were developed for the Earth Observing System and have produced a combined 13 year data record of global lightning activity. Instrument formulation studies were completed in March 2007 and the implementation phase to develop a prototype model and up to four flight models will be underway in the latter part of 2007. In parallel with the instrument development, a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms and applications. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds (e.g., Lightning Mapping Arrays in North Alabama and the Washington DC Metropolitan area) are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. Real time lightning mapping data are being provided in an experimental mode to selected National Weather Service (NWS) forecast offices in Southern and Eastern Region. This effort is designed to help improve our understanding of the application of these data in operational settings.

Operational algorithm development and refinement approaches

NASA Astrophysics Data System (ADS)

Ardanuy, Philip E.

2003-11-01

Next-generation polar and geostationary systems, such as the National Polar-orbiting Operational Environmental Satellite System (NPOESS) and the Geostationary Operational Environmental Satellite (GOES)-R, will deploy new generations of electro-optical reflective and emissive capabilities. These will include low-radiometric-noise, improved spatial resolution multi-spectral and hyperspectral imagers and sounders. To achieve specified performances (e.g., measurement accuracy, precision, uncertainty, and stability), and best utilize the advanced space-borne sensing capabilities, a new generation of retrieval algorithms will be implemented. In most cases, these advanced algorithms benefit from ongoing testing and validation using heritage research mission algorithms and data [e.g., the Earth Observing System (EOS)] Moderate-resolution Imaging Spectroradiometer (MODIS) and Shuttle Ozone Limb Scattering Experiment (SOLSE)/Limb Ozone Retreival Experiment (LORE). In these instances, an algorithm's theoretical basis is not static, but rather improves with time. Once frozen, an operational algorithm can "lose ground" relative to research analogs. Cost/benefit analyses provide a basis for change management. The challenge is in reconciling and balancing the stability, and "comfort," that today"s generation of operational platforms provide (well-characterized, known, sensors and algorithms) with the greatly improved quality, opportunities, and risks, that the next generation of operational sensors and algorithms offer. By using the best practices and lessons learned from heritage/groundbreaking activities, it is possible to implement an agile process that enables change, while managing change. This approach combines a "known-risk" frozen baseline with preset completion schedules with insertion opportunities for algorithm advances as ongoing validation activities identify and repair areas of weak performance. This paper describes an objective, adaptive implementation roadmap that takes into account the specific maturities of each system"s (sensor and algorithm) technology to provide for a program that contains continuous improvement while retaining its manageability.

NASA/GSFC Research Activities for the Global Ocean Carbon Cycle: A Prospectus for the 21st Century

NASA Technical Reports Server (NTRS)

Gregg, W. W.; Behrenfield, M. J.; Hoge, F. E.; Esaias, W. E.; Huang, N. E.; Long, S. R.; McClain, C. R.

2000-01-01

There are increasing concerns that anthropogenic inputs of carbon dioxide into the Earth system have the potential for climate change. In response to these concerns, the GSFC Laboratory for Hydrospheric Processes has formed the Ocean Carbon Science Team (OCST) to contribute to greater understanding of the global ocean carbon cycle. The overall goals of the OCST are to: 1) detect changes in biological components of the ocean carbon cycle through remote sensing of biooptical properties, 2) refine understanding of ocean carbon uptake and sequestration through application of basic research results, new satellite algorithms, and improved model parameterizations, 3) develop and implement new sensors providing critical missing environmental information related to the oceanic carbon cycle and the flux of CO2 across the air-sea interface. The specific objectives of the OCST are to: 1) establish a 20-year time series of ocean color, 2) develop new remote sensing technologies, 3) validate ocean remote sensing observations, 4) conduct ocean carbon cycle scientific investigations directly related to remote sensing data, emphasizing physiological, empirical and coupled physical/biological models, satellite algorithm development and improvement, and analysis of satellite data sets. These research and mission objectives are intended to improve our understanding of global ocean carbon cycling and contribute to national goals by maximizing the use of remote sensing data.

Consistent satellite XCO 2 retrievals from SCIAMACHY and GOSAT using the BESD algorithm

DOE PAGES

Heymann, J.; Reuter, M.; Hilker, M.; ...

2015-02-13

Consistent and accurate long-term data sets of global atmospheric concentrations of carbon dioxide (CO 2) are required for carbon cycle and climate related research. However, global data sets based on satellite observations may suffer from inconsistencies originating from the use of products derived from different satellites as needed to cover a long enough time period. One reason for inconsistencies can be the use of different retrieval algorithms. We address this potential issue by applying the same algorithm, the Bremen Optimal Estimation DOAS (BESD) algorithm, to different satellite instruments, SCIAMACHY on-board ENVISAT (March 2002–April 2012) and TANSO-FTS on-board GOSAT (launched inmore » January 2009), to retrieve XCO 2, the column-averaged dry-air mole fraction of CO 2. BESD has been initially developed for SCIAMACHY XCO 2 retrievals. Here, we present the first detailed assessment of the new GOSAT BESD XCO 2 product. GOSAT BESD XCO 2 is a product generated and delivered to the MACC project for assimilation into ECMWF's Integrated Forecasting System (IFS). We describe the modifications of the BESD algorithm needed in order to retrieve XCO 2 from GOSAT and present detailed comparisons with ground-based observations of XCO 2 from the Total Carbon Column Observing Network (TCCON). We discuss detailed comparison results between all three XCO 2 data sets (SCIAMACHY, GOSAT and TCCON). The comparison results demonstrate the good consistency between the SCIAMACHY and the GOSAT XCO 2. For example, we found a mean difference for daily averages of −0.60 ± 1.56 ppm (mean difference ± standard deviation) for GOSAT-SCIAMACHY (linear correlation coefficient r = 0.82), −0.34 ± 1.37 ppm ( r = 0.86) for GOSAT-TCCON and 0.10 ± 1.79 ppm ( r = 0.75) for SCIAMACHY-TCCON. The remaining differences between GOSAT and SCIAMACHY are likely due to non-perfect collocation (±2 h, 10° × 10° around TCCON sites), i.e., the observed air masses are not exactly identical, but likely also due to a still non-perfect BESD retrieval algorithm, which will be continuously improved in the future. Our overarching goal is to generate a satellite-derived XCO 2 data set appropriate for climate and carbon cycle research covering the longest possible time period. We therefore also plan to extend the existing SCIAMACHY and GOSAT data set discussed here by using also data from other missions (e.g., OCO-2, GOSAT-2, CarbonSat) in the future.« less

The Importance of Measurement Errors for Deriving Accurate Reference Leaf Area Index Maps for Validation of Moderate-Resolution Satellite LAI Products

NASA Technical Reports Server (NTRS)

Huang, Dong; Yang, Wenze; Tan, Bin; Rautiainen, Miina; Zhang, Ping; Hu, Jiannan; Shabanov, Nikolay V.; Linder, Sune; Knyazikhin, Yuri; Myneni, Ranga B.

2006-01-01

The validation of moderate-resolution satellite leaf area index (LAI) products such as those operationally generated from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor data requires reference LAI maps developed from field LAI measurements and fine-resolution satellite data. Errors in field measurements and satellite data determine the accuracy of the reference LAI maps. This paper describes a method by which reference maps of known accuracy can be generated with knowledge of errors in fine-resolution satellite data. The method is demonstrated with data from an international field campaign in a boreal coniferous forest in northern Sweden, and Enhanced Thematic Mapper Plus images. The reference LAI map thus generated is used to assess modifications to the MODIS LAI/fPAR algorithm recently implemented to derive the next generation of the MODIS LAI/fPAR product for this important biome type.

Investigation of cloud/water vapor motion winds from geostationary satellite

NASA Technical Reports Server (NTRS)

Nieman, Steve; Velden, Chris; Hayden, Kit; Menzel, Paul

1993-01-01

Work has been primarily focussed on three tasks: (1) comparison of wind fields produced at MSFC with the CO2 autowind/autoeditor system newly installed in NESDIS operations; (2) evaluation of techniques for improved tracer selection through use of cloud classification predictors; and (3) development of height assignment algorithm with water vapor channel radiances. The contract goal is to improve the CIMSS wind system by developing new techniques and assimilating better existing techniques. The work reported here was done in collaboration with the NESDIS scientists working on the operational winds software, so that NASA funded research can benefit NESDIS operational algorithms.

Automated tracking for advanced satellite laser ranging systems

NASA Astrophysics Data System (ADS)

McGarry, Jan F.; Degnan, John J.; Titterton, Paul J., Sr.; Sweeney, Harold E.; Conklin, Brion P.; Dunn, Peter J.

1996-06-01

NASA's Satellite Laser Ranging Network was originally developed during the 1970's to track satellites carrying corner cube reflectors. Today eight NASA systems, achieving millimeter ranging precision, are part of a global network of more than 40 stations that track 17 international satellites. To meet the tracking demands of a steadily growing satellite constellation within existing resources, NASA is embarking on a major automation program. While manpower on the current systems will be reduced to a single operator, the fully automated SLR2000 system is being designed to operate for months without human intervention. Because SLR2000 must be eyesafe and operate in daylight, tracking is often performed in a low probability of detection and high noise environment. The goal is to automatically select the satellite, setup the tracking and ranging hardware, verify acquisition, and close the tracking loop to optimize data yield. TO accomplish the autotracking tasks, we are investigating (1) improved satellite force models, (2) more frequent updates of orbital ephemerides, (3) lunar laser ranging data processing techniques to distinguish satellite returns from noise, and (4) angular detection and search techniques to acquire the satellite. A Monte Carlo simulator has been developed to allow optimization of the autotracking algorithms by modeling the relevant system errors and then checking performance against system truth. A combination of simulator and preliminary field results will be presented.

Deep Blue Retrievals of Asian Aerosol Properties During ACE-Asia

NASA Technical Reports Server (NTRS)

Hsu, N. Christina; Tsay, Si-Cee; King, Michael D.; Herman, Jay R.

2006-01-01

During the ACE-Asia field campaign, unprecedented amounts of aerosol property data in East Asia during springtime were collected from an array of aircraft, shipboard, and surface instruments. However, most of the observations were obtained in areas downwind of the source regions. In this paper, the newly developed satellite aerosol algorithm called "Deep Blue" was employed to characterize the properties of aerosols over source regions using radiance measurements from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS). Based upon the ngstr m exponent derived from the Deep Blue algorithm, it was demonstrated that this new algorithm is able to distinguish dust plumes from fine-mode pollution particles even in complex aerosol environments such as the one over Beijing. Furthermore, these results were validated by comparing them with observations from AERONET sites in China and Mongolia during spring 2001. These comparisons show that the values of satellite-retrieved aerosol optical thickness from Deep Blue are generally within 20%-30% of those measured by sunphotometers. The analyses also indicate that the roles of mineral dust and anthropogenic particles are comparable in contributing to the overall aerosol distributions during spring in northern China, while fine-mode particles are dominant over southern China. The spring season in East Asia consists of one of the most complex environments in terms of frequent cloudiness and wide ranges of aerosol loadings and types. This paper will discuss how the factors contributing to this complexity influence the resulting aerosol monthly averages from various satellite sensors and, thus, the synergy among satellite aerosol products.

Reusing Joint Polar Satellite System (jpss) Ground System Components to Process AURA Ozone Monitoring Instrument (omi) Science Products

NASA Astrophysics Data System (ADS)

Moses, J. F.; Jain, P.; Johnson, J.; Doiron, J. A.

2017-12-01

New Earth observation instruments are planned to enable advancements in Earth science research over the next decade. Diversity of Earth observing instruments and their observing platforms will continue to increase as new instrument technologies emerge and are deployed as part of National programs such as Joint Polar Satellite System (JPSS), Geostationary Operational Environmental Satellite system (GOES), Landsat as well as the potential for many CubeSat and aircraft missions. The practical use and value of these observational data often extends well beyond their original purpose. The practicing community needs intuitive and standardized tools to enable quick unfettered development of tailored products for specific applications and decision support systems. However, the associated data processing system can take years to develop and requires inherent knowledge and the ability to integrate increasingly diverse data types from multiple sources. This paper describes the adaptation of a large-scale data processing system built for supporting JPSS algorithm calibration and validation (Cal/Val) node to a simplified science data system for rapid application. The new configurable data system reuses scalable JAVA technologies built for the JPSS Government Resource for Algorithm Verification, Independent Test, and Evaluation (GRAVITE) system to run within a laptop environment and support product generation and data processing of AURA Ozone Monitoring Instrument (OMI) science products. Of particular interest are the root requirements necessary for integrating experimental algorithms and Hierarchical Data Format (HDF) data access libraries into a science data production system. This study demonstrates the ability to reuse existing Ground System technologies to support future missions with minimal changes.

Using Remotely Sensed Information for Near Real-Time Landslide Hazard Assessment

NASA Technical Reports Server (NTRS)

Kirschbaum, Dalia; Adler, Robert; Peters-Lidard, Christa

2013-01-01

The increasing availability of remotely sensed precipitation and surface products provides a unique opportunity to explore how landslide susceptibility and hazard assessment may be approached at larger spatial scales with higher resolution remote sensing products. A prototype global landslide hazard assessment framework has been developed to evaluate how landslide susceptibility and satellite-derived precipitation estimates can be used to identify potential landslide conditions in near-real time. Preliminary analysis of this algorithm suggests that forecasting errors are geographically variable due to the resolution and accuracy of the current susceptibility map and the application of satellite-based rainfall estimates. This research is currently working to improve the algorithm through considering higher spatial and temporal resolution landslide susceptibility information and testing different rainfall triggering thresholds, antecedent rainfall scenarios, and various surface products at regional and global scales.

Application of side-oblique image-motion blur correction to Kuaizhou-1 agile optical images.

PubMed

Sun, Tao; Long, Hui; Liu, Bao-Cheng; Li, Ying

2016-03-21

Given the recent development of agile optical satellites for rapid-response land observation, side-oblique image-motion (SOIM) detection and blur correction have become increasingly essential for improving the radiometric quality of side-oblique images. The Chinese small-scale agile mapping satellite Kuaizhou-1 (KZ-1) was developed by the Harbin Institute of Technology and launched for multiple emergency applications. Like other agile satellites, KZ-1 suffers from SOIM blur, particularly in captured images with large side-oblique angles. SOIM detection and blur correction are critical for improving the image radiometric accuracy. This study proposes a SOIM restoration method based on segmental point spread function detection. The segment region width is determined by satellite parameters such as speed, height, integration time, and side-oblique angle. The corresponding algorithms and a matrix form are proposed for SOIM blur correction. Radiometric objective evaluation indices are used to assess the restoration quality. Beijing regional images from KZ-1 are used as experimental data. The radiometric quality is found to increase greatly after SOIM correction. Thus, the proposed method effectively corrects image motion for KZ-1 agile optical satellites.

Evaluation of a moderate resolution, satellite-based impervious surface map using an independent, high-resolution validation data set

USGS Publications Warehouse

Jones, J.W.; Jarnagin, T.

2009-01-01

Given the relatively high cost of mapping impervious surfaces at regional scales, substantial effort is being expended in the development of moderate-resolution, satellite-based methods for estimating impervious surface area (ISA). To rigorously assess the accuracy of these data products high quality, independently derived validation data are needed. High-resolution data were collected across a gradient of development within the Mid-Atlantic region to assess the accuracy of National Land Cover Data (NLCD) Landsat-based ISA estimates. Absolute error (satellite predicted area - "reference area") and relative error [satellite (predicted area - "reference area")/ "reference area"] were calculated for each of 240 sample regions that are each more than 15 Landsat pixels on a side. The ability to compile and examine ancillary data in a geographic information system environment provided for evaluation of both validation and NLCD data and afforded efficient exploration of observed errors. In a minority of cases, errors could be explained by temporal discontinuities between the date of satellite image capture and validation source data in rapidly changing places. In others, errors were created by vegetation cover over impervious surfaces and by other factors that bias the satellite processing algorithms. On average in the Mid-Atlantic region, the NLCD product underestimates ISA by approximately 5%. While the error range varies between 2 and 8%, this underestimation occurs regardless of development intensity. Through such analyses the errors, strengths, and weaknesses of particular satellite products can be explored to suggest appropriate uses for regional, satellite-based data in rapidly developing areas of environmental significance. ?? 2009 ASCE.

Effect of Ionosphere on Geostationary Communication Satellite Signals

NASA Astrophysics Data System (ADS)

Erdem, Esra; Arikan, Feza; Gulgonul, Senol

2016-07-01

Geostationary orbit (GEO) communications satellites allow radio, television, and telephone transmissions to be sent live anywhere in the world. They are extremely important in daily life and also for military applications. Since, satellite communication is an expensive technology addressing crowd of people, it is critical to improve the performance of this technology. GEO satellites are at 35,786 kilometres from Earth's surface situated directly over the equator. A satellite in a geostationary orbit (GEO) appears to stand still in the sky, in a fixed position with respect to an observer on the earth, because the satellite's orbital period is the same as the rotation rate of the Earth. The advantage of this orbit is that ground antennas can be fixed to point towards to satellite without their having to track the satellite's motion. Radio frequency ranges used in satellite communications are C, X, Ku, Ka and even EHG and V-band. Satellite signals are disturbed by atmospheric effects on the path between the satellite and the receiver antenna. These effects are mostly rain, cloud and gaseous attenuation. It is expected that ionosphere has a minor effect on the satellite signals when the ionosphere is quiet. But there are anomalies and perturbations on the structure of ionosphere with respect to geomagnetic field and solar activity and these conditions may cause further affects on the satellite signals. In this study IONOLAB-RAY algorithm is adopted to examine the effect of ionosphere on satellite signals. IONOLAB-RAY is developed to calculate propagation path and characteristics of high frequency signals. The algorithm does not have any frequency limitation and models the plasmasphere up to 20,200 km altitude, so that propagation between a GEO satellite and antenna on Earth can be simulated. The algorithm models inhomogeneous, anisotropic and time dependent structure of the ionosphere with a 3-D spherical grid geometry and calculates physical parameters of the ionosphere using IRI-Plas-G software. One of the outstanding features of IONOLAB-RAY is the opportunity of Global Ionospheric Map-Total Electron Content (GIM-TEC) assimilation. This feature enables more realistic representation of ionosphere, especially for the times when ionosphere deviates from the generalized models, such as during geomagnetic storms. This feature is critical to examine the effect of ionosphere on satellite signals under ionospheric storm conditions. In this study TURKSAT satellite data is used to compare the results of IONOLAB-RAY and evaluate the effect of ionosphere. TURKSAT is one of the world's leading companies providing all sorts of satellite communications through the satellites of TURKSAT as well as the other satellites. Providing services for voice, data, internet, TV, and radio broadcasting through the satellites across a wide area extending from Europe to Asia. The latest satellite of TURKSAT, namely Turksat 4B was launched on October 2015, before that various versions of TURKSAT satellites are launched since 1994. In the future enlargement of broadcasting area towards equatorial region is aimed, where the ionospheric anomalies and storms are highly expected. In the future this study can be applied to the satellite signals in equatorial regions and effects of ionosphere especially under storm conditions can be discussed. This study is supported by TUBITAK 114E541, 115E915 and Joint TUBITAK 114E092 and AS CR 14/001 projects.

The Breakthrough Listen Search for Intelligent Life: Radio Frequency Interference in the Green Bank Telescope

NASA Astrophysics Data System (ADS)

Dana, Ryan

2018-01-01

In the search for extra terrestrial intelligence, the vast majority of our “signals of interest,” are simply satellite radio frequency interference. The goal to my research, therefore, was to accurately predict the exact locations of satellites in our sky to analyze specific satellites causing the interference as well as potentially predict when satellites will cross in the way of our beams so that we can further optimize our scripts and get more usable data.I have built an algorithm that plots the exact location in altitude and azimuth of any grouping of satellites that you want in the sky from any position on earth in latitude, longitude, and elevation. From there, you can input a specific right ascension and declination of the location you are trying to track in the sky with a telescope. Using these inputs, we can calculate the angular and positional distance of certain satellites to our beam to further analyze satellite radio frequency interference.The process begins by importing a list of Two Line Element information that the algorithm reads in. Two Line Elements are how Satellites are organized and are updated frequently. They give a variety of information ranging from the Satellite ID to its Mean Motion or anomaly. From there, the code breaks up the information given by these elements to predict their location. The algorithm can also plot in 3D coordinates around an earthlike sphere to conceptualize the route that each Satellite has taken.The code has been used in a variety of ways but most notably to identify satellites interfering with the beam for Arecibo’s Ross 128 Candidate signal. From here, the code will be the backbone to calculating drift rates, Doppler shifts and intensity of certain satellites and why our team consistently receives estranged satellite signals of interest. Furthermore, in the case of a serious candidate signal in the near future, it will be important to analyze satellites interfering in the beam.

Using the Multiplicative Schwarz Alternating Algorithm (MSAA) for Solving the Large Linear System of Equations Related to Global Gravity Field Recovery up to Degree and Order 120

NASA Astrophysics Data System (ADS)

Safari, A.; Sharifi, M. A.; Amjadiparvar, B.

2010-05-01

The GRACE mission has substantiated the low-low satellite-to-satellite tracking (LL-SST) concept. The LL-SST configuration can be combined with the previously realized high-low SST concept in the CHAMP mission to provide a much higher accuracy. The line of sight (LOS) acceleration difference between the GRACE satellite pair is the mostly used observable for mapping the global gravity field of the Earth in terms of spherical harmonic coefficients. In this paper, mathematical formulae for LOS acceleration difference observations have been derived and the corresponding linear system of equations has been set up for spherical harmonic up to degree and order 120. The total number of unknowns is 14641. Such a linear equation system can be solved with iterative solvers or direct solvers. However, the runtime of direct methods or that of iterative solvers without a suitable preconditioner increases tremendously. This is the reason why we need a more sophisticated method to solve the linear system of problems with a large number of unknowns. Multiplicative variant of the Schwarz alternating algorithm is a domain decomposition method, which allows it to split the normal matrix of the system into several smaller overlaped submatrices. In each iteration step the multiplicative variant of the Schwarz alternating algorithm solves linear systems with the matrices obtained from the splitting successively. It reduces both runtime and memory requirements drastically. In this paper we propose the Multiplicative Schwarz Alternating Algorithm (MSAA) for solving the large linear system of gravity field recovery. The proposed algorithm has been tested on the International Association of Geodesy (IAG)-simulated data of the GRACE mission. The achieved results indicate the validity and efficiency of the proposed algorithm in solving the linear system of equations from accuracy and runtime points of view. Keywords: Gravity field recovery, Multiplicative Schwarz Alternating Algorithm, Low-Low Satellite-to-Satellite Tracking

GLAS Spacecraft Pointing Study

NASA Technical Reports Server (NTRS)

Born, George H.; Gold, Kenn; Ondrey, Michael; Kubitschek, Dan; Axelrad, Penina; Komjathy, Attila

1998-01-01

Science requirements for the GLAS mission demand that the laser altimeter be pointed to within 50 m of the location of the previous repeat ground track. The satellite will be flown in a repeat orbit of 182 days. Operationally, the required pointing information will be determined on the ground using the nominal ground track, to which pointing is desired, and the current propagated orbit of the satellite as inputs to the roll computation algorithm developed by CCAR. The roll profile will be used to generate a set of fit coefficients which can be uploaded on a daily basis and used by the on-board attitude control system. In addition, an algorithm has been developed for computation of the associated command quaternions which will be necessary when pointing at targets of opportunity. It may be desirable in the future to perform the roll calculation in an autonomous real-time mode on-board the spacecraft. GPS can provide near real-time tracking of the satellite, and the nominal ground track can be stored in the on-board computer. It will be necessary to choose the spacing of this nominal ground track to meet storage requirements in the on-board environment. Several methods for generating the roll profile from a sparse reference ground track are presented.

Numerical arc segmentation algorithm for a radio conference: A software tool for communication satellite systems planning

NASA Technical Reports Server (NTRS)

Whyte, W. A.; Heyward, A. O.; Ponchak, D. S.; Spence, R. L.; Zuzek, J. E.

1988-01-01

The Numerical Arc Segmentation Algorithm for a Radio Conference (NASARC) provides a method of generating predetermined arc segments for use in the development of an allotment planning procedure to be carried out at the 1988 World Administrative Radio Conference (WARC) on the Use of the Geostationary Satellite Orbit and the Planning of Space Services Utilizing It. Through careful selection of the predetermined arc (PDA) for each administration, flexibility can be increased in terms of choice of system technical characteristics and specific orbit location while reducing the need for coordination among administrations. The NASARC software determines pairwise compatibility between all possible service areas at discrete arc locations. NASARC then exhaustively enumerates groups of administrations whose satellites can be closely located in orbit, and finds the arc segment over which each such compatible group exists. From the set of all possible compatible groupings, groups and their associated arc segments are selected using a heuristic procedure such that a PDA is identified for each administration. Various aspects of the NASARC concept and how the software accomplishes specific features of allotment planning are discussed.

Fast Emission Estimates in China Constrained by Satellite Observations (Invited)

NASA Astrophysics Data System (ADS)

Mijling, B.; van der A, R.

2013-12-01

Emission inventories of air pollutants are crucial information for policy makers and form important input data for air quality models. Unfortunately, bottom-up emission inventories, compiled from large quantities of statistical data, are easily outdated for an emerging economy such as China, where rapid economic growth changes emissions accordingly. Alternatively, top-down emission estimates from satellite observations of air constituents have important advantages of being spatial consistent, having high temporal resolution, and enabling emission updates shortly after the satellite data become available. Constraining emissions from concentration measurements is, however, computationally challenging. Within the GlobEmission project of the European Space Agency (ESA) a new algorithm has been developed, specifically designed for fast daily emission estimates of short-lived atmospheric species on a mesoscopic scale (0.25 × 0.25 degree) from satellite observations of column concentrations. The algorithm needs only one forward model run from a chemical transport model to calculate the sensitivity of concentration to emission, using trajectory analysis to account for transport away from the source. By using a Kalman filter in the inverse step, optimal use of the a priori knowledge and the newly observed data is made. We apply the algorithm for NOx emission estimates in East China, using the CHIMERE model together with tropospheric NO2 column retrievals of the OMI and GOME-2 satellite instruments. The observations are used to construct a monthly emission time series, which reveal important emission trends such as the emission reduction measures during the Beijing Olympic Games, and the impact and recovery from the global economic crisis. The algorithm is also able to detect emerging sources (e.g. new power plants) and improve emission information for areas where proxy data are not or badly known (e.g. shipping emissions). The new emission estimates result in a better agreement between observations and simulations of air pollutant concentrations, facilitating improved air quality forecasts. The EU project MarcoPolo will combine these emission estimates from space with statistical information on e.g. land use, population density and traffic to construct a new up-to-date emission inventory for China.

Water resource monitoring in Iran using satellite altimetry and satellite gravimetry (GRACE)

NASA Astrophysics Data System (ADS)

Khaki, Mehdi; Sneeuw, Nico

2015-04-01

Human civilization has always been in evolution by having direct access to water resources throughout history. Water, with its qualitative and quantitative effects, plays an important role in economic and social developments. Iran with an arid and semi-arid geographic specification is located in Southwest Asia. Water crisis has appeared in Iran as a serious problem. In this study we're going to use various data sources including satellite radar altimetry and satellite gravimetry to monitor and investigate water resources in Iran. Radar altimeters are an invaluable tool to retrieve from space vital hydrological information such as water level, volume and discharge, in particular from regions where the in situ data collection is difficult. Besides, Gravity Recovery and Climate Experiment (GRACE) provide global high resolution observations of the time variable gravity field of the Earth. This information is used to derive spatio-temporal changes of the terrestrial water storage body. This study isolates the anthropogenic perturbations to available water supplies in order to quantify human water use as compared to available resources. Long-term monitor of water resources in Iran is contain of observing freshwaters, lakes and rivers as well as exploring ground water bodies. For these purposes, several algorithms are developed to quantitatively monitor the water resources in Iran. The algorithms contain preprocessing on datasets, eliminating biases and atmospheric corrections, establishing water level time series and estimating terrestrial water storage considering impacts of biases and leakage on GRACE data. Our primary goal in this effort is to use the combination of satellite radar altimetry and GRACE data to study on water resources as well as methods to dealing with error sources include cross over errors and atmospheric impacts.

Synthetic aperture radar signal data compression using block adaptive quantization

NASA Technical Reports Server (NTRS)

Kuduvalli, Gopinath; Dutkiewicz, Melanie; Cumming, Ian

1994-01-01

This paper describes the design and testing of an on-board SAR signal data compression algorithm for ESA's ENVISAT satellite. The Block Adaptive Quantization (BAQ) algorithm was selected, and optimized for the various operational modes of the ASAR instrument. A flexible BAQ scheme was developed which allows a selection of compression ratio/image quality trade-offs. Test results show the high quality of the SAR images processed from the reconstructed signal data, and the feasibility of on-board implementation using a single ASIC.

Use of Multiangle Satellite Observations to Retrieve Aerosol Properties and Ocean Color

NASA Technical Reports Server (NTRS)

Martonchik, John V.; Diner, David; Khan, Ralph

2005-01-01

A new technique is described for retrieving aerosol over ocean water and the associated ocean color using multiangle satellite observations. Unlike current satellite aerosol retrieval algorithms which only utilize observations at red wavelengths and longer, with the assumption that these wavelengths have a negligible ocean (water-leaving radiance), this new algorithm uses all available spectral bands and simultaneously retrieves both aerosol properties and the spectral ocean color. We show some results of case studies using MISR data, performed over different water conditions (coastal water, blooms, and open water).

Adaptive antenna arrays for satellite communication

NASA Technical Reports Server (NTRS)

Gupta, Inder J.

1989-01-01

The feasibility of using adaptive antenna arrays to provide interference protection in satellite communications was studied. The feedback loops as well as the sample matric inversion (SMI) algorithm for weight control were studied. Appropriate modifications in the two were made to achieve the required interference suppression. An experimental system was built to test the modified feedback loops and the modified SMI algorithm. The performance of the experimental system was evaluated using bench generated signals and signals received from TVRO geosynchronous satellites. A summary of results is given. Some suggestions for future work are also presented.

Determination of cloud parameters from infrared sounder data

NASA Technical Reports Server (NTRS)

Yeh, H.-Y. M.

1984-01-01

The World Climate Research Programme (WCRP) plan is concerned with the need to develop a uniform global cloud climatology as part of a broad research program on climate processes. The International Satellite Cloud Climatology Project (ISCCP) has been approved as the first project of the WCRP. The ISCCP has the basic objective to collect and analyze satellite radiance data to infer the global distribution of cloud radiative properties in order to improve the modeling of cloud effects on climate. Research is conducted to explore an algorithm for retrieving cloud properties by utilizing the available infrared sounder data from polar-orbiting satellites. A numerical method is developed for computing cloud top heights, amount, and emissivity on the basis of a parameterized infrared radiative transfer equation for cloudy atmospheres. Theoretical studies were carried out by considering a synthetic atmosphere.

Post-hurricane forest damage assessment using satellite remote sensing

Treesearch

W. Wang; J.J. Qu; X. Hao; Y. Liu; J.A. Stanturf

2010-01-01

This study developed a rapid assessment algorithm for post-hurricane forest damage estimation using moderate resolution imaging spectroradiometer (MODIS) measurements. The performance of five commonly used vegetation indices as post-hurricane forest damage indicators was investigated through statistical analysis. The Normalized Difference Infrared Index (NDII) was...

An analysis of MODIS algorithms for surface salinity and dissolved organic carbon in northwest Florida estuaries

EPA Science Inventory

Synoptic and frequent monitoring of water quality parameters from satellite is useful for determining the health of aquatic ecosystems and development of effective management strategies. Northwest Florida estuaries are classified as optically-complex, or waters influenced by chlo...

Evaluation of Multiple Kernel Learning Algorithms for Crop Mapping Using Satellite Image Time-Series Data

NASA Astrophysics Data System (ADS)

Niazmardi, S.; Safari, A.; Homayouni, S.

2017-09-01

Crop mapping through classification of Satellite Image Time-Series (SITS) data can provide very valuable information for several agricultural applications, such as crop monitoring, yield estimation, and crop inventory. However, the SITS data classification is not straightforward. Because different images of a SITS data have different levels of information regarding the classification problems. Moreover, the SITS data is a four-dimensional data that cannot be classified using the conventional classification algorithms. To address these issues in this paper, we presented a classification strategy based on Multiple Kernel Learning (MKL) algorithms for SITS data classification. In this strategy, initially different kernels are constructed from different images of the SITS data and then they are combined into a composite kernel using the MKL algorithms. The composite kernel, once constructed, can be used for the classification of the data using the kernel-based classification algorithms. We compared the computational time and the classification performances of the proposed classification strategy using different MKL algorithms for the purpose of crop mapping. The considered MKL algorithms are: MKL-Sum, SimpleMKL, LPMKL and Group-Lasso MKL algorithms. The experimental tests of the proposed strategy on two SITS data sets, acquired by SPOT satellite sensors, showed that this strategy was able to provide better performances when compared to the standard classification algorithm. The results also showed that the optimization method of the used MKL algorithms affects both the computational time and classification accuracy of this strategy.

Uncertainties and applications of satellite-derived coastal water quality products

NASA Astrophysics Data System (ADS)

Zheng, Guangming; DiGiacomo, Paul M.

2017-12-01

Recent and forthcoming launches of a plethora of ocean color radiometry sensors, coupled with increasingly adopted free and open data policies are expected to boost usage of satellite ocean color data and drive the demand to use these data in a quantitative and routine manner. Here we review factors that introduce uncertainties to various satellite-derived water quality products and recommend approaches to minimize the uncertainty of a specific product. We show that the regression relationships between remote-sensing reflectance and water turbidity (in terms of nephelometric units) established for different regions tend to converge and therefore it is plausible to develop a global satellite water turbidity product derived using a single algorithm. In contrast, solutions to derive suspended particulate matter concentration are much less generalizable; in one case it might be more accurate to estimate this parameter based on satellite-derived particulate backscattering coefficient, whereas in another the nonagal particulate absorption coefficient might be a better proxy. Regarding satellite-derived chlorophyll concentration, known to be subject to large uncertainties in coastal waters, studies summarized here clearly indicate that the accuracy of classical reflectance band-ratio algorithms depends largely on the contribution of phytoplankton to total light absorption coefficient as well as the degree of correlation between phytoplankton and the dominant nonalgal contributions. Our review also indicates that currently available satellite-derived water quality products are restricted to optically significant materials, whereas many users are interested in toxins, nutrients, pollutants, and pathogens. Presently, proxies or indicators for these constituents are inconsistently (and often incorrectly) developed and applied. Progress in this general direction will remain slow unless, (i) optical oceanographers and environmental scientists start collaborating more closely and make optical and environmental measurements in parallel, (ii) more efforts are devoted to identifying optical, ecological, and environmental forerunners of autochthonous water quality issues (e.g., onsite growth of pathogens), and, (iii) environmental processes associated with the source, transport, and transformation of allochthonous issues (e.g., transport of nutrients) are better understood. Accompanying these challenges, the need still exists to conduct fundamental research in satellite ocean color radiometry, including development of more robust atmospheric correction methods as well as inverse models for coastal regions where optical properties of both aerosols and hydrosols are complex.

The RadioSat (sm) network

NASA Technical Reports Server (NTRS)

Noreen, Gary K.

1991-01-01

The RadioSat network under development by radio Satellite Corporation will use mobile satellite (MSAT) technology to provide diverse personal communications, broadcast, and navigation services. The network will support these services simultaneously for integrated mobile radios throughout Canada and the United States. The RadioSat network takes advantage of several technological breakthroughs, all coming to fruition by the time the first MSAT satellite is launched in 1994. The most important of these breakthroughs is the enormous radiated power of each MSAT spacecraft - orders of magnitude greater than the radiated power of previous L-band spacecraft. Another important breakthrough is the development of advanced digital audio compression algorithms, enabling the transmission of broadcast quality music at moderate data rates. Finally, continuing dramatic increases in VLSI capabilities permit the production of complex, multi-function mobile satellite radios in very large quantities at prices little more than those of conventional car radios. In addition to performance breakthroughs and their economic implications to RadioSat, the design of the RadioSat network is reviewed.

Satellite-Based Stratospheric and Tropospheric Measurements: Determination of Global Ozone and Other Trace Species

NASA Technical Reports Server (NTRS)

Chance, Kelly

2003-01-01

This grant is an extension to our previous NASA Grant NAG5-3461, providing incremental funding to continue GOME (Global Ozone Monitoring Experiment) and SCIAMACHY (SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY) studies. This report summarizes research done under these grants through December 31, 2002. The research performed during this reporting period includes development and maintenance of scientific software for the GOME retrieval algorithms, consultation on operational software development for GOME, consultation and development for SCIAMACHY near-real-time (NRT) and off-line (OL) data products, and participation in initial SCIAMACHY validation studies. The Global Ozone Monitoring Experiment was successfully launched on the ERS-2 satellite on April 20, 1995, and remains working in normal fashion. SCIAMACHY was launched March 1, 2002 on the ESA Envisat satellite. Three GOME-2 instruments are now scheduled to fly on the Metop series of operational meteorological satellites (Eumetsat). K. Chance is a member of the reconstituted GOME Scientific Advisory Group, which will guide the GOME-2 program as well as the continuing ERS-2 GOME program.

Rainfall assimilation in RAMS by means of the Kuo parameterisation inversion: method and preliminary results

NASA Astrophysics Data System (ADS)

Orlandi, A.; Ortolani, A.; Meneguzzo, F.; Levizzani, V.; Torricella, F.; Turk, F. J.

2004-03-01

In order to improve high-resolution forecasts, a specific method for assimilating rainfall rates into the Regional Atmospheric Modelling System model has been developed. It is based on the inversion of the Kuo convective parameterisation scheme. A nudging technique is applied to 'gently' increase with time the weight of the estimated precipitation in the assimilation process. A rough but manageable technique is explained to estimate the partition of convective precipitation from stratiform one, without requiring any ancillary measurement. The method is general purpose, but it is tuned for geostationary satellite rainfall estimation assimilation. Preliminary results are presented and discussed, both through totally simulated experiments and through experiments assimilating real satellite-based precipitation observations. For every case study, Rainfall data are computed with a rapid update satellite precipitation estimation algorithm based on IR and MW satellite observations. This research was carried out in the framework of the EURAINSAT project (an EC research project co-funded by the Energy, Environment and Sustainable Development Programme within the topic 'Development of generic Earth observation technologies', Contract number EVG1-2000-00030).

Satellite-Based Stratospheric and Tropospheric Measurements: Determination of Global Ozone and Other Trace Species

NASA Astrophysics Data System (ADS)

Chance, Kelly

2003-02-01

This grant is an extension to our previous NASA Grant NAG5-3461, providing incremental funding to continue GOME (Global Ozone Monitoring Experiment) and SCIAMACHY (SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY) studies. This report summarizes research done under these grants through December 31, 2002. The research performed during this reporting period includes development and maintenance of scientific software for the GOME retrieval algorithms, consultation on operational software development for GOME, consultation and development for SCIAMACHY near-real-time (NRT) and off-line (OL) data products, and participation in initial SCIAMACHY validation studies. The Global Ozone Monitoring Experiment was successfully launched on the ERS-2 satellite on April 20, 1995, and remains working in normal fashion. SCIAMACHY was launched March 1, 2002 on the ESA Envisat satellite. Three GOME-2 instruments are now scheduled to fly on the Metop series of operational meteorological satellites (Eumetsat). K. Chance is a member of the reconstituted GOME Scientific Advisory Group, which will guide the GOME-2 program as well as the continuing ERS-2 GOME program.

Space-based Doppler lidar sampling strategies: Algorithm development and simulated observation experiments

NASA Technical Reports Server (NTRS)

Emmitt, G. D.; Wood, S. A.; Morris, M.

1990-01-01

Lidar Atmospheric Wind Sounder (LAWS) Simulation Models (LSM) were developed to evaluate the potential impact of global wind observations on the basic understanding of the Earth's atmosphere and on the predictive skills of current forecast models (GCM and regional scale). Fully integrated top to bottom LAWS Simulation Models for global and regional scale simulations were developed. The algorithm development incorporated the effects of aerosols, water vapor, clouds, terrain, and atmospheric turbulence into the models. Other additions include a new satellite orbiter, signal processor, line of sight uncertainty model, new Multi-Paired Algorithm and wind error analysis code. An atmospheric wind field library containing control fields, meteorological fields, phenomena fields, and new European Center for Medium Range Weather Forecasting (ECMWF) data was also added. The LSM was used to address some key LAWS issues and trades such as accuracy and interpretation of LAWS information, data density, signal strength, cloud obscuration, and temporal data resolution.

Desert Dust Satellite Retrieval Intercomparison

NASA Technical Reports Server (NTRS)

Carboni, E.; Thomas, G. E.; Sayer, A. M.; Siddans, R.; Poulsen, C. A.; Grainger, R. G.; Ahn, C.; Antoine, D.; Bevan, S.; Braak, R.;

Development of fog detection algorithm using Himawari-8/AHI data at daytime

NASA Astrophysics Data System (ADS)

Han, Ji-Hye; Kim, So-Hyeong; suh, Myoung-Seok

2017-04-01

Fog is defined that small cloud water drops or ice particles float in the air and visibility is less than 1 km. In general, fog affects ecological system, radiation budget and human activities such as airplane, ship, and car. In this study, we developed a fog detection algorithm (FDA) consisted of four threshold tests of optical and textual properties of fog using satellite and ground observation data at daytime. For the detection of fog, we used satellite data (Himawari-8/AHI data) and other ancillary data such as air temperature from NWP data (over land), SST from OSTIA (over sea). And for validation, ground observed visibility data from KMA. The optical and textual properties of fog are normalized albedo (NAlb) and normalized local standard deviation (NLSD), respectively. In addition, differences between air temperature (SST) and fog top temperature (FTa(S)) are applied to discriminate the fog from low clouds. And post-processing is performed to detect the fog edge based on spatial continuity of fog. Threshold values for each test are determined by optimization processes based on the ROC analysis for the selected fog cases. Fog detection is performed according to solar zenith angle (SZA) because of the difference of available satellite data. In this study, we defined daytime when SZA is less than 85˚ . Result of FDA is presented by probability (0 ˜ 100 %) of fog through the weighted sum of each test result. The validation results with ground observed visibility data showed that POD and FAR are 0.63 ˜ 0.89 and 0.29 ˜ 0.46 according to the fog intensity and type, respectively. In general, the detection skills are better in the cases of intense and without high clouds than localized and weak fog. We are plan to transfer this algorithm to the National Meteorological Satellite Center of KMA for the operational detection of fog using GK-2A/AMI data which will be launched in 2018.

A method for automated snow avalanche debris detection through use of synthetic aperture radar (SAR) imaging

NASA Astrophysics Data System (ADS)

Vickers, H.; Eckerstorfer, M.; Malnes, E.; Larsen, Y.; Hindberg, H.

2016-11-01

Avalanches are a natural hazard that occur in mountainous regions of Troms County in northern Norway during winter and can cause loss of human life and damage to infrastructure. Knowledge of when and where they occur especially in remote, high mountain areas is often lacking due to difficult access. However, complete, spatiotemporal avalanche activity data sets are important for accurate avalanche forecasting, as well as for deeper understanding of the link between avalanche occurrences and the triggering snowpack and meteorological factors. It is therefore desirable to develop a technique that enables active mapping and monitoring of avalanches over an entire winter. Avalanche debris can be observed remotely over large spatial areas, under all weather and light conditions by synthetic aperture radar (SAR) satellites. The recently launched Sentinel-1A satellite acquires SAR images covering the entire Troms County with frequent updates. By focusing on a case study from New Year 2015 we use Sentinel-1A images to develop an automated avalanche debris detection algorithm that utilizes change detection and unsupervised object classification methods. We compare our results with manually identified avalanche debris and field-based images to quantify the algorithm accuracy. Our results indicate that a correct detection rate of over 60% can be achieved, which is sensitive to several algorithm parameters that may need revising. With further development and refinement of the algorithm, we believe that this method could play an effective role in future operational monitoring of avalanches within Troms and has potential application in avalanche forecasting areas worldwide.

Evaluation of Passive Multilayer Cloud Detection Using Preliminary CloudSat and CALIPSO Cloud Profiles

NASA Astrophysics Data System (ADS)

Minnis, P.; Sun-Mack, S.; Chang, F.; Huang, J.; Nguyen, L.; Ayers, J. K.; Spangenberg, D. A.; Yi, Y.; Trepte, C. R.

2006-12-01

During the last few years, several algorithms have been developed to detect and retrieve multilayered clouds using passive satellite data. Assessing these techniques has been difficult due to the need for active sensors such as cloud radars and lidars that can "see" through different layers of clouds. Such sensors have been available only at a few surface sites and on aircraft during field programs. With the launch of the CALIPSO and CloudSat satellites on April 28, 2006, it is now possible to observe multilayered systems all over the globe using collocated cloud radar and lidar data. As part of the A- Train, these new active sensors are also matched in time ad space with passive measurements from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer - EOS (AMSR-E). The Clouds and the Earth's Radiant Energy System (CERES) has been developing and testing algorithms to detect ice-over-water overlapping cloud systems and to retrieve the cloud liquid path (LWP) and ice water path (IWP) for those systems. One technique uses a combination of the CERES cloud retrieval algorithm applied to MODIS data and a microwave retrieval method applied to AMSR-E data. The combination of a CO2-slicing cloud retireval technique with the CERES algorithms applied to MODIS data (Chang et al., 2005) is used to detect and analyze such overlapped systems that contain thin ice clouds. A third technique uses brightness temperature differences and the CERES algorithms to detect similar overlapped methods. This paper uses preliminary CloudSat and CALIPSO data to begin a global scale assessment of these different methods. The long-term goals are to assess and refine the algorithms to aid the development of an optimal combination of the techniques to better monitor ice 9and liquid water clouds in overlapped conditions.

Evaluation of Passive Multilayer Cloud Detection Using Preliminary CloudSat and CALIPSO Cloud Profiles

NASA Astrophysics Data System (ADS)

Minnis, P.; Sun-Mack, S.; Chang, F.; Huang, J.; Nguyen, L.; Ayers, J. K.; Spangenberg, D. A.; Yi, Y.; Trepte, C. R.

2005-05-01

During the last few years, several algorithms have been developed to detect and retrieve multilayered clouds using passive satellite data. Assessing these techniques has been difficult due to the need for active sensors such as cloud radars and lidars that can "see" through different layers of clouds. Such sensors have been available only at a few surface sites and on aircraft during field programs. With the launch of the CALIPSO and CloudSat satellites on April 28, 2006, it is now possible to observe multilayered systems all over the globe using collocated cloud radar and lidar data. As part of the A- Train, these new active sensors are also matched in time ad space with passive measurements from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer - EOS (AMSR-E). The Clouds and the Earth's Radiant Energy System (CERES) has been developing and testing algorithms to detect ice-over-water overlapping cloud systems and to retrieve the cloud liquid path (LWP) and ice water path (IWP) for those systems. One technique uses a combination of the CERES cloud retrieval algorithm applied to MODIS data and a microwave retrieval method applied to AMSR-E data. The combination of a CO2-slicing cloud retireval technique with the CERES algorithms applied to MODIS data (Chang et al., 2005) is used to detect and analyze such overlapped systems that contain thin ice clouds. A third technique uses brightness temperature differences and the CERES algorithms to detect similar overlapped methods. This paper uses preliminary CloudSat and CALIPSO data to begin a global scale assessment of these different methods. The long-term goals are to assess and refine the algorithms to aid the development of an optimal combination of the techniques to better monitor ice 9and liquid water clouds in overlapped conditions.

Advanced Oil Spill Detection Algorithms For Satellite Based Maritime Environment Monitoring

NASA Astrophysics Data System (ADS)

Radius, Andrea; Azevedo, Rui; Sapage, Tania; Carmo, Paulo

2013-12-01

During the last years, the increasing pollution occurrence and the alarming deterioration of the environmental health conditions of the sea, lead to the need of global monitoring capabilities, namely for marine environment management in terms of oil spill detection and indication of the suspected polluter. The sensitivity of Synthetic Aperture Radar (SAR) to the different phenomena on the sea, especially for oil spill and vessel detection, makes it a key instrument for global pollution monitoring. The SAR performances in maritime pollution monitoring are being operationally explored by a set of service providers on behalf of the European Maritime Safety Agency (EMSA), which has launched in 2007 the CleanSeaNet (CSN) project - a pan-European satellite based oil monitoring service. EDISOFT, which is from the beginning a service provider for CSN, is continuously investing in R&D activities that will ultimately lead to better algorithms and better performance on oil spill detection from SAR imagery. This strategy is being pursued through EDISOFT participation in the FP7 EC Sea-U project and in the Automatic Oil Spill Detection (AOSD) ESA project. The Sea-U project has the aim to improve the current state of oil spill detection algorithms, through the informative content maximization obtained with data fusion, the exploitation of different type of data/ sensors and the development of advanced image processing, segmentation and classification techniques. The AOSD project is closely related to the operational segment, because it is focused on the automation of the oil spill detection processing chain, integrating auxiliary data, like wind information, together with image and geometry analysis techniques. The synergy between these different objectives (R&D versus operational) allowed EDISOFT to develop oil spill detection software, that combines the operational automatic aspect, obtained through dedicated integration of the processing chain in the existing open source NEST software, with new detection, filtering and classification algorithms. Particularly, dedicated filtering algorithm development based on Wavelet filtering was exploited for the improvement of oil spill detection and classification. In this work we present the functionalities of the developed software and the main results in support of the developed algorithm validity.

Adaptation of an aerosol retrieval algorithm using multi-wavelength and multi-pixel information of satellites (MWPM) to GOSAT/TANSO-CAI

NASA Astrophysics Data System (ADS)

Hashimoto, M.; Takenaka, H.; Higurashi, A.; Nakajima, T.

2017-12-01

Aerosol in the atmosphere is an important constituent for determining the earth's radiation budget, so the accurate aerosol retrievals from satellite is useful. We have developed a satellite remote sensing algorithm to retrieve the aerosol optical properties using multi-wavelength and multi-pixel information of satellite imagers (MWPM). The method simultaneously derives aerosol optical properties, such as aerosol optical thickness (AOT), single scattering albedo (SSA) and aerosol size information, by using spatial difference of wavelegths (multi-wavelength) and surface reflectances (multi-pixel). The method is useful for aerosol retrieval over spatially heterogeneous surface like an urban region. In this algorithm, the inversion method is a combination of an optimal method and smoothing constraint for the state vector. Furthermore, this method has been combined with the direct radiation transfer calculation (RTM) numerically solved by each iteration step of the non-linear inverse problem, without using look up table (LUT) with several constraints. However, it takes too much computation time. To accelerate the calculation time, we replaced the RTM with an accelerated RTM solver learned by neural network-based method, EXAM (Takenaka et al., 2011), using Rster code. And then, the calculation time was shorternd to about one thouthandth. We applyed MWPM combined with EXAM to GOSAT/TANSO-CAI (Cloud and Aerosol Imager). CAI is a supplement sensor of TANSO-FTS, dedicated to measure cloud and aerosol properties. CAI has four bands, 380, 674, 870 and 1600 nm, and observes in 500 meters resolution for band1, band2 and band3, and 1.5 km for band4. Retrieved parameters are aerosol optical properties, such as aerosol optical thickness (AOT) of fine and coarse mode particles at a wavelenth of 500nm, a volume soot fraction in fine mode particles, and ground surface albedo of each observed wavelength by combining a minimum reflectance method and Fukuda et al. (2013). We will show the results and discuss the accuracy of the algorithm for various surface types. Our future work is to extend the algorithm for analysis of GOSAT-2/TANSO-CAI-2 and GCOM/C-SGLI data.

AATSR Based Volcanic Ash Plume Top Height Estimation

NASA Astrophysics Data System (ADS)

Virtanen, Timo H.; Kolmonen, Pekka; Sogacheva, Larisa; Sundstrom, Anu-Maija; Rodriguez, Edith; de Leeuw, Gerrit

2015-11-01

The AATSR Correlation Method (ACM) height estimation algorithm is presented. The algorithm uses Advanced Along Track Scanning Radiometer (AATSR) satellite data to detect volcanic ash plumes and to estimate the plume top height. The height estimate is based on the stereo-viewing capability of the AATSR instrument, which allows to determine the parallax between the satellite's nadir and 55◦ forward views, and thus the corresponding height. AATSR provides an advantage compared to other stereo-view satellite instruments: with AATSR it is possible to detect ash plumes using brightness temperature difference between thermal infrared (TIR) channels centered at 11 and 12 μm. The automatic ash detection makes the algorithm efficient in processing large quantities of data: the height estimate is calculated only for the ash-flagged pixels. Besides ash plumes, the algorithm can be applied to any elevated feature with sufficient contrast to the background, such as smoke and dust plumes and clouds. The ACM algorithm can be applied to the Sea and Land Surface Temperature Radiometer (SLSTR), scheduled for launch at the end of 2015.

Ship detection in satellite imagery using rank-order greyscale hit-or-miss transforms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harvey, Neal R; Porter, Reid B; Theiler, James

2010-01-01

Ship detection from satellite imagery is something that has great utility in various communities. Knowing where ships are and their types provides useful intelligence information. However, detecting and recognizing ships is a difficult problem. Existing techniques suffer from too many false-alarms. We describe approaches we have taken in trying to build ship detection algorithms that have reduced false alarms. Our approach uses a version of the grayscale morphological Hit-or-Miss transform. While this is well known and used in its standard form, we use a version in which we use a rank-order selection for the dilation and erosion parts of themore » transform, instead of the standard maximum and minimum operators. This provides some slack in the fitting that the algorithm employs and provides a method for tuning the algorithm's performance for particular detection problems. We describe our algorithms, show the effect of the rank-order parameter on the algorithm's performance and illustrate the use of this approach for real ship detection problems with panchromatic satellite imagery.« less

True Colour Classification of Natural Waters with Medium-Spectral Resolution Satellites: SeaWiFS, MODIS, MERIS and OLCI

PubMed Central

van der Woerd, Hendrik J.; Wernand, Marcel R.

2015-01-01

The colours from natural waters differ markedly over the globe, depending on the water composition and illumination conditions. The space-borne “ocean colour” instruments are operational instruments designed to retrieve important water-quality indicators, based on the measurement of water leaving radiance in a limited number (5 to 10) of narrow (≈10 nm) bands. Surprisingly, the analysis of the satellite data has not yet paid attention to colour as an integral optical property that can also be retrieved from multispectral satellite data. In this paper we re-introduce colour as a valuable parameter that can be expressed mainly by the hue angle (α). Based on a set of 500 synthetic spectra covering a broad range of natural waters a simple algorithm is developed to derive the hue angle from SeaWiFS, MODIS, MERIS and OLCI data. The algorithm consists of a weighted linear sum of the remote sensing reflectance in all visual bands plus a correction term for the specific band-setting of each instrument. The algorithm is validated by a set of 603 hyperspectral measurements from inland-, coastal- and near-ocean waters. We conclude that the hue angle is a simple objective parameter of natural waters that can be retrieved uniformly for all space-borne ocean colour instruments. PMID:26473859

A satellite-based radar wind sensor

NASA Technical Reports Server (NTRS)

Xin, Weizhuang

1991-01-01

The objective is to investigate the application of Doppler radar systems for global wind measurement. A model of the satellite-based radar wind sounder (RAWS) is discussed, and many critical problems in the designing process, such as the antenna scan pattern, tracking the Doppler shift caused by satellite motion, and backscattering of radar signals from different types of clouds, are discussed along with their computer simulations. In addition, algorithms for measuring mean frequency of radar echoes, such as the Fast Fourier Transform (FFT) estimator, the covariance estimator, and the estimators based on autoregressive models, are discussed. Monte Carlo computer simulations were used to compare the performance of these algorithms. Anti-alias methods are discussed for the FFT and the autoregressive methods. Several algorithms for reducing radar ambiguity were studied, such as random phase coding methods and staggered pulse repitition frequncy (PRF) methods. Computer simulations showed that these methods are not applicable to the RAWS because of the broad spectral widths of the radar echoes from clouds. A waveform modulation method using the concept of spread spectrum and correlation detection was developed to solve the radar ambiguity. Radar ambiguity functions were used to analyze the effective signal-to-noise ratios for the waveform modulation method. The results showed that, with suitable bandwidth product and modulation of the waveform, this method can achieve the desired maximum range and maximum frequency of the radar system.

Method for validating cloud mask obtained from satellite measurements using ground-based sky camera.

PubMed

Letu, Husi; Nagao, Takashi M; Nakajima, Takashi Y; Matsumae, Yoshiaki

2014-11-01

Error propagation in Earth's atmospheric, oceanic, and land surface parameters of the satellite products caused by misclassification of the cloud mask is a critical issue for improving the accuracy of satellite products. Thus, characterizing the accuracy of the cloud mask is important for investigating the influence of the cloud mask on satellite products. In this study, we proposed a method for validating multiwavelength satellite data derived cloud masks using ground-based sky camera (GSC) data. First, a cloud cover algorithm for GSC data has been developed using sky index and bright index. Then, Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data derived cloud masks by two cloud-screening algorithms (i.e., MOD35 and CLAUDIA) were validated using the GSC cloud mask. The results indicate that MOD35 is likely to classify ambiguous pixels as "cloudy," whereas CLAUDIA is likely to classify them as "clear." Furthermore, the influence of error propagations caused by misclassification of the MOD35 and CLAUDIA cloud masks on MODIS derived reflectance, brightness temperature, and normalized difference vegetation index (NDVI) in clear and cloudy pixels was investigated using sky camera data. It shows that the influence of the error propagation by the MOD35 cloud mask on the MODIS derived monthly mean reflectance, brightness temperature, and NDVI for clear pixels is significantly smaller than for the CLAUDIA cloud mask; the influence of the error propagation by the CLAUDIA cloud mask on MODIS derived monthly mean cloud products for cloudy pixels is significantly smaller than that by the MOD35 cloud mask.

Cloud cover determination in polar regions from satellite imagery

NASA Technical Reports Server (NTRS)

Barry, R. G.; Key, J. R.; Maslanik, J. A.

1988-01-01

The principal objectives of this project are: (1) to develop suitable validation data sets to evaluate the effectiveness of the International Satellite Cloud Climatology Project (ISCCP) operational algorithm for cloud retrieval in polar regions and to validate model simulations of polar cloud cover; (2) to identify limitations of current procedures for varying atmospheric surface conditions, and to explore potential means to remedy them using textural classifiers; and (3) to compare synoptic cloud data from a control run experiment of the GISS climate model II with typical observed synoptic cloud patterns.

Effects of Whitecaps on Satellite-Derived Ocean Color

NASA Technical Reports Server (NTRS)

Frouin, Robert

2000-01-01

During the 3.25 years of the project, various aspects of satellite ocean-color remote sensing were investigated, including effect of whitecaps on atmospheric correction, validity of aerosol models, and evaluation of ocean-color products. Algorithms to estimate pigment concentration and photo-synthetically active radiation (PAR) were developed, and studies of geophysical phenomena, such as the 1998 Asian Dust event, were performed. The influence of solar radiation absorption by phytoplankton on mixed layer dynamics, ocean circulation, and climate was also investigated. The project's results and findings are described.

Small Fire Detection Algorithm Development using VIIRS 375m Imagery: Application to Agricultural Fires in Eastern China

NASA Astrophysics Data System (ADS)

Zhang, Tianran; Wooster, Martin

2016-04-01

Until recently, crop residues have been the second largest industrial waste product produced in China and field-based burning of crop residues is considered to remain extremely widespread, with impacts on air quality and potential negative effects on health, public transportation. However, due to the small size and perhaps short-lived nature of the individual burns, the extent of the activity and its spatial variability remains somewhat unclear. Satellite EO data has been used to gauge the timing and magnitude of Chinese crop burning, but current approaches very likely miss significant amounts of the activity because the individual burned areas are either too small to detect with frequently acquired moderate spatial resolution data such as MODIS. The Visible Infrared Imaging Radiometer Suite (VIIRS) on-board Suomi-NPP (National Polar-orbiting Partnership) satellite launched on October, 2011 has one set of multi-spectral channels providing full global coverage at 375 m nadir spatial resolutions. It is expected that the 375 m spatial resolution "I-band" imagery provided by VIIRS will allow active fires to be detected that are ~ 10× smaller than those that can be detected by MODIS. In this study the new small fire detection algorithm is built based on VIIRS-I band global fire detection algorithm and hot spot detection algorithm for the BIRD satellite mission. VIIRS-I band imagery data will be used to identify agricultural fire activity across Eastern China. A 30 m spatial resolution global land cover data map is used for false alarm masking. The ground-based validation is performed using images taken from UAV. The fire detection result is been compared with active fire product from the long-standing MODIS sensor onboard the TERRA and AQUA satellites, which shows small fires missed from traditional MODIS fire product may count for over 1/3 of total fire energy in Eastern China.

GPM Plans for Radiometer Intercalibration

NASA Technical Reports Server (NTRS)

Stocker, Erich Franz; Stout, John; Chou, Joyce

2011-01-01

The international Global Precipitation Measurement (GPM) mission led by NASA and JAXA is planned as a multi-radiometer constellation mission. A key mission component is the ability to intercalibrate the Tb from the partner constellation radiometers and create inter-calibrated, mission consistent Tc. One of the enabling strategies for this approach is the launching of a joint NASA/JAXA core satellite which contains a JAXA/NICT provided dual precipitation radar and a NASA provided Microwave Imaging passive radiometer. The observations from these instruments on the core satellite provide the opportunity to develop a transfer reference standard that can then be applied across the partner provided constellation radiometers that enables the creation of mission consistent brightness temperatures. The other aspect of the strategy is the development of a community consensus intercalibration algorithm that will be applied to the Tb observations from partner radiometers and create the best calibrated Tc. Also described is the development of the framework in which the inter-calibration is included in the final algorithm. A part of the latter effort has been the development of a generic, logical structure which can be applied across radiometer types and which guarantees the user community that key information for using Tc properly is recorded. Key

a Comprehensive Review of Pansharpening Algorithms for GÖKTÜRK-2 Satellite Images

NASA Astrophysics Data System (ADS)

Kahraman, S.; Ertürk, A.

2017-11-01

In this paper, a comprehensive review and performance evaluation of pansharpening algorithms for GÖKTÜRK-2 images is presented. GÖKTÜRK-2 is the first high resolution remote sensing satellite of Turkey which was designed and built in Turkey, by The Ministry of Defence, TUBITAK-UZAY and Turkish Aerospace Industry (TUSAŞ) collectively. GÖKTÜRK-2 was launched at 18th. December 2012 in Jinguan, China and provides 2.5 meter panchromatic (PAN) and 5 meter multispectral (MS) spatial resolution satellite images. In this study, a large number of pansharpening algorithms are implemented and evaluated for performance on multiple GÖKTÜRK-2 satellite images. Quality assessments are conducted both qualitatively through visual results and quantitatively using Root Mean Square Error (RMSE), Correlation Coefficient (CC), Spectral Angle Mapper (SAM), Erreur Relative Globale Adimensionnelle de Synthése (ERGAS), Peak Signal to Noise Ratio (PSNR), Structural Similarity Index (SSIM) and Universal Image Quality Index (UIQI).

Recent results of the Global Precipitation Measurement (GPM) mission in Japan

NASA Astrophysics Data System (ADS)

Kubota, Takuji; Oki, Riko; Furukawa, Kinji; Kaneko, Yuki; Yamaji, Moeka; Iguchi, Toshio; Takayabu, Yukari

2017-04-01

The Global Precipitation Measurement (GPM) mission is an international collaboration to achieve highly accurate and highly frequent global precipitation observations. The GPM mission consists of the GPM Core Observatory jointly developed by U.S. and Japan and Constellation Satellites that carry microwave radiometers and provided by the GPM partner agencies. The GPM Core Observatory, launched on February 2014, carries the Dual-frequency Precipitation Radar (DPR) by the Japan Aerospace Exploration Agency (JAXA) and the National Institute of Information and Communications Technology (NICT). JAXA develops the DPR Level 1 algorithm, and the NASA-JAXA Joint Algorithm Team develops the DPR Level 2 and DPR-GMI combined Level2 algorithms. The Japan Meteorological Agency (JMA) started the DPR assimilation in the meso-scale Numerical Weather Prediction (NWP) system on March 24 2016. This was regarded as the world's first "operational" assimilation of spaceborne radar data in the NWP system of meteorological agencies. JAXA also develops the Global Satellite Mapping of Precipitation (GSMaP), as national product to distribute hourly and 0.1-degree horizontal resolution rainfall map. The GSMaP near-real-time version (GSMaP_NRT) product is available 4-hour after observation through the "JAXA Global Rainfall Watch" web site (http://sharaku.eorc.jaxa.jp/GSMaP) since 2008. The GSMaP_NRT product gives higher priority to data latency than accuracy, and has been used by various users for various purposes, such as rainfall monitoring, flood alert and warning, drought monitoring, crop yield forecast, and agricultural insurance. There is, however, a requirement for shortening of data latency time from GSMaP users. To reduce data latency, JAXA has developed the GSMaP realtime version (GSMaP_NOW) product for observation area of the geostationary satellite Himawari-8 operated by the Japan Meteorological Agency (JMA). GSMaP_NOW product was released to public in November 2, 2015 through the "JAXA Realtime Rainfall Watch" web site (http://sharaku.eorc.jaxa.jp/GSMaP_NOW/). All GPM standard products and the GPM-GSMaP product have been released to the public since September 2014 as Version 03. The GPM products can be downloaded via the internet through the JAXA G-Portal (https://www.gportal.jaxa.jp). On Mar. 2016, the DPR, the GMI, and the DPR-GMI combined algorithms were updated and the first GPM latent heating product (in the TRMM coverage) were released. Therefore, the GPM Version 04 standard products have been provided since Mar. 2016. Furthermore, the GPM-GSMaP algorithms were updated and the GPM-GSMaP Version 04 products have been provided since Jan. 2017.

Design of an Efficient CAC for a Broadband DVB-S/DVB-RCS Satellite Access Network

NASA Astrophysics Data System (ADS)

Inzerilli, Tiziano; Montozzi, Simone

2003-07-01

This paper deals with efficient utilization of network resources in an advanced broadband satellite access system. It proposes a technique for admission control of IP streams with guaranteed QoS which does not interfere with the particular BoD (Bandwidth on Demand) algorithm that handles access to uplink bandwidth, an essential part of a DVB- RCS architecture. This feature of the admission control greatly simplify its integration in the satellite network. The purpose of this admission control algorithm in particular is to suitably and dynamically configure the overall traffic control parameters, in the access terminal of the user and service segment, with a simple approach which does not introduces limitations and/or constraints to the BoD algorithm. Performance of the proposed algorithm is evaluated thorugh Opnet simulations using an ad-hoc platform modeling DVB-based satellite access.The results presented in this paper were obtained within SATIP6 project, which is sponsored within the 5th EU Research Programme, IST. The aims of the project are to evaluate and demonstrate key issues of the integration of satellite-based access networks into the Internet in order to support multimedia services over wide areas. The satellite link layer is based on DVB-S on the forward link and DVB-RCS on the return link. Adaptation and optimization of the DVB-RCS access standard in order to support QoS provision are central issues of the project. They are handled through an integration of Connection Admission Control (CAC), Traffic Shaping and Policing techniques.

The remote sensing image segmentation mean shift algorithm parallel processing based on MapReduce

NASA Astrophysics Data System (ADS)

Chen, Xi; Zhou, Liqing

2015-12-01

With the development of satellite remote sensing technology and the remote sensing image data, traditional remote sensing image segmentation technology cannot meet the massive remote sensing image processing and storage requirements. This article put cloud computing and parallel computing technology in remote sensing image segmentation process, and build a cheap and efficient computer cluster system that uses parallel processing to achieve MeanShift algorithm of remote sensing image segmentation based on the MapReduce model, not only to ensure the quality of remote sensing image segmentation, improved split speed, and better meet the real-time requirements. The remote sensing image segmentation MeanShift algorithm parallel processing algorithm based on MapReduce shows certain significance and a realization of value.

Transfer and distortion of atmospheric information in the satellite temperature retrieval problem

NASA Technical Reports Server (NTRS)

Thompson, O. E.

1981-01-01

A systematic approach to investigating the transfer of basic ambient temperature information and its distortion by satellite systems and subsequent analysis algorithms is discussed. The retrieval analysis cycle is derived, the variance spectrum of information is examined as it takes different forms in that process, and the quality and quantity of information existing at each stop is compared with the initial ambient temperature information. Temperature retrieval algorithms can smooth, add, or further distort information, depending on how stable the algorithm is, and how heavily influenced by a priori data.

Estimating surface soil moisture from SMAP observations using a neural network technique

USDA-ARS?s Scientific Manuscript database

A Neural Network (NN) algorithm was developed to estimate global surface soil moisture for April 2015 to June 2016 with a 2-3 day repeat frequency using passive microwave observations from the Soil Moisture Active Passive (SMAP) satellite, surface soil temperatures from the NASA Goddard Earth Observ...

Estimating Contrail Climate Effects from Satellite Data

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Duda, David P.; Palikonda, Rabindra; Bedka, Sarah T.; Boeke, Robyn; Khlopenkov, Konstantin; Chee, Thad; Bedka, Kristopher T.

2011-01-01

An automated contrail detection algorithm (CDA) is developed to exploit six of the infrared channels on the 1-km MODerate-resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites. The CDA is refined and balanced using visual error analysis. It is applied to MODIS data taken by Terra and Aqua over the United States during 2006 and 2008. The results are consistent with flight track data, but differ markedly from earlier analyses. Contrail coverage is a factor of 4 less than other retrievals and the retrieved contrail optical depths and radiative forcing are smaller by approx.30%. The discrepancies appear to be due to the inability to detect wider, older contrails that comprise a significant amount of the contrail coverage. An example of applying the algorithm to MODIS data over the entire Northern Hemisphere is also presented. Overestimates of contrail coverage are apparent in some tropical regions. Methods for improving the algorithm are discussed and are to be implemented before analyzing large amounts of Northern Hemisphere data. The results should be valuable for guiding and validating climate models seeking to account for aviation effects on climate.

Ionospheric Specifications for SAR Interferometry (ISSI)

NASA Technical Reports Server (NTRS)

Pi, Xiaoqing; Chapman, Bruce D; Freeman, Anthony; Szeliga, Walter; Buckley, Sean M.; Rosen, Paul A.; Lavalle, Marco

2013-01-01

The ISSI software package is designed to image the ionosphere from space by calibrating and processing polarimetric synthetic aperture radar (PolSAR) data collected from low Earth orbit satellites. Signals transmitted and received by a PolSAR are subject to the Faraday rotation effect as they traverse the magnetized ionosphere. The ISSI algorithms combine the horizontally and vertically polarized (with respect to the radar system) SAR signals to estimate Faraday rotation and ionospheric total electron content (TEC) with spatial resolutions of sub-kilometers to kilometers, and to derive radar system calibration parameters. The ISSI software package has been designed and developed to integrate the algorithms, process PolSAR data, and image as well as visualize the ionospheric measurements. A number of tests have been conducted using ISSI with PolSAR data collected from various latitude regions using the phase array-type L-band synthetic aperture radar (PALSAR) onboard Japan Aerospace Exploration Agency's Advanced Land Observing Satellite mission, and also with Global Positioning System data. These tests have demonstrated and validated SAR-derived ionospheric images and data correction algorithms.

Development, Comparisons and Evaluation of Aerosol Retrieval Algorithms

NASA Astrophysics Data System (ADS)

de Leeuw, G.; Holzer-Popp, T.; Aerosol-cci Team

2011-12-01

The Climate Change Initiative (cci) of the European Space Agency (ESA) has brought together a team of European Aerosol retrieval groups working on the development and improvement of aerosol retrieval algorithms. The goal of this cooperation is the development of methods to provide the best possible information on climate and climate change based on satellite observations. To achieve this, algorithms are characterized in detail as regards the retrieval approaches, the aerosol models used in each algorithm, cloud detection and surface treatment. A round-robin intercomparison of results from the various participating algorithms serves to identify the best modules or combinations of modules for each sensor. Annual global datasets including their uncertainties will then be produced and validated. The project builds on 9 existing algorithms to produce spectral aerosol optical depth (AOD and Ångström exponent) as well as other aerosol information; two instruments are included to provide the absorbing aerosol index (AAI) and stratospheric aerosol information. The algorithms included are: - 3 for ATSR (ORAC developed by RAL / Oxford university, ADV developed by FMI and the SU algorithm developed by Swansea University ) - 2 for MERIS (BAER by Bremen university and the ESA standard handled by HYGEOS) - 1 for POLDER over ocean (LOA) - 1 for synergetic retrieval (SYNAER by DLR ) - 1 for OMI retreival of the absorbing aerosol index with averaging kernel information (KNMI) - 1 for GOMOS stratospheric extinction profile retrieval (BIRA) The first seven algorithms aim at the retrieval of the AOD. However, each of the algorithms used differ in their approach, even for algorithms working with the same instrument such as ATSR or MERIS. To analyse the strengths and weaknesses of each algorithm several tests are made. The starting point for comparison and measurement of improvements is a retrieval run for 1 month, September 2008. The data from the same month are subsequently used for several runs with a prescribed set of aerosol models and an a priori data set derived from the median of AEROCOM model runs. The aerosol models and a priori data can be used in several ways, i.e. fully prescribed or with some freedom to choose a combination of aerosol models, based on the a priori or not. Another test gives insight in the effect of the cloud masks used, i.e. retrievals using the same cloud mask (the AATSR APOLLO cloud mask for collocated instruments) are compared with runs using the standard cloud masks. Tests to determine the influence of surface treatment are planned as well. The results of all these tests are evaluated by an independent team which compares the retrieval results with ground-based remote sensing (in particular AERONET) and in-situ data, and by a scoring method. Results are compared with other satellites such as MODIS and MISR. Blind tests using synthetic data are part of the algorithm characterization. The presentation will summarize results of the ongoing phase 1 inter-comparison and evaluation work within the Aerosol_cci project.

A recursively formulated first-order semianalytic artificial satellite theory based on the generalized method of averaging. Volume 1: The generalized method of averaging applied to the artificial satellite problem

NASA Technical Reports Server (NTRS)

Mcclain, W. D.

1977-01-01

A recursively formulated, first-order, semianalytic artificial satellite theory, based on the generalized method of averaging is presented in two volumes. Volume I comprehensively discusses the theory of the generalized method of averaging applied to the artificial satellite problem. Volume II presents the explicit development in the nonsingular equinoctial elements of the first-order average equations of motion. The recursive algorithms used to evaluate the first-order averaged equations of motion are also presented in Volume II. This semianalytic theory is, in principle, valid for a term of arbitrary degree in the expansion of the third-body disturbing function (nonresonant cases only) and for a term of arbitrary degree and order in the expansion of the nonspherical gravitational potential function.

The Goes-R Geostationary Lightning Mapper (GLM)

NASA Technical Reports Server (NTRS)

Goodman, Steven J.; Blakeslee, Richard J.; Koshak, William J.; Mach, Douglas

2011-01-01

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. Superior spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved storm diagnostic capability with the Advanced Baseline Imager. The GLM will map total lightning activity (in-cloud and cloud-to-ground lighting flashes) continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency. In parallel with the instrument development, a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms, cal/val performance monitoring tools, and new applications. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. In this paper we will report on new Nowcasting and storm warning applications being developed and evaluated at various NOAA Testbeds.

Pre-seismic anomalies from optical satellite observations: a review

NASA Astrophysics Data System (ADS)

Jiao, Zhong-Hu; Zhao, Jing; Shan, Xinjian

2018-04-01

Detecting various anomalies using optical satellite data prior to strong earthquakes is key to understanding and forecasting earthquake activities because of its recognition of thermal-radiation-related phenomena in seismic preparation phases. Data from satellite observations serve as a powerful tool in monitoring earthquake preparation areas at a global scale and in a nearly real-time manner. Over the past several decades, many new different data sources have been utilized in this field, and progressive anomaly detection approaches have been developed. This paper reviews the progress and development of pre-seismic anomaly detection technology in this decade. First, precursor parameters, including parameters from the top of the atmosphere, in the atmosphere, and on the Earth's surface, are stated and discussed. Second, different anomaly detection methods, which are used to extract anomalous signals that probably indicate future seismic events, are presented. Finally, certain critical problems with the current research are highlighted, and new developing trends and perspectives for future work are discussed. The development of Earth observation satellites and anomaly detection algorithms can enrich available information sources, provide advanced tools for multilevel earthquake monitoring, and improve short- and medium-term forecasting, which play a large and growing role in pre-seismic anomaly detection research.

Long-term spatial distributions and trends of the latent heat fluxes over the global cropland ecosystem using multiple satellite-based models

PubMed Central

Feng, Fei; Yao, Yunjun; Liu, Meng

2017-01-01

Estimating cropland latent heat flux (LE) from continental to global scales is vital to modeling crop production and managing water resources. Over the past several decades, numerous LE models were developed, such as the moderate resolution imaging spectroradiometer LE (MOD16) algorithm, revised remote sensing-based Penman–Monteith LE algorithm (RRS), the Priestley–Taylor LE algorithm of the Jet Propulsion Laboratory (PT-JPL) and the modified satellite-based Priestley-Taylor LE algorithm (MS-PT). However, these LE models have not been directly compared over the global cropland ecosystem using various algorithms. In this study, we evaluated the performances of these four LE models using 34 eddy covariance (EC) sites. The results showed that mean annual LE for cropland varied from 33.49 to 58.97 W/m2 among the four models. The interannual LE slightly increased during 1982–2009 across the global cropland ecosystem. All models had acceptable performances with the coefficient of determination (R2) ranging from 0.4 to 0.7 and a root mean squared error (RMSE) of approximately 35 W/m2. MS-PT had good overall performance across the cropland ecosystem with the highest R2, lowest RMSE and a relatively low bias. The reduced performances of MOD16 and RRS, with R2 ranging from 0.4 to 0.6 and RMSEs from 30 to 39 W/m2, might be attributed to empirical parameters in the structure algorithms and calibrated coefficients. PMID:28837704

Reinforcement Learning in Distributed Domains: Beyond Team Games

NASA Technical Reports Server (NTRS)

Wolpert, David H.; Sill, Joseph; Turner, Kagan

2000-01-01

Distributed search algorithms are crucial in dealing with large optimization problems, particularly when a centralized approach is not only impractical but infeasible. Many machine learning concepts have been applied to search algorithms in order to improve their effectiveness. In this article we present an algorithm that blends Reinforcement Learning (RL) and hill climbing directly, by using the RL signal to guide the exploration step of a hill climbing algorithm. We apply this algorithm to the domain of a constellations of communication satellites where the goal is to minimize the loss of importance weighted data. We introduce the concept of 'ghost' traffic, where correctly setting this traffic induces the satellites to act to optimize the world utility. Our results indicated that the bi-utility search introduced in this paper outperforms both traditional hill climbing algorithms and distributed RL approaches such as team games.

The automatic control system and stand-by facilities of the TDMA-40 equipment

NASA Astrophysics Data System (ADS)

Gudenko, D. V.; Pankov, G. Kh.; Pauk, A. G.; Tsirlin, V. M.

1980-10-01

When a controlling station in a satellite communications system is out of order, a complex algorithm must be carried out for automatic operation of the stand-by equipment. A processor has been developed to perform this algorithm, as well as operations involving the stand-by facilities of the receiving-transmitting equipment of the station. The design principles and solutions to problems in developing the equipment for the monitoring and controlling systems are described. These systems are based on multistation access using time division multiplexing. Algorithms are presented for the operation of the synchronizing processor and the control processor of the equipment. The automatic control system and stand-by facilities make it possible to reduce the service personnel and to design an unattended station.

Fuzzy B-spline optimization for urban slum three-dimensional reconstruction using ENVISAT satellite data

NASA Astrophysics Data System (ADS)

Marghany, Maged

2014-06-01

A critical challenges in urban aeras is slums. In fact, they are considered a source of crime and disease due to poor-quality housing, unsanitary conditions, poor infrastructures and occupancy security. The poor in the dense urban slums are the most vulnerable to infection due to (i) inadequate and restricted access to safety, drinking water and sufficient quantities of water for personal hygiene; (ii) the lack of removal and treatment of excreta; and (iii) the lack of removal of solid waste. This study aims to investigate the capability of ENVISAT ASAR satellite and Google Earth data for three-dimensional (3-D) slum urban reconstruction in developed countries such as Egypt. The main objective of this work is to utilize some 3-D automatic detection algorithm for urban slum in ENVISAT ASAR and Google Erath images were acquired in Cairo, Egypt using Fuzzy B-spline algorithm. The results show that the fuzzy algorithm is the best indicator for chaotic urban slum as it can discriminate between them from its surrounding environment. The combination of Fuzzy and B-spline then used to reconstruct 3-D of urban slum. The results show that urban slums, road network, and infrastructures are perfectly discriminated. It can therefore be concluded that the fuzzy algorithm is an appropriate algorithm for chaotic urban slum automatic detection in ENVSIAT ASAR and Google Earth data.

SatCam: A mobile application for coordinated ground/satellite observation of clouds and validation of satellite-derived cloud mask products.

NASA Astrophysics Data System (ADS)

Gumley, L.; Parker, D.; Flynn, B.; Holz, R.; Marais, W.

2011-12-01

SatCam is an application for iOS devices that allows users to collect observations of local cloud and surface conditions in coordination with an overpass of the Terra, Aqua, or NPP satellites. SatCam allows users to acquire images of sky conditions and ground conditions at their location anywhere in the world using the built-in iPhone or iPod Touch camera at the same time that the satellite is passing overhead and viewing their location. Immediately after the sky and ground observations are acquired, the application asks the user to rate the level of cloudiness in the sky (Completely Clear, Mostly Clear, Partly Cloudy, Overcast). For the ground observation, the user selects their assessment of the surface conditions (Urban, Green Vegetation, Brown Vegetation, Desert, Snow, Water). The sky condition and surface condition selections are stored along with the date, time, and geographic location for the images, and the images are uploaded to a central server. When the MODIS (Terra and Aqua) or VIIRS (NPP) imagery acquired over the user location becomes available, a MODIS or VIIRS true color image centered at the user's location is delivered back to the SatCam application on the user's iOS device. SSEC also proposes to develop a community driven SatCam website where users can share their observations and assessments of satellite cloud products in a collaborative environment. SSEC is developing a server side data analysis system to ingest the SatCam user observations, apply quality control, analyze the sky images for cloud cover, and collocate the observations with MODIS and VIIRS satellite products (e.g., cloud mask). For each observation that is collocated with a satellite observation, the server will determine whether the user scored a "hit", meaning their sky observation and sky assessment matched the automated cloud mask obtained from the satellite observation. The hit rate will be an objective assessment of the accuracy of the user's sky observations. Users with high hit rates will be identified automatically and their observations will be used globally to evaluate the performance of the MODIS cloud mask algorithm for Terra and Aqua and the VIIRS cloud mask algorithm for NPP. The user's assessment of the ground conditions will also be used to evaluate the cloud mask accuracy in selecting the correct surface type at the user's location, which is an important element in the decision path used internally by the cloud mask algorithm. This presentation will describe the SatCam application, how it is used, and show examples of SatCam observations.

Large Scale Ice Water Path and 3-D Ice Water Content

DOE Data Explorer

Liu, Guosheng

2008-01-15

Cloud ice water concentration is one of the most important, yet poorly observed, cloud properties. Developing physical parameterizations used in general circulation models through single-column modeling is one of the key foci of the ARM program. In addition to the vertical profiles of temperature, water vapor and condensed water at the model grids, large-scale horizontal advective tendencies of these variables are also required as forcing terms in the single-column models. Observed horizontal advection of condensed water has not been available because the radar/lidar/radiometer observations at the ARM site are single-point measurement, therefore, do not provide horizontal distribution of condensed water. The intention of this product is to provide large-scale distribution of cloud ice water by merging available surface and satellite measurements. The satellite cloud ice water algorithm uses ARM ground-based measurements as baseline, produces datasets for 3-D cloud ice water distributions in a 10 deg x 10 deg area near ARM site. The approach of the study is to expand a (surface) point measurement to an (satellite) areal measurement. That is, this study takes the advantage of the high quality cloud measurements at the point of ARM site. We use the cloud characteristics derived from the point measurement to guide/constrain satellite retrieval, then use the satellite algorithm to derive the cloud ice water distributions within an area, i.e., 10 deg x 10 deg centered at ARM site.

Understanding the Milky Way Halo through Large Surveys

NASA Astrophysics Data System (ADS)

Koposov, Sergey

This thesis presents an extensive study of stellar substructure in the outskirts of the Milky Way(MW), combining data mining of SDSS with theoretical modeling. Such substructure, either bound star clusters and satellite galaxies, or tidally disrupted objects forming stellar streams are powerful diagnostics of the Milky Way's dynamics and formation history. I have developed an algorithmic technique of searching for stellar overdensities in the MW halo, based on SDSS catalogs. This led to the discovery of unusual ultra-faint ~ (1000Lsun) globular clusters with very compact sizes and relaxation times << t_Hubble. The detailed analysis of a known stellar stream (GD-1), allowed me to make the first 6-D phase space map for such an object along 60 degrees on the sky. By modeling the stream's orbit I could place strong constraints on the Galactic potential, e.g. Vcirc(R0)= 224+/-13 km/s. The application of the algorithmic search for stellar overdensities to the SDSS dataset and to mock datasets allowed me to quantify SDSS's severe radial incompleteness in its search for ultra-faint dwarf galaxies and to determine the luminosity function of MW satellites down to luminosities of M_V ~ -3. I used the semi-analytical model in order to compare the CDM model predictions for the MW satellite population with the observations; this comparison has shown that the recently increased census of MW satellites, better understanding of the radial incompleteness and the suppression of star formation after the reionization can fully solve the "Missing satellite problem".

A 1DVAR-based snowfall rate retrieval algorithm for passive microwave radiometers

NASA Astrophysics Data System (ADS)

Meng, Huan; Dong, Jun; Ferraro, Ralph; Yan, Banghua; Zhao, Limin; Kongoli, Cezar; Wang, Nai-Yu; Zavodsky, Bradley

2017-06-01

Snowfall rate retrieval from spaceborne passive microwave (PMW) radiometers has gained momentum in recent years. PMW can be so utilized because of its ability to sense in-cloud precipitation. A physically based, overland snowfall rate (SFR) algorithm has been developed using measurements from the Advanced Microwave Sounding Unit-A/Microwave Humidity Sounder sensor pair and the Advanced Technology Microwave Sounder. Currently, these instruments are aboard five polar-orbiting satellites, namely, NOAA-18, NOAA-19, Metop-A, Metop-B, and Suomi-NPP. The SFR algorithm relies on a separate snowfall detection algorithm that is composed of a satellite-based statistical model and a set of numerical weather prediction model-based filters. There are four components in the SFR algorithm itself: cloud properties retrieval, computation of ice particle terminal velocity, ice water content adjustment, and the determination of snowfall rate. The retrieval of cloud properties is the foundation of the algorithm and is accomplished using a one-dimensional variational (1DVAR) model. An existing model is adopted to derive ice particle terminal velocity. Since no measurement of cloud ice distribution is available when SFR is retrieved in near real time, such distribution is implicitly assumed by deriving an empirical function that adjusts retrieved SFR toward radar snowfall estimates. Finally, SFR is determined numerically from a complex integral. The algorithm has been validated against both radar and ground observations of snowfall events from the contiguous United States with satisfactory results. Currently, the SFR product is operationally generated at the National Oceanic and Atmospheric Administration and can be obtained from that organization.

Development of Time-Series Human Settlement Mapping System Using Historical Landsat Archive

NASA Astrophysics Data System (ADS)

Miyazaki, H.; Nagai, M.; Shibasaki, R.

2016-06-01

Methodology of automated human settlement mapping is highly needed for utilization of historical satellite data archives for urgent issues of urban growth in global scale, such as disaster risk management, public health, food security, and urban management. As development of global data with spatial resolution of 10-100 m was achieved by some initiatives using ASTER, Landsat, and TerraSAR-X, next goal has targeted to development of time-series data which can contribute to studies urban development with background context of socioeconomy, disaster risk management, public health, transport and other development issues. We developed an automated algorithm to detect human settlement by classification of built-up and non-built-up in time-series Landsat images. A machine learning algorithm, Local and Global Consistency (LLGC), was applied with improvements for remote sensing data. The algorithm enables to use MCD12Q1, a MODIS-based global land cover map with 500-m resolution, as training data so that any manual process is not required for preparation of training data. In addition, we designed the method to composite multiple results of LLGC into a single output to reduce uncertainty. The LLGC results has a confidence value ranging 0.0 to 1.0 representing probability of built-up and non-built-up. The median value of the confidence for a certain period around a target time was expected to be a robust output of confidence to identify built-up or non-built-up areas against uncertainties in satellite data quality, such as cloud and haze contamination. Four scenes of Landsat data for each target years, 1990, 2000, 2005, and 2010, were chosen among the Landsat archive data with cloud contamination less than 20%.We developed a system with the algorithms on the Data Integration and Analysis System (DIAS) in the University of Tokyo and processed 5200 scenes of Landsat data for cities with more than one million people worldwide.

Reduction of Non-uniform Beam Filling Effects by Vertical Decorrelation: Theory and Simulations

NASA Technical Reports Server (NTRS)

Short, David; Nakagawa, Katsuhiro; Iguchi, Toshio

2013-01-01

Algorithms for estimating precipitation rates from spaceborne radar observations of apparent radar reflectivity depend on attenuation correction procedures. The algorithm suite for the Ku-band precipitation radar aboard the Tropical Rainfall Measuring Mission satellite is one such example. The well-known problem of nonuniform beam filling is a source of error in the estimates, especially in regions where intense deep convection occurs. The error is caused by unresolved horizontal variability in precipitation characteristics such as specific attenuation, rain rate, and effective reflectivity factor. This paper proposes the use of vertical decorrelation for correcting the nonuniform beam filling error developed under the assumption of a perfect vertical correlation. Empirical tests conducted using ground-based radar observations in the current simulation study show that decorrelation effects are evident in tilted convective cells. However, the problem of obtaining reasonable estimates of a governing parameter from the satellite data remains unresolved.

Bathymetric analysis of in-water upwelling-radiance data

NASA Astrophysics Data System (ADS)

Fay, Temple H.; Miller, H. V.; Clark, R. K.

1990-09-01

In June 1988, the Naval Ocean Research and Development Activity (NORDA) collected some "in-water" data using its Towed Underwater Pumping System (TUPS) in the near-shore waters off St. Andrews State Park, Shell Island, Florida. These in situ data include latitude; longitude; depth in meters; narrow-band upwelling at 465 nm, 507 nm, and 532 nm; broad-band downwelling collected at the surface; temperature; salinity; atid transmissivity. In this paper, we investigate the relationship between depth and the normalized upwelling irradiance (upwelling divided by downwelling) in the three bands. Algorithms used to calculate water depth from remotely sensed airborne and satellite multispectral data are applied to the TUPS data and results compared. The TEJPS data have the advantage over most aircraft- and satellite-collected data because they were collected over an essentially uniform bottom type (smooth sandy bottom with steady slope) and have no atmospheric contamination. A new algorithm for depth calculation is proposed.

Retrieval of ice cloud properties from Himawari-8 satellite measurements by Voronoi ice particle model

NASA Astrophysics Data System (ADS)

Letu, H.; Nagao, T. M.; Nakajima, T. Y.; Ishimoto, H.; Riedi, J.; Shang, H.

2017-12-01

Ice cloud property product from satellite measurements is applicable in climate change study, numerical weather prediction, as well as atmospheric study. Ishimoto et al., (2010) and Letu et al., (2016) developed a single scattering property of the highly irregular ice particle model, called the Voronoi model for developing ice cloud product of the GCOM-C satellite program. It is investigated that Voronoi model has a good performance on retrieval of the ice cloud properties by comparing it with other well-known scattering models. Cloud property algorithm (Nakajima et al., 1995, Ishida and Nakajima., 2009, Ishimoto et al., 2009, Letu et al., 2012, 2014, 2016) of the GCOM-C satellite program is improved to produce the Himawari-8/AHI cloud products based on the variation of the solar zenith angle. Himawari-8 is the new-generational geostationary meteorological satellite, which is successfully launched by the Japan Meteorological Agency (JMA) on 7 October 2014. In this study, ice cloud optical and microphysical properties are simulated from RSTAR radiative transfer code by using various model. Scattering property of the Voronoi model is investigated for developing the AHI ice cloud products. Furthermore, optical and microphysical properties of the ice clouds are retrieved from Himawari-8/AHI satellite measurements. Finally, retrieval results from Himawari-8/AHI are compared to MODIS-C6 cloud property products for validation of the AHI cloud products.

On-line Flagging of Anomalies and Adaptive Sequential Hypothesis Testing for Fine-feature Characterization of Geosynchronous Satellites

NASA Astrophysics Data System (ADS)

Chaudhary, A.; Payne, T.; Kinateder, K.; Dao, P.; Beecher, E.; Boone, D.; Elliott, B.

The objective of on-line flagging in this paper is to perform interactive assessment of geosynchronous satellites anomalies such as cross-tagging of a satellites in a cluster, solar panel offset change, etc. This assessment will utilize a Bayesian belief propagation procedure and will include automated update of baseline signature data for the satellite, while accounting for the seasonal changes. Its purpose is to enable an ongoing, automated assessment of satellite behavior through its life cycle using the photometry data collected during the synoptic search performed by a ground or space-based sensor as a part of its metrics mission. The change in the satellite features will be reported along with the probabilities of Type I and Type II errors. The objective of adaptive sequential hypothesis testing in this paper is to define future sensor tasking for the purpose of characterization of fine features of the satellite. The tasking will be designed in order to maximize new information with the least number of photometry data points to be collected during the synoptic search by a ground or space-based sensor. Its calculation is based on the utilization of information entropy techniques. The tasking is defined by considering a sequence of hypotheses in regard to the fine features of the satellite. The optimal observation conditions are then ordered in order to maximize new information about a chosen fine feature. The combined objective of on-line flagging and adaptive sequential hypothesis testing is to progressively discover new information about the features of a geosynchronous satellites by leveraging the regular but sparse cadence of data collection during the synoptic search performed by a ground or space-based sensor. Automated Algorithm to Detect Changes in Geostationary Satellite's Configuration and Cross-Tagging Phan Dao, Air Force Research Laboratory/RVB By characterizing geostationary satellites based on photometry and color photometry, analysts can evaluate satellite operational status and affirm its true identity. The process of ingesting photometry data and deriving satellite physical characteristics can be directed by analysts in a batch mode, meaning using a batch of recent data, or by automated algorithms in an on-line mode in which the assessment is updated with each new data point. Tools used for detecting change to satellite's status or identity, whether performed with a human in the loop or automated algorithms, are generally not built to detect with minimum latency and traceable confidence intervals. To alleviate those deficiencies, we investigate the use of Hidden Markov Models (HMM), in a Bayesian Network framework, to infer the hidden state (changed or unchanged) of a three-axis stabilized geostationary satellite using broadband and color photometry. Unlike frequentist statistics which exploit only the stationary statistics of the observables in the database, HMM also exploits the temporal pattern of the observables as well. The algorithm also operates in “learning” mode to gradually evolve the HMM and accommodate natural changes such as due to the seasonal dependence of GEO satellite's light curve. Our technique is designed to operate with missing color data. The version that ingests both panchromatic and color data can accommodate gaps in color photometry data. That attribute is important because while color indices, e.g. Johnson R and B, enhance the belief (probability) of a hidden state, in real world situations, flux data is collected sporadically in an untasked collect, and color data is limited and sometimes absent. Fluxes are measured with experimental error whose effect on the algorithm will be studied. Photometry data in the AFRL's Geo Color Photometry Catalog and Geo Observations with Latitudinal Diversity Simultaneously (GOLDS) data sets are used to simulate a wide variety of operational changes and identity cross tags. The algorithm is tested against simulated sequences of observed magnitudes, mimicking both the cadence of untasked SSN and other ground sensors, occasional operational changes and possible occurrence of cross tags of in-cluster satellites. We would like to show that the on-line algorithm can detect change; sometimes right after the first post-change data point is analyzed, for zero latency. We also want to show the unsupervised “learning” capability that allows the HMM to evolve with time without user's assistance. For example, the users are not required to “label” the true state of the data points.

Monitoring Fires from Space: a case study in transitioning from research to applications

NASA Astrophysics Data System (ADS)

Justice, C. O.; Giglio, L.; Vadrevu, K. P.; Csiszar, I. A.; Schroeder, W.; Davies, D.

2012-12-01

This paper discusses the heritage and relationships between science and applications in the context of global satellite-based fire monitoring. The development of algorithms for satellite-based fire detection has been supported primarily by NASA for the polar orbiters with a global focus, and initially by NOAA and more recently by EUMETSAT for the geostationary satellites, with a regional focus. As the feasibility and importance of space-based fire monitoring was recognized, satellite missions were designed to include fire detection capabilities. As a result, the algorithms and accuracy of the detections have improved. Due to the role of fire in the Earth System and its relevance to society, at each step in the development of the sensing capability the research has made a transition into fire-related applications to such an extent that there is now broad use of these data worldwide. The origin of the polar-orbiting satellite fire detection capability was with the AVHRR sensor beginning in the early 1980s, but was transformed with the launch of the EOS MODIS instruments, which included sensor characteristics specifically for fire detection. NASA gave considerable emphasis on the accuracy assessment of the fire detection and the development of fire characterization and burned area products from MODIS. Collaboration between the MODIS Fire Team and the RSAC USFS, initiated in the context of the Montana wildfires of 2001, prompted the development of a Rapid Response System for fire data and eventually led to operational use of MODIS data by the USFS for strategic fire monitoring. Building on this success, the Fire Information for Resource Management Systems (FIRMS) project was funded by NASA Applications to further develop products and services for the fire information community. The FIRMS was developed as a web-based geospatial tool, offering a range of geospatial data services, including SMS text messaging and is now widely used. This system, developed in the research domain, has now been successfully moved to an operational home at the UN FAO, as the Global Fire Information Management System (GFIMS). With a view to operational data continuity, the Suomi-NPP/JPSS VIIRS system was also designed with a fire detection capability, and is providing promising results for fire monitoring both from the standard operational production system and experimental product enhancements. International coordination on fire observations and outreach has been successfully developed under the GOFC GOLD program.

The combined use of the RST-FIRES algorithm and geostationary satellite data to timely detect fires

NASA Astrophysics Data System (ADS)

Filizzola, Carolina; Corrado, Rosita; Marchese, Francesco; Mazzeo, Giuseppe; Paciello, Rossana; Pergola, Nicola; Tramutoli, Valerio

2017-04-01

Timely detection of fires may enable a rapid contrast action before they become uncontrolled and wipe out entire forests. Remote sensing, especially based on geostationary satellite data, can be successfully used to this aim. Differently from sensors onboard polar orbiting platforms, instruments on geostationary satellites guarantee a very high temporal resolution (from 30 to 2,5 minutes) which may be usefully employed to carry out a "continuous" monitoring over large areas as well as to timely detect fires at their early stages. Together with adequate satellite data, an appropriate fire detection algorithm should be used. Over the last years, many fire detection algorithms have been just adapted from polar to geostationary sensors and, consequently, the very high temporal resolution of geostationary sensors is not exploited at all in tests for fire identification. In addition, even when specifically designed for geostationary satellite sensors, fire detection algorithms are frequently based on fixed thresholds tests which are generally set up in the most conservative way to avoid false alarm proliferation. The result is a low algorithm sensitivity which generally means that only large and/or extremely intense events are detected. This work describes the Robust Satellite Techniques for FIRES detection and monitoring (RST-FIRES) which is a multi-temporal change-detection technique trying to overcome the above mentioned issues. Its performance in terms of reliability and sensitivity was verified using data acquired by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor onboard the Meteosat Second Generation (MSG) geostationary platform. More than 20,000 SEVIRI images, collected during a four-year-collaboration with the Regional Civil Protection Departments and Local Authorities of two Italian regions, were used. About 950 near real-time ground and aerial checks of the RST-FIRES detections were performed. This study also demonstrates the added value of the RST-FIRES technique to detect starting/small fires and its sensitivity from 3 to 70 times higher than any other similar SEVIRI-based products.

Satellite-based estimation of evapotranspiration in typical forests of China

NASA Astrophysics Data System (ADS)

Wang, Y.; Li, R.

2017-12-01

Evapotranspiration (ET) is the key process affecting the interaction between land surface and atmosphere. Satellite remote sensing is the only feasible technique to monitor the terrestrial ET on large scale. Microwave Emissivity Difference Vegetation Index (EDVI) indicates vegetation water content and can be retrieved under both clear and cloudy sky. Based on EDVI, a quantitative algorithm for ET estimation in China was developed. In this study, we improved the EDVI-based ET algorithm by using the datasets from multiple platforms, including Moderate-Resolution Imaging Spectroradiometer (MODIS), Clouds and Earth's Radiation energy system (CERES) and European Centre for Medium-Range Weather Forecasts (ECMWF). As primary inputs of the algorithm, they are all independent from ground-based measurements. The improved algorithm was tested in three ChinaFlux forest sites, Dinghushan(DHS) subtropical evergreen broad-leaved forest site, Qianyanzhou(QYZ) subtropical man-planted forest site and Changbaishan(CBS) temperate deciduous broad-leaved coniferous mixed forest site. Validations against the in-situ measured ETobs from 2003 to 2005 showed that the EDVI-based algorithm has the capability to simulate midday ET within reasonable accuracies. In terms of the magnitude and seasonal cycle, the estimated ETcal are in very good agreement with the ETobs. The correlation coefficients(R) between ETcal and ETobs during midday vary from 0.51 to 0.80 over the study years, with the annual mean bias (relative bias) ranging from -53.02 Wm-2 (-26.46%) to 34.02 Wm-2 (+23.69%). At monthly scale, the R of monthly mean ETcal and ETobs can reach to 0.83, 0.93 and 0.82 at DHS, QYZ and CBS, with bias of +3.0%, -22.3% and -9.7%, respectively. Contamination from precipitation can partly affect the performances of this algorithm. Validation results generally become better after removing those samples in rainy days. The results indicate that this EDVI-based algorithm, driven completely by using satellite and reanalysis datasets, has a great potential for monitoring terrestrial ET in large spatial scale and under both clear and cloudy sky.

First Attempt of Orbit Determination of SLR Satellites and Space Debris Using Genetic Algorithms

NASA Astrophysics Data System (ADS)

Deleflie, F.; Coulot, D.; Descosta, R.; Fernier, A.; Richard, P.

2013-08-01

We present an orbit determination method based on genetic algorithms. Contrary to usual estimation methods mainly based on least-squares methods, these algorithms do not require any a priori knowledge of the initial state vector to be estimated. These algorithms can be applied when a new satellite is launched or for uncatalogued objects that appear in images obtained from robotic telescopes such as the TAROT ones. We show in this paper preliminary results obtained from an SLR satellite, for which tracking data acquired by the ILRS network enable to build accurate orbital arcs at a few centimeter level, which can be used as a reference orbit ; in this case, the basic observations are made up of time series of ranges, obtained from various tracking stations. We show as well the results obtained from the observations acquired by the two TAROT telescopes on the Telecom-2D satellite operated by CNES ; in that case, the observations are made up of time series of azimuths and elevations, seen from the two TAROT telescopes. The method is carried out in several steps: (i) an analytical propagation of the equations of motion, (ii) an estimation kernel based on genetic algorithms, which follows the usual steps of such approaches: initialization and evolution of a selected population, so as to determine the best parameters. Each parameter to be estimated, namely each initial keplerian element, has to be searched among an interval that is preliminary chosen. The algorithm is supposed to converge towards an optimum over a reasonable computational time.

A Novel Method for Satellite Maneuver Prediction

NASA Astrophysics Data System (ADS)

Shabarekh, C.; Kent-Bryant, J.; Keselman, G.; Mitidis, A.

2016-09-01

A space operations tradecraft consisting of detect-track-characterize-catalog is insufficient for maintaining Space Situational Awareness (SSA) as space becomes increasingly congested and contested. In this paper, we apply analytical methodology from the Geospatial-Intelligence (GEOINT) community to a key challenge in SSA: predicting where and when a satellite may maneuver in the future. We developed a machine learning approach to probabilistically characterize Patterns of Life (PoL) for geosynchronous (GEO) satellites. PoL are repeatable, predictable behaviors that an object exhibits within a context and is driven by spatio-temporal, relational, environmental and physical constraints. An example of PoL are station-keeping maneuvers in GEO which become generally predictable as the satellite re-positions itself to account for orbital perturbations. In an earlier publication, we demonstrated the ability to probabilistically predict maneuvers of the Galaxy 15 (NORAD ID: 28884) satellite with high confidence eight days in advance of the actual maneuver. Additionally, we were able to detect deviations from expected PoL within hours of the predicted maneuver [6]. This was done with a custom unsupervised machine learning algorithm, the Interval Similarity Model (ISM), which learns repeating intervals of maneuver patterns from unlabeled historical observations and then predicts future maneuvers. In this paper, we introduce a supervised machine learning algorithm that works in conjunction with the ISM to produce a probabilistic distribution of when future maneuvers will occur. The supervised approach uses a Support Vector Machine (SVM) to process the orbit state whereas the ISM processes the temporal intervals between maneuvers and the physics-based characteristics of the maneuvers. This multiple model approach capitalizes on the mathematical strengths of each respective algorithm while incorporating multiple features and inputs. Initial findings indicate that the combined approach can predict 70% of maneuver times within 3 days of a true maneuver time and 22% of maneuver times within 24 hours of a maneuver. We have also been able to detect deviations from expected maneuver patterns up to a week in advance.

Lower Tropospheric Ozone Retrievals from Infrared Satellite Observations Using a Self-Adapting Regularization Method

NASA Astrophysics Data System (ADS)

Eremenko, M.; Sgheri, L.; Ridolfi, M.; Dufour, G.; Cuesta, J.

2017-12-01

Lower tropospheric ozone (O3) retrievals from nadir sounders is challenging due to the lack of vertical sensitivity of the measurements and towards the lowest layers. If improvements have been made during the last decade, it is still important to explore possibilities to improve the retrieval algorithms themselves. O3 retrieval from nadir satellite observations is an ill-conditioned problem, which requires regularization using constraint matrices. Up to now, most of the retrieval algorithms rely on a fixed constraint. The constraint is determined and fixed beforehand, on the basis of sensitivity tests. This does not allow ones to take advantage of the entire capabilities of the satellite measurements, which vary with the thermal conditions of the observed scenes. To overcome this limitation, we developed a self-adapting and altitude-dependent regularization scheme. A crucial step is the choice of the strength of the constraint. This choice is done during an iterative process and depends on the measurement errors and on the sensitivity of the measurements to the target parameters at the different altitudes. The challenge is to limit the use of a priori constraints to the minimal amount needed to perform the inversion. The algorithm has been tested on synthetic observations matching the future IASI-NG satellite instrument. IASI-NG measurements are simulated on the basis of O3 concentrations taken from an atmospheric model and retrieved using two retrieval schemes (the standard and self-adapting ones). Comparison of the results shows that the sensitivity of the observations to the O3 amount in the lowest layers (given by the degrees of freedom for the solution) is increased, which allows a better description of the ozone distribution, especially in the case of large ozone plumes. Biases are reduced and the spatial correlation is improved. Tentative of application to real observations from IASI, currently onboard the Metop satellite will also be presented.

Hydrologic Evaluation of Integrated Multi-satellite Retrivals for GPM over Nanliu River Basin in Southern China

NASA Astrophysics Data System (ADS)

Zhenqing, L.; Sheng, C.; Chaoying, H.

2017-12-01

The core satellite of Global Precipitation Measurement (GPM) mission was launched on 27 February2014 with two core sensors dual-frequency precipitation radar (DPR) and microwave imager (GMI). The algorithm of Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG) blends the advantages of currently most popular satellite-based quantitative precipitation estimates (QPE) algorithms, i.e. TRMM Multi-satellite Precipitation Analysis (TMPA), Climate Prediction Center morphing technique (CMORPH) ADDIN EN.CITE ADDIN EN.CITE.DATA , Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS).Therefore, IMERG is deemed to be the state-of-art precipitation product with high spatio-temporal resolution of 0.1°/30min. The real-time and post real-time IMERG products are now available online at https://stormpps.gsfc.nasa.gov/storm. Early studies about assessment of IMERG with gauge observations or analysis products show that the current version GPM Day-1 product IMERG demonstrates promising performance over China [1], Europe [2], and United States [3]. However, few studies are found to study the IMERG' potentials of hydrologic utility.In this study, the real-time and final run post real-time IMERG products are hydrologically evaluated with gauge analysis product as reference over Nanliu River basin (Fig.1) in Southern China since March 2014 to February 2017 with Xinanjiang model. Statistics metrics Relative Bias (RB), Root-Mean-Squared Error (RMSE), Correlation Coefficient (CC), Probability Of Detection (POD), False Alarm Ratio (FAR), Critical Success Index (CSI), and Nash-Sutcliffe (NSCE) index will be used to compare the stream flow simulated with IMERG to the observed stream flow. This timely hydrologic evaluation is expected to offer insights into IMERG' potentials in hydrologic utility and thus provide useful feedback to the IMERG algorithm developers and the hydrologic users.

Near-optimal reconfiguration and maintenance of close spacecraft formations.

PubMed

Lovell, T A; Tragesser, S G

2004-05-01

This paper investigates orbit guidance algorithms for formation flying experiments. The relative motion of one satellite about a reference satellite is formulated in terms of a set of parameters that clearly describe the size, shape, and orientation of the formation. A nominal three-impulse burn maneuver algorithm is presented that is applicable for both reconfiguration and maintenance of spacecraft formations. Two methods of implementing the algorithm are discussed, one involving fixed times between each burn and one allowing the wait times to vary. The implications of employing four or more impulses for maneuvers are assessed. Examples applying the algorithm to various formation scenarios are presented, along with practical implications of each result.

Shadow Detection from Very High Resoluton Satellite Image Using Grabcut Segmentation and Ratio-Band Algorithms

NASA Astrophysics Data System (ADS)

Kadhim, N. M. S. M.; Mourshed, M.; Bray, M. T.

2015-03-01

Very-High-Resolution (VHR) satellite imagery is a powerful source of data for detecting and extracting information about urban constructions. Shadow in the VHR satellite imageries provides vital information on urban construction forms, illumination direction, and the spatial distribution of the objects that can help to further understanding of the built environment. However, to extract shadows, the automated detection of shadows from images must be accurate. This paper reviews current automatic approaches that have been used for shadow detection from VHR satellite images and comprises two main parts. In the first part, shadow concepts are presented in terms of shadow appearance in the VHR satellite imageries, current shadow detection methods, and the usefulness of shadow detection in urban environments. In the second part, we adopted two approaches which are considered current state-of-the-art shadow detection, and segmentation algorithms using WorldView-3 and Quickbird images. In the first approach, the ratios between the NIR and visible bands were computed on a pixel-by-pixel basis, which allows for disambiguation between shadows and dark objects. To obtain an accurate shadow candidate map, we further refine the shadow map after applying the ratio algorithm on the Quickbird image. The second selected approach is the GrabCut segmentation approach for examining its performance in detecting the shadow regions of urban objects using the true colour image from WorldView-3. Further refinement was applied to attain a segmented shadow map. Although the detection of shadow regions is a very difficult task when they are derived from a VHR satellite image that comprises a visible spectrum range (RGB true colour), the results demonstrate that the detection of shadow regions in the WorldView-3 image is a reasonable separation from other objects by applying the GrabCut algorithm. In addition, the derived shadow map from the Quickbird image indicates significant performance of the ratio algorithm. The differences in the characteristics of the two satellite imageries in terms of spatial and spectral resolution can play an important role in the estimation and detection of the shadow of urban objects.

Remote assessment of ocean color for interpretation of satellite visible imagery: A review

NASA Technical Reports Server (NTRS)

Gordon, H. R.; Morel, A. Y.

1983-01-01

An assessment is presented of the state-of-the-art of remote, (satellite-based) Coastal Zone Color (CZCS) Scanning of color variations in the ocean due to phytoplankton. Attention is given to physical problems associated with ocean color remote sensing, in-water algorithms for the correction of atmospheric effects, constituent retrieval algorithms and application of the algorithms to CZCS imagery. The applicability of CZCS to both near-coast and mid-ocean waters is considered, and it is concluded that while differences between the two environments are complex, universal algorithms can be used for the case of mid-ocean waters, and site-specific algorithms are adequate for CZCS imaging of the near-coast oceanic environment. A short description of CVCS and some sample photographs are provided in an appendix.

Examination of Regional Trends in Cloud Properties over Surface Sites Derived from MODIS and AVHRR using the CERES Cloud Algorithm

NASA Astrophysics Data System (ADS)

Smith, W. L., Jr.; Minnis, P.; Bedka, K. M.; Sun-Mack, S.; Chen, Y.; Doelling, D. R.; Kato, S.; Rutan, D. A.

2017-12-01

Recent studies analyzing long-term measurements of surface insolation at ground sites suggest that decadal-scale trends of increasing (brightening) and decreasing (dimming) downward solar flux have occurred at various times over the last century. Regional variations have been reported that range from near 0 Wm-2/decade to as large as 9 Wm-2/decade depending on the location and time period analyzed. The more significant trends have been attributed to changes in overhead clouds and aerosols, although quantifying their relative impacts using independent observations has been difficult, owing in part to a lack of consistent long-term measurements of cloud properties. This paper examines new satellite based records of cloud properties derived from MODIS (2000-present) and AVHRR (1981- present) data to infer cloud property trends over a number of surface radiation sites across the globe. The MODIS cloud algorithm was developed for the NASA Clouds and the Earth's Radiant Energy System (CERES) project to provide a consistent record of cloud properties to help improve broadband radiation measurements and to better understand cloud radiative effects. The CERES-MODIS cloud algorithm has been modified to analyze other satellites including the AVHRR on the NOAA satellites. Compared to MODIS, obtaining consistent cloud properties over a long period from AVHRR is a much more significant challenge owing to the number of different satellites, instrument calibration uncertainties, orbital drift and other factors. Nevertheless, both the MODIS and AVHRR cloud properties will be analyzed to determine trends, and their level of consistency and correspondence with surface radiation trends derived from the ground-based radiometer data. It is anticipated that this initial study will contribute to an improved understanding of surface solar radiation trends and their relationship to clouds.

Improvements and Extensions for Joint Polar Satellite System Algorithms

NASA Astrophysics Data System (ADS)

Grant, K. D.

2016-12-01

The National Oceanic and Atmospheric Administration (NOAA) and National Aeronautics and Space Administration (NASA) are jointly acquiring the next-generation civilian weather satellite system: the Joint Polar Satellite System (JPSS). JPSS replaced the afternoon orbit component and ground processing of the old POES system managed by NOAA. JPSS satellites carry sensors designed to collect meteorological, oceanographic, climatological, and solar-geophysical observations of the earth, atmosphere, and space. The ground processing system for JPSS is the Common Ground System (CGS), and provides command, control, and communications (C3), data processing and product delivery. CGS's data processing capability provides environmental data products (Sensor Data Records (SDRs) and Environmental Data Records (EDRs)) to the NOAA Satellite Operations Facility. The first satellite in the JPSS constellation, S-NPP, was launched in October 2011. The second satellite, JPSS-1, is scheduled for launch in January 2017. During a satellite's calibration and validation (Cal/Val) campaign, numerous algorithm updates occur. Changes identified during Cal/Val become available for implementation into the operational system for both S-NPP and JPSS-1. In addition, new capabilities, such as higher spectral and spatial resolution, will be exercised on JPSS-1. This paper will describe changes to current algorithms and products as a result of S-NPP Cal/Val and related initiatives for improved capabilities. Improvements include Cross Track Infrared Sounder high spectral processing, extended spectral and spatial ranges for Ozone Mapping and Profiler Suite ozone Total Column and Nadir Profiles, and updates to Vegetation Index, Snow Cover, Active Fires, Suspended Matter, and Ocean Color. Updates will include Sea Surface Temperature, Cloud Mask, Cloud Properties, and other improvements.

A mission-oriented orbit design method of remote sensing satellite for region monitoring mission based on evolutionary algorithm

NASA Astrophysics Data System (ADS)

Shen, Xin; Zhang, Jing; Yao, Huang

2015-12-01

Remote sensing satellites play an increasingly prominent role in environmental monitoring and disaster rescue. Taking advantage of almost the same sunshine condition to same place and global coverage, most of these satellites are operated on the sun-synchronous orbit. However, it brings some problems inevitably, the most significant one is that the temporal resolution of sun-synchronous orbit satellite can't satisfy the demand of specific region monitoring mission. To overcome the disadvantages, two methods are exploited: the first one is to build satellite constellation which contains multiple sunsynchronous satellites, just like the CHARTER mechanism has done; the second is to design non-predetermined orbit based on the concrete mission demand. An effective method for remote sensing satellite orbit design based on multiobjective evolution algorithm is presented in this paper. Orbit design problem is converted into a multi-objective optimization problem, and a fast and elitist multi-objective genetic algorithm is utilized to solve this problem. Firstly, the demand of the mission is transformed into multiple objective functions, and the six orbit elements of the satellite are taken as genes in design space, then a simulate evolution process is performed. An optimal resolution can be obtained after specified generation via evolution operation (selection, crossover, and mutation). To examine validity of the proposed method, a case study is introduced: Orbit design of an optical satellite for regional disaster monitoring, the mission demand include both minimizing the average revisit time internal of two objectives. The simulation result shows that the solution for this mission obtained by our method meet the demand the users' demand. We can draw a conclusion that the method presented in this paper is efficient for remote sensing orbit design.

Overview of geostationary ocean color imager (GOCI) and GOCI data processing system (GDPS)

NASA Astrophysics Data System (ADS)

Ryu, Joo-Hyung; Han, Hee-Jeong; Cho, Seongick; Park, Young-Je; Ahn, Yu-Hwan

2012-09-01

GOCI, the world's first geostationary ocean color satellite, provides images with a spatial resolution of 500 m at hourly intervals up to 8 times a day, allowing observations of short-term changes in the Northeast Asian region. The GOCI Data Processing System (GDPS), a specialized data processing software for GOCI, was developed for real-time generation of various products. This paper describes GOCI characteristics and GDPS workflow/products, so as to enable the efficient utilization of GOCI. To provide quality images and data, atmospheric correction and data analysis algorithms must be improved through continuous Cal/Val. GOCI-II will be developed by 2018 to facilitate in-depth studies on geostationary ocean color satellites.

Computation of Solar Radiative Fluxes by 1D and 3D Methods Using Cloudy Atmospheres Inferred from A-train Satellite Data

NASA Technical Reports Server (NTRS)

Barker, Howard W.; Kato, Serji; Wehr, T.

2012-01-01

The main point of this study was to use realistic representations of cloudy atmospheres to assess errors in solar flux estimates associated with 1D radiative transfer models. A scene construction algorithm, developed for the EarthCARE satellite mission, was applied to CloudSat, CALIPSO, and MODIS satellite data thus producing 3D cloudy atmospheres measuring 60 km wide by 13,000 km long at 1 km grid-spacing. Broadband solar fluxes and radiances for each (1 km)2 column where then produced by a Monte Carlo photon transfer model run in both full 3D and independent column approximation mode (i.e., a 1D model).

Ship and satellite bio-optical research in the California Bight

NASA Technical Reports Server (NTRS)

Smith, R. C.; Baker, K. S.

1982-01-01

Mesoscale biological patterns and processes in productive coastal waters were studied. The physical and biological processes leading to chlorophyll variability were investigated. The ecological and evolutionary significance of this variability, and its relation to the prediction of fish recruitment and marine mammal distributions was studied. Seasonal primary productivity (using chlorophyll as an indication of phytoplankton biomass) for the entire Southern California Bight region was assessed. Complementary and contemporaneous ship and satellite (Nimbus 7-CZCS) bio-optical data from the Southern California Bight and surrounding waters were obtained and analyzed. These data were also utilized for the development of multi-platform sampling strategies and the optimization of algorithms for the estimation of phytoplankton biomass and primary production from satellite imagery.

Retrieval of total water vapour in the Arctic using microwave humidity sounders

NASA Astrophysics Data System (ADS)

Cristian Scarlat, Raul; Melsheimer, Christian; Heygster, Georg

2018-04-01

Quantitative retrievals of atmospheric water vapour in the Arctic present numerous challenges because of the particular climate characteristics of this area. Here, we attempt to build upon the work of Melsheimer and Heygster (2008) to retrieve total atmospheric water vapour (TWV) in the Arctic from satellite microwave radiometers. While the above-mentioned algorithm deals primarily with the ice-covered central Arctic, with this work we aim to extend the coverage to partially ice-covered and ice-free areas. By using modelled values for the microwave emissivity of the ice-free sea surface, we develop two sub-algorithms using different sets of channels that deal solely with open-ocean areas. The new algorithm extends the spatial coverage of the retrieval throughout the year but especially in the warmer months when higher TWV values are frequent. The high TWV measurements over both sea-ice and open-water surfaces are, however, connected to larger uncertainties as the retrieval values are close to the instrument saturation limits.This approach allows us to apply the algorithm to regions where previously no data were available and ensures a more consistent physical analysis of the satellite measurements by taking into account the contribution of the surface emissivity to the measured signal.

Improvement of retrieval algorithms for severe air pollution

NASA Astrophysics Data System (ADS)

Mukai, Sonoyo; Sano, Itaru; Nakata, Makiko

2016-10-01

Increased emissions of anthropogenic aerosols associated with economic growth can lead to increased concentrations of hazardous air pollutants. Furthermore, dust storms or biomass burning plumes can cause serious environmental hazards, yet their aerosol properties are poorly understood. Our research group has worked on the development of an efficient algorithm for aerosol retrieval during hazy episodes (dense concentrations of atmospheric aerosols). It is noted that near UV measurements are available for detection of carbonaceous aerosols. The biomass burning aerosols (BBA) due to large-scale forest fires and/or burn agriculture exacerbated the severe air pollution. It is known that global warming and climate change have caused increasing instances of forest fires, which have in turn accelerated climate change. It is well known that this negative cycle decreases the quality of the global environment and human health. The Japan Aerospace Exploration Agency (JAXA) has been developing a new Earth observing system, the GCOM (Global Change Observation Mission) project, which consists of two satellite series: GCOM-W1 and GCOM-C1. The first GCOM-C satellite will board the SGLI (second generation GLI [global imager]) to be launched in early 2017. The SGLI is capable of multi-channel (19) observation, including a near UV channel (0.380 μm) and two polarization channels at red and near-infrared wavelengths of 0.67 and 0.87 μm. Thus, global aerosol retrieval will be achieved with simultaneous polarization and total radiance. In this study, algorithm improvement for aerosol remote sensing, especially of BBA episodes, is examined using Terra/MODIS measurements from 2003, when the GLI and POLDER-2 sensors were working onboard the Japanese satellite ADEOS-2.

An efficient solution of real-time data processing for multi-GNSS network

NASA Astrophysics Data System (ADS)

Gong, Xiaopeng; Gu, Shengfeng; Lou, Yidong; Zheng, Fu; Ge, Maorong; Liu, Jingnan

2017-12-01

Global navigation satellite systems (GNSS) are acting as an indispensable tool for geodetic research and global monitoring of the Earth, and they have been rapidly developed over the past few years with abundant GNSS networks, modern constellations, and significant improvement in mathematic models of data processing. However, due to the increasing number of satellites and stations, the computational efficiency becomes a key issue and it could hamper the further development of GNSS applications. In this contribution, this problem is overcome from the aspects of both dense linear algebra algorithms and GNSS processing strategy. First, in order to fully explore the power of modern microprocessors, the square root information filter solution based on the blocked QR factorization employing as many matrix-matrix operations as possible is introduced. In addition, the algorithm complexity of GNSS data processing is further decreased by centralizing the carrier-phase observations and ambiguity parameters, as well as performing the real-time ambiguity resolution and elimination. Based on the QR factorization of the simulated matrix, we can conclude that compared to unblocked QR factorization, the blocked QR factorization can greatly improve processing efficiency with a magnitude of nearly two orders on a personal computer with four 3.30 GHz cores. Then, with 82 globally distributed stations, the processing efficiency is further validated in multi-GNSS (GPS/BDS/Galileo) satellite clock estimation. The results suggest that it will take about 31.38 s per epoch for the unblocked method. While, without any loss of accuracy, it only takes 0.50 and 0.31 s for our new algorithm per epoch for float and fixed clock solutions, respectively.

Detection of Unknown LEO Satellite Using Radar Measurements

NASA Astrophysics Data System (ADS)

Kamensky, S.; Samotokhin, A.; Khutorovsky, Z.; Alfriend, T.

While processing of the radar information aimed at satellite catalog maintenance some measurements do not correlate with cataloged and tracked satellites. These non-correlated measurements participate in the detection (primary orbit determination) of new (not cataloged) satellites. The satellite is considered newly detected when it is missing in the catalog and the primary orbit determination on the basis of the non-correlated measurements provides the accuracy sufficient for reliable correlation of future measurements. We will call this the detection condition. One non-correlated measurement in real conditions does not have enough accuracy and thus does not satisfy the detection condition. Two measurements separated by a revolution or more normally provides orbit determination with accuracy sufficient for selection of other measurements. However, it is not always possible to say with high probability (close to 1) that two measurements belong to one satellite. Three measurements for different revolutions, which are included into one orbit, have significantly higher chances to belong to one satellite. Thus the suggested detection (primary orbit determination) algorithm looks for three uncorrelated measurements in different revolutions for which we can determine the orbit inscribing them. The detection procedure based on search for the triplets is rather laborious. Thus only relatively high efficiency can be the reason for its practical implementation. The work presents the detailed description of the suggested detection procedure based on the search for triplets of uncorrelated measurements (for radar measurements). The break-ups of the tracked satellites provide the most difficult conditions for the operation of the detection algorithm and reveal explicitly its characteristics. The characteristics of time efficiency and reliability of the detected orbits are of maximum interest. Within this work we suggest to determine these characteristics using simulation of break-ups with further acquisition of measurements generated by the fragments. In particular, using simulation we can not only evaluate the characteristics of the algorithm but adjust its parameters for certain conditions: the orbit of the fragmented satellite, the features of the break-up, capabilities of detection radars etc. We describe the algorithm performing the simulation of radar measurements produced by the fragments of the parent satellite. This algorithm accounts of the basic factors affecting the characteristics of time efficiency and reliability of the detection. The catalog maintenance algorithm includes two major components detection and tracking. These are two processes permanently interacting with each other. This is actually in place for the processing of real radar data. The simulation must take this into account since one cannot obtain reliable characteristics of detection procedure simulating only this process. Thus we simulated both processes in their interaction. The work presents the results of simulation for the simplest case of a break-up in near-circular orbit with insignificant atmospheric drag. The simulations show rather high efficiency. We demonstrate as well that the characteristics of time efficiency and reliability of determined orbits essentially depend on the density of the observed break-up fragments.

Spring green-up date derived from GIMMS3g and SPOT-VGT NDVI of winter wheat cropland in the North China Plain

NASA Astrophysics Data System (ADS)

Liu, Zhengjia; Wu, Chaoyang; Liu, Yansui; Wang, Xiaoyue; Fang, Bin; Yuan, Wenping; Ge, Quansheng

2017-08-01

Satellite temporal resolution affects the fitting accuracy of vegetation growth curves. However, there are few studies that evaluate the impact of different satellite data (including temporal resolution and time series change) on spring green-up date (GUD) extraction. In this study, four GUD algorithms and two different temporal resolution satellite data (GIMMS3g during 1982-2013 and SPOT-VGT during 1999-2013) were used to investigate winter wheat GUD in the North China Plain. Four GUD algorithms included logistic-NDVI (normalized difference vegetation index), logistic-cumNDVI (cumulative NDVI), polynomial-NDVI and polynomial-cumNDVI algorithms. All algorithms and data were first regrouped into eight controlled cases. At site scale, we evaluated the performance of each case using correlation coefficient (r), bias and root mean square error (RMSE). We further compared spatial patterns and inter-annual trends of GUD inferred from different algorithms, and then analyzed the difference between GIMMS3g-based GUD and SPOT-VGT-based GUD. Our results showed that all satellite-based GUD were correlated with observations with r ranging from 0.32 to 0.57 (p < 0.01). SPOT-VGT-based GUD generally had better correlations with observed GUD than those of GIMMS3g. Spatially, SPOT-VGT-based GUD performed more reasonable spatial distributions. Inter-annual regional averaged satellite-based GUD presented overall advanced trends during 1982-2013 (0.3-2.0 days/decade) while delayed trends were observed during 1999-2013 (1.7-7.4 days/decade for GIMMS3g and 3.8-7.4 days/decade for SPOT-VGT). However, their significance levels were highly dependent on the data and algorithms used. Our findings suggest cautions on previous results of inter-annual variability of phenology from a single data/method.

Detecting Climate Variability in Tropical Rainfall

NASA Astrophysics Data System (ADS)

Berg, W.

2004-05-01

A number of satellite and merged satellite/in-situ rainfall products have been developed extending as far back as 1979. While the availability of global rainfall data covering over two decades and encompassing two major El Niño events is a valuable resource for a variety of climate studies, significant differences exist between many of these products. Unfortunately, issues such as availability often determine the use of a product for a given application instead of an understanding of the strengths and weaknesses of the various products. Significant efforts have been made to address the impact of sparse sampling by satellite sensors of variable rainfall processes by merging various satellite and in-situ rainfall products. These combine high spatial and temporal frequency satellite infrared data with higher quality passive microwave observations and rain gauge observations. Combining such an approach with spatial and temporal averaging of the data can reduce the large random errors inherent in satellite rainfall estimates to very small levels. Unfortunately, systematic biases can and do result in artificial climate signals due to the underconstrained nature of the rainfall retrieval problem. Because all satellite retrieval algorithms make assumptions regarding the cloud structure and microphysical properties, systematic changes in these assumed parameters between regions and/or times results in regional and/or temporal biases in the rainfall estimates. These biases tend to be relatively small compared to random errors in the retrieval, however, when random errors are reduced through spatial and temporal averaging for climate applications, they become the dominant source of error. Whether or not such biases impact the results for climate studies is very much dependent on the application. For example, all of the existing satellite rainfall products capture the increased rainfall in the east Pacific associated with El Niño, however, the resulting tropical response to El Niño is substantially smaller due to decreased rainfall in the west Pacific partially canceling increases in the central and east Pacific. These differences are not limited to the long-term merged rainfall products using infrared data, but are also exist in state-of-the-art rainfall retrievals from the active and passive microwave sensors on board the Tropical Rainfall Measuring Mission (TRMM). For example, large differences exist in the response of tropical mean rainfall retrieved from the TRMM microwave imager (TMI) 2A12 algorithm and the precipitation radar (PR) 2A25 algorithm to the 1997/98 El Niño. To assist scientists attempting to wade through the vast array of climate rainfall products currently available, and to help them determine whether systematic biases in these rainfall products impact the conclusions of a given study, we have developed a Climate Rainfall Data Center (CRDC). The CRDC web site (rain.atmos.colostate.edu/CRDC) provides climate researchers information on the various rainfall datasets available as well as access to experts in the field of satellite rainfall retrievals to assist them in the appropriate selection and use of climate rainfall products.

Evaluation of MODIS columnar aerosol retrievals using AERONET in semi-arid Nevada and California, U.S.A., during the summer of 2012

NASA Astrophysics Data System (ADS)

Loría-Salazar, S. Marcela; Holmes, Heather A.; Patrick Arnott, W.; Barnard, James C.; Moosmüller, Hans

2016-11-01

Satellite characterization of local aerosol pollution is desirable because of the potential for broad spatial coverage, enabling transport studies of pollution from major sources, such as biomass burning events. However, retrieval of quantitative measures of air pollution such as Aerosol Optical Depth (AOD) from satellite measurements is challenging over land because the underlying surface albedo may be heterogeneous in space and time. Ground-based sunphotometer measurements of AOD are unaffected by surface albedo and are crucial in enabling evaluation, testing, and further development of satellite instruments and retrieval algorithms. Columnar aerosol optical properties from ground-based sunphotometers (Cimel CE-318) as part of AERONET and MODIS aerosol retrievals from Aqua and Terra satellites were compared over semi-arid California and Nevada during the summer season of 2012. Sunphotometer measurements were used as a 'ground truth' to evaluate the current state of satellite retrievals in this spatiotemporal domain. Satellite retrieved (MODIS Collection 6) AOD showed the presence of wildfires in northern California during August. During the study period, the dark-target (DT) retrieval algorithm appears to overestimate AERONET AOD by an average factor of 3.85 in the entire study domain. AOD from the deep-blue (DB) algorithm overestimates AERONET AOD by an average factor of 1.64. Low AOD correlation was also found between AERONET, DT, and DB retrievals. Smoke from fires strengthened the aerosol signal, but MODIS versus AERONET AOD correlation hardly increased during fire events (r2∼0.1-0.2 during non-fire periods and r2∼0-0.31 during fire periods). Furthermore, aerosol from fires increased the normalized mean bias (NMB) of MODIS retrievals of AOD (NMB∼23%-154% for non-fire periods and NMB∼77%-196% for fire periods). Ångström Extinction Exponent (AEE) from DB for both Terra and Aqua did not correlate with AERONET observations. High surface reflectance and incorrect aerosol physical parametrizations may still be affecting the DT and DB MODIS AOD retrievals in the semi-arid western U.S.

Pre-Launch Algorithms and Risk Reduction in Support of the Geostationary Lightning Mapper for GOES-R and Beyond

NASA Technical Reports Server (NTRS)

Goodman, Steven; Blakeslee, Richard; Koshak, William; Petersen, Walt; Buechler, Dennis; Krehbiel, Paul; Gatlin, Patrick; Zubrick, Steven

2008-01-01

The Geostationary Lightning Mapper (GLM) is a single channel, near-IR optical transient event detector, used to detect, locate and measure total lightning activity over the full-disk as part of a 3-axis stabilized, geostationary weather satellite system. The next generation NOAA Geostationary Operational Environmental Satellite (GOES-R) series with a planned launch in 2014 will carry a GLM that will provide continuous day and night observations of lightning from the west coast of Africa (GOES-E) to New Zealand (GOES-W) when the constellation is fully operational.The mission objectives for the GLM are to 1) provide continuous,full-disk lightning measurements for storm warning and Nowcasting, 2) provide early warning of tornadic activity, and 3) accumulate a long-term database to track decadal changes of lightning. The GLM owes its heritage to the NASA Lightning Imaging Sensor (1997-Present) and the Optical Transient Detector (1995-2000), which were developed for the Earth Observing System and have produced a combined 13 year data record of global lightning activity. Instrument formulation studies were completed in March 2007 and the implementation phase to develop a prototype model and up to four flight units is expected to begin in latter part of the year. In parallel with the instrument development, a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2B algorithms and applications. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) sate]lite and regional test beds (e.g., Lightning Mapping Arrays in North Alabama and the Washington DC Metropolitan area) are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. Real time lightning mapping data provided to selected National Weather Service forecast offices in Southern and Eastern Region are also improving our understanding of the application of these data in the severe storm warning process and help to accelerate the development of the pre-launch algorithms and Nowcasting applications. Abstract for the 3 rd Conference on Meteorological

Schedule Optimization of Imaging Missions for Multiple Satellites and Ground Stations Using Genetic Algorithm

NASA Astrophysics Data System (ADS)

Lee, Junghyun; Kim, Heewon; Chung, Hyun; Kim, Haedong; Choi, Sujin; Jung, Okchul; Chung, Daewon; Ko, Kwanghee

2018-04-01

In this paper, we propose a method that uses a genetic algorithm for the dynamic schedule optimization of imaging missions for multiple satellites and ground systems. In particular, the visibility conflicts of communication and mission operation using satellite resources (electric power and onboard memory) are integrated in sequence. Resource consumption and restoration are considered in the optimization process. Image acquisition is an essential part of satellite missions and is performed via a series of subtasks such as command uplink, image capturing, image storing, and image downlink. An objective function for optimization is designed to maximize the usability by considering the following components: user-assigned priority, resource consumption, and image-acquisition time. For the simulation, a series of hypothetical imaging missions are allocated to a multi-satellite control system comprising five satellites and three ground stations having S- and X-band antennas. To demonstrate the performance of the proposed method, simulations are performed via three operation modes: general, commercial, and tactical.

Broad-search algorithms for finding triple-and quadruple-satellite-aided captures at Jupiter from 2020 to 2080

NASA Astrophysics Data System (ADS)

Lynam, Alfred E.

2015-04-01

Multiple-satellite-aided capture is a -efficient technique for capturing a spacecraft into orbit at Jupiter. However, finding the times when the Galilean moons of Jupiter align such that three or four of them can be encountered in a single pass is difficult using standard astrodynamics algorithms such as Lambert's problem. In this paper, we present simple but powerful techniques that simplify the dynamics and geometry of the Galilean satellites so that many of these triple- and quadruple-satellite-aided capture sequences can be found quickly over an extended 60-year time period from 2020 to 2080. The techniques find many low-fidelity trajectories that could be used as initial guesses for future high-fidelity optimization. Results indicate the existence of approximately 3,100 unique triple-satellite-aided capture trajectories and 6 unique quadruple-satellite-aided capture trajectories during the 60-year time period. The entire search takes less than one minute of computational time.

Using Ground-Based Measurements and Retrievals to Validate Satellite Data

NASA Technical Reports Server (NTRS)

Dong, Xiquan

2002-01-01

The proposed research is to use the DOE ARM ground-based measurements and retrievals as the ground-truth references for validating satellite cloud results and retrieving algorithms. This validation effort includes four different ways: (1) cloud properties on different satellites, therefore different sensors, TRMM VIRS and TERRA MODIS; (2) cloud properties at different climatic regions, such as DOE ARM SGP, NSA, and TWP sites; (3) different cloud types, low and high level cloud properties; and (4) day and night retrieving algorithms. Validation of satellite-retrieved cloud properties is very difficult and a long-term effort because of significant spatial and temporal differences between the surface and satellite observing platforms. The ground-based measurements and retrievals, only carefully analyzed and validated, can provide a baseline for estimating errors in the satellite products. Even though the validation effort is so difficult, a significant progress has been made during the proposed study period, and the major accomplishments are summarized in the follow.

Development of thunderstorm monitoring technologies and algorithms by integration of radar, sensors, and satellite images

NASA Astrophysics Data System (ADS)

Adzhieva, Aida A.; Shapovalov, Vitaliy A.; Boldyreff, Anton S.

2017-10-01

In the context of rising the frequency of natural disasters and catastrophes humanity has to develop methods and tools to ensure safe living conditions. Effectiveness of preventive measures greatly depends on quality and lead time of the forecast of disastrous natural phenomena, which is based on the amount of knowledge about natural hazards, their causes, manifestations, and impact. To prevent them it is necessary to get complete and comprehensive information about the extent of spread and severity of natural processes that can act within a defined territory. For these purposes the High Mountain Geophysical Institute developed the automated workplace for mining, analysis and archiving of radar, satellite, lightning sensors information and terrestrial (automatic weather station) weather data. The combination and aggregation of data from different sources of meteorological data provides a more informativity of the system. Satellite data shows the global cloud region in visible and infrared ranges, but have an uncertainty in terms of weather events and large time interval between the two periods of measurements, which complicates the use of this information for very short range forecasts of weather phenomena. Radar and lightning sensors data provide the detection of weather phenomena and their localization on the background of the global pattern of cloudiness in the region and have a low period measurement of atmospheric phenomena (hail, thunderstorms, showers, squalls, tornadoes). The authors have developed the improved algorithms for recognition of dangerous weather phenomena, based on the complex analysis of incoming information using the mathematical apparatus of pattern recognition.

Marine Boundary Layer Cloud Property Retrievals from High-Resolution ASTER Observations: Case Studies and Comparison with Terra MODIS

NASA Technical Reports Server (NTRS)

Werner, Frank; Wind, Galina; Zhang, Zhibo; Platnick, Steven; Di Girolamo, Larry; Zhao, Guangyu; Amarasinghe, Nandana; Meyer, Kerry

2016-01-01

A research-level retrieval algorithm for cloud optical and microphysical properties is developed for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra satellite. It is based on the operational MODIS algorithm. This paper documents the technical details of this algorithm and evaluates the retrievals for selected marine boundary layer cloud scenes through comparisons with the operational MODIS Data Collection 6 (C6) cloud product. The newly developed, ASTERspecific cloud masking algorithm is evaluated through comparison with an independent algorithm reported in Zhao and Di Girolamo (2006). To validate and evaluate the cloud optical thickness (tau) and cloud effective radius (r(sub eff)) from ASTER, the high-spatial-resolution ASTER observations are first aggregated to the same 1000m resolution as MODIS. Subsequently, tau(sub aA) and r(sub eff, aA) retrieved from the aggregated ASTER radiances are compared with the collocated MODIS retrievals. For overcast pixels, the two data sets agree very well with Pearson's product-moment correlation coefficients of R greater than 0.970. However, for partially cloudy pixels there are significant differences between r(sub eff, aA) and the MODIS results which can exceed 10 micrometers. Moreover, it is shown that the numerous delicate cloud structures in the example marine boundary layer scenes, resolved by the high-resolution ASTER retrievals, are smoothed by the MODIS observations. The overall good agreement between the research-level ASTER results and the operational MODIS C6 products proves the feasibility of MODIS-like retrievals from ASTER reflectance measurements and provides the basis for future studies concerning the scale dependency of satellite observations and three-dimensional radiative effects.

Detection of convective initiation using Meteosat SEVIRI: implementation in and verification with the tracking and nowcasting algorithm Cb-TRAM

NASA Astrophysics Data System (ADS)

Merk, D.; Zinner, T.

2013-02-01

In this paper a new detection scheme for Convective Initation (CI) under day and night conditions is presented. The new algorithm combines the strengths of two existing methods for detecting Convective Initation with geostationary satellite data and uses the channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG). For the new algorithm five infrared criteria from the Satellite Convection Analysis and Tracking algorithm (SATCAST) and one High Resolution Visible channel (HRV) criteria from Cb-TRAM were adapted. This set of criteria aims for identifying the typical development of quickly developing convective cells in an early stage. The different criteria include timetrends of the 10.8 IR channel and IR channel differences as well as their timetrends. To provide the trend fields an optical flow based method is used, the Pyramidal Matching algorithm which is part of Cb-TRAM. The new detection scheme is implemented in Cb-TRAM and is verified for seven days which comprise different weather situations in Central Europe. Contrasted with the original early stage detection scheme of Cb-TRAM skill scores are provided. From the comparison against detections of later thunderstorm stages, which are also provided by Cb-TRAM, a decrease in false prior warnings (false alarm ratio) from 91 to 81% is presented, an increase of the critical success index from 7.4 to 12.7%, and a decrease of the BIAS from 320 to 146% for normal scan mode. Similar trends are found for rapid scan mode. Most obvious is the decline of false alarms found for synoptic conditions with upper cold air masses triggering convection.

Detection of convective initiation using Meteosat SEVIRI: implementation in and verification with the tracking and nowcasting algorithm Cb-TRAM

NASA Astrophysics Data System (ADS)

Merk, D.; Zinner, T.

2013-08-01

In this paper a new detection scheme for convective initiation (CI) under day and night conditions is presented. The new algorithm combines the strengths of two existing methods for detecting CI with geostationary satellite data. It uses the channels of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG). For the new algorithm five infrared (IR) criteria from the Satellite Convection Analysis and Tracking algorithm (SATCAST) and one high-resolution visible channel (HRV) criteria from Cb-TRAM were adapted. This set of criteria aims to identify the typical development of quickly developing convective cells in an early stage. The different criteria include time trends of the 10.8 IR channel, and IR channel differences, as well as their time trends. To provide the trend fields an optical-flow-based method is used: the pyramidal matching algorithm, which is part of Cb-TRAM. The new detection scheme is implemented in Cb-TRAM, and is verified for seven days which comprise different weather situations in central Europe. Contrasted with the original early-stage detection scheme of Cb-TRAM, skill scores are provided. From the comparison against detections of later thunderstorm stages, which are also provided by Cb-TRAM, a decrease in false prior warnings (false alarm ratio) from 91 to 81% is presented, an increase of the critical success index from 7.4 to 12.7%, and a decrease of the BIAS from 320 to 146% for normal scan mode. Similar trends are found for rapid scan mode. Most obvious is the decline of false alarms found for the synoptic class "cold air" masses.

Marine boundary layer cloud property retrievals from high-resolution ASTER observations: case studies and comparison with Terra MODIS

NASA Astrophysics Data System (ADS)

Werner, Frank; Wind, Galina; Zhang, Zhibo; Platnick, Steven; Di Girolamo, Larry; Zhao, Guangyu; Amarasinghe, Nandana; Meyer, Kerry

2016-12-01

A research-level retrieval algorithm for cloud optical and microphysical properties is developed for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra satellite. It is based on the operational MODIS algorithm. This paper documents the technical details of this algorithm and evaluates the retrievals for selected marine boundary layer cloud scenes through comparisons with the operational MODIS Data Collection 6 (C6) cloud product. The newly developed, ASTER-specific cloud masking algorithm is evaluated through comparison with an independent algorithm reported in [Zhao and Di Girolamo(2006)]. To validate and evaluate the cloud optical thickness (τ) and cloud effective radius (reff) from ASTER, the high-spatial-resolution ASTER observations are first aggregated to the same 1000 m resolution as MODIS. Subsequently, τaA and reff, aA retrieved from the aggregated ASTER radiances are compared with the collocated MODIS retrievals. For overcast pixels, the two data sets agree very well with Pearson's product-moment correlation coefficients of R > 0.970. However, for partially cloudy pixels there are significant differences between reff, aA and the MODIS results which can exceed 10 µm. Moreover, it is shown that the numerous delicate cloud structures in the example marine boundary layer scenes, resolved by the high-resolution ASTER retrievals, are smoothed by the MODIS observations. The overall good agreement between the research-level ASTER results and the operational MODIS C6 products proves the feasibility of MODIS-like retrievals from ASTER reflectance measurements and provides the basis for future studies concerning the scale dependency of satellite observations and three-dimensional radiative effects.

The performance of Yonsei CArbon Retrieval (YCAR) algorithm with improved aerosol information using GOSAT measurements over East Asia

NASA Astrophysics Data System (ADS)

Jung, Y.; Kim, J.; Kim, W.; Boesch, H.; Yoshida, Y.; Cho, C.; Lee, H.; Goo, T. Y.

2016-12-01

The Greenhouse Gases Observing SATellite (GOSAT) is the first satellite dedicated to measure atmospheric CO2 concentrations from space that can able to improve our knowledge about carbon cycle. Several studies have performed to develop the CO2 retrieval algorithms using GOSAT measurements, but limitations in spatial coverage and uncertainties due to aerosols and thin cirrus clouds are still remained as a problem for monitoring CO2 concentration globally. In this study, we develop the Yonsei CArbon Retrieval (YCAR) algorithm based on optimal estimation method to retrieve the column-averaged dry-air mole fraction of carbon dioxide (XCO2) with optimized a priori CO2 profiles and aerosol models over East Asia. In previous studies, the aerosol optical properties (AOP) and the aerosol top height used to cause significant errors in retrieved XCO2 up to 2.5 ppm. Since this bias comes from a rough assumption of aerosol information in the forward model used in CO2 retrieval process, the YCAR algorithm improves the process to take into account AOPs as well as aerosol vertical distribution; total AOD and the fine mode fraction (FMF) are obtained from the ground-based measurements closely located, and other parameters are obtained from a priori information. Comparing to ground-based XCO2 measurements, the YCAR XCO2 product has a bias of 0.59±0.48 ppm and 2.16±0.87 ppm at Saga and Tsukuba sites, respectively, showing lower biases and higher correlations rather than the GOSAT standard products. These results reveal that considering better aerosol information can improve the accuracy of CO2 retrieval algorithm and provide more useful XCO2 information with reduced uncertainties.

Improvement and further development of SSM/I overland parameter algorithms using the WetNet workstation

NASA Technical Reports Server (NTRS)

Neale, Christopher M. U.; Mcdonnell, Jeffrey J.; Ramsey, Douglas; Hipps, Lawrence; Tarboton, David

1993-01-01

Since the launch of the DMSP Special Sensor Microwave/Imager (SSM/I), several algorithms have been developed to retrieve overland parameters. These include the present operational algorithms resulting from the Navy calibration/validation effort such as land surface type (Neale et al. 1990), land surface temperature (McFarland et al. 1990), surface moisture (McFarland and Neale, 1991) and snow parameters (McFarland and Neale, 1991). In addition, other work has been done including the classification of snow cover and precipitation using the SSM/I (Grody, 1991). Due to the empirical nature of most of the above mentioned algorithms, further research is warranted and improvements can probably be obtained through a combination of radiative transfer modelling to study the physical processes governing the microwave emissions at the SSM/I frequencies, and the incorporation of additional ground truth data and special cases into the regression data sets. We have proposed specifically to improve the retrieval of surface moisture and snow parameters using the WetNet SSM/I data sets along with ground truth information namely climatic variables from the NOAA cooperative network of weather stations as well as imagery from other satellite sensors such as the AVHRR and Thematic Mapper. In the case of surface moisture retrievals the characterization of vegetation density is of primary concern. The higher spatial resolution satellite imagery collected at concurrent periods will be used to characterize vegetation types and amounts which, along with radiative transfer modelling should lead to more physically based retrievals. Snow parameter retrieval algorithm improvement will initially concentrate on the classification of snowpacks (dry snow, wet snow, refrozen snow) and later on specific products such as snow water equivalent. Significant accomplishments in the past year are presented.

Estimation of phytoplankton production from space: current status and future potential of satellite remote sensing.

PubMed

Joint; Groom

2000-07-30

A new generation of ocean colour satellites is now operational, with frequent observation of the global ocean. This paper reviews the potential to estimate marine primary production from satellite images. The procedures involved in retrieving estimates of phytoplankton biomass, as pigment concentrations, are discussed. Algorithms are applied to SeaWiFS ocean colour data to indicate seasonal variations in phytoplankton biomass in the Celtic Sea, on the continental shelf to the south west of the UK. Algorithms to estimate primary production rates from chlorophyll concentration are compared and the advantages and disadvantage discussed. The simplest algorithms utilise correlations between chlorophyll concentration and production rate and one equation is used to estimate daily primary production rates for the western English Channel and Celtic Sea; these estimates compare favourably with published values. Primary production for the central Celtic Sea in the period April to September inclusive is estimated from SeaWiFS data to be 102 gC m(-2) in 1998 and 93 gC m(-2) in 1999; published estimates, based on in situ incubations, are ca. 80 gC m(-2). The satellite data demonstrate large variations in primary production between 1998 and 1999, with a significant increase in late summer in 1998 which did not occur in 1999. Errors are quantified for the estimation of primary production from simple algorithms based on satellite-derived chlorophyll concentration. These data show the potential to obtain better estimates of marine primary production than are possible with ship-based methods, with the ability to detect short-lived phytoplankton blooms. In addition, the potential to estimate new production from satellite data is discussed.

Rainfall Estimation over the Nile Basin using an Adapted Version of the SCaMPR Algorithm

NASA Astrophysics Data System (ADS)

Habib, E. H.; Kuligowski, R. J.; Elshamy, M. E.; Ali, M. A.; Haile, A.; Amin, D.; Eldin, A.

2011-12-01

Management of Egypt's Aswan High Dam is critical not only for flood control on the Nile but also for ensuring adequate water supplies for most of Egypt since rainfall is scarce over the vast majority of its land area. However, reservoir inflow is driven by rainfall over Sudan, Ethiopia, Uganda, and several other countries from which routine rain gauge data are sparse. Satellite-derived estimates of rainfall offer a much more detailed and timely set of data to form a basis for decisions on the operation of the dam. A single-channel infrared algorithm is currently in operational use at the Egyptian Nile Forecast Center (NFC). This study reports on the adaptation of a multi-spectral, multi-instrument satellite rainfall estimation algorithm (Self-Calibrating Multivariate Precipitation Retrieval, SCaMPR) for operational application over the Nile Basin. The algorithm uses a set of rainfall predictors from multi-spectral Infrared cloud top observations and self-calibrates them to a set of predictands from Microwave (MW) rain rate estimates. For application over the Nile Basin, the SCaMPR algorithm uses multiple satellite IR channels recently available to NFC from the Spinning Enhanced Visible and Infrared Imager (SEVIRI). Microwave rain rates are acquired from multiple sources such as SSM/I, SSMIS, AMSU, AMSR-E, and TMI. The algorithm has two main steps: rain/no-rain separation using discriminant analysis, and rain rate estimation using stepwise linear regression. We test two modes of algorithm calibration: real-time calibration with continuous updates of coefficients with newly coming MW rain rates, and calibration using static coefficients that are derived from IR-MW data from past observations. We also compare the SCaMPR algorithm to other global-scale satellite rainfall algorithms (e.g., 'Tropical Rainfall Measuring Mission (TRMM) and other sources' (TRMM-3B42) product, and the National Oceanographic and Atmospheric Administration Climate Prediction Center (NOAA-CPC) CMORPH product. The algorithm has several potential future applications such as: improving the performance accuracy of hydrologic forecasting models over the Nile Basin, and utilizing the enhanced rainfall datasets and better-calibrated hydrologic models to assess the impacts of climate change on the region's water availability.

NASA sea ice and snow validation plan for the Defense Meteorological Satellite Program special sensor microwave/imager

NASA Technical Reports Server (NTRS)

Cavalieri, Donald J. (Editor); Swift, Calvin T. (Editor)

1987-01-01

This document addresses the task of developing and executing a plan for validating the algorithm used for initial processing of sea ice data from the Special Sensor Microwave/Imager (SSMI). The document outlines a plan for monitoring the performance of the SSMI, for validating the derived sea ice parameters, and for providing quality data products before distribution to the research community. Because of recent advances in the application of passive microwave remote sensing to snow cover on land, the validation of snow algorithms is also addressed.

Atmospheric transformation of multispectral remote sensor data. [Great Lakes

NASA Technical Reports Server (NTRS)

Turner, R. E. (Principal Investigator)

1977-01-01

The author has identified the following significant results. The effects of earth's atmosphere were accounted for, and a simple algorithm, based upon a radiative transfer model, was developed to determine the radiance at earth's surface free of atmospheric effects. Acutal multispectral remote sensor data for Lake Erie and associated optical thickness data were used to demonstrate the effectiveness of the atmospheric transformation algorithm. The basic transformation was general in nature and could be applied to the large scale processing of multispectral aircraft or satellite remote sensor data.

Development of MODIS data-based algorithm for retrieving sea surface temperature in coastal waters.

PubMed

Wang, Jiao; Deng, Zhiqiang

2017-06-01

A new algorithm was developed for retrieving sea surface temperature (SST) in coastal waters using satellite remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua platform. The new SST algorithm was trained using the Artificial Neural Network (ANN) method and tested using 8 years of remote sensing data from MODIS Aqua sensor and in situ sensing data from the US coastal waters in Louisiana, Texas, Florida, California, and New Jersey. The ANN algorithm could be utilized to map SST in both deep offshore and particularly shallow nearshore waters at the high spatial resolution of 1 km, greatly expanding the coverage of remote sensing-based SST data from offshore waters to nearshore waters. Applications of the ANN algorithm require only the remotely sensed reflectance values from the two MODIS Aqua thermal bands 31 and 32 as input data. Application results indicated that the ANN algorithm was able to explaining 82-90% variations in observed SST in US coastal waters. While the algorithm is generally applicable to the retrieval of SST, it works best for nearshore waters where important coastal resources are located and existing algorithms are either not applicable or do not work well, making the new ANN-based SST algorithm unique and particularly useful to coastal resource management.

SAO Participation in the GOME and SCIAMACHY Satellite Instrument Programs

NASA Technical Reports Server (NTRS)

Hilsenrath, Ernest (Technical Monitor); Chance, Kelly; Kurosu, Thomas

2004-01-01

This report summarizes the progress on our three-year program of research to refine the measurement capability for satellite-based instruments that monitor ozone and other trace species in the Earth's stratosphere and troposphere, to retrieve global distributions of these and other constituents h m the GOME and SCIAMACHY satellite instruments, and to conduct scientific studies for the ILAS instruments. This continues our involvements as a U.S. participant in GOME and SCIAMACHY since their inception, and as a member of the ILAS-II Science Team. These programs have led to the launch of the first satellite instrument specifically designed to measure height-resolved ozone, including the tropospheric component (GOME), and the development of the first satellite instrument that will measure tropospheric ozone simultaneously with NO2, CO, HCHO, N2O, H2O, and CH4 (SCIAMACHY). The GOME program now includes the GOME-2 instruments, to be launched on the Eumetsat Metop satellites, providing long-term continuity in European measurements of global ozone that complement the measurements of the TOMS, SBUV, OMI, OMPS instruments. The research primarily focuses on two areas: Data analysis, including algorithm development and validation studies that will improve the quality of retrieved data products, in support for future field campaigns (to complement in situ and airborne campaigns with satellite measurements), and scientific analyses to be interfaced to atmospheric modeling studies.

SAO Participation in the GOME and SCIAMACHY Satellite Instrument Programs

NASA Technical Reports Server (NTRS)

Chance, Kelly; Kurosu, Thomas

2003-01-01

This report summarizes the progress on our three-year program of research to refine the measurement capability for satellite-based instruments that monitor ozone and other trace species in the Earth's stratosphere and troposphere, to retrieve global distributions of these and other constituents from the GOME and SCIAMACHY satellite instruments, and to conduct scientific studies for the ILAS instruments. This continues our involvements as a U.S. participant in GOME and SCIAMACHY since their inception, and as a member of the ILAS-II Science Team. These programs have led to the launch of the first satellite instrument specifically designed to measure height-resolved ozone, including the tropospheric component (GOME), and the development of the first satellite instrument that will measure tropospheric ozone simultaneously with NO2, CO, HCHO, N2O, H2O, and CH4 (SCIAMACHY). The GOME program now includes the GOME-2 instruments, to be launched on the Eumetsat Metop satellites, providing long-term continuity in European measurements of global ozone that complement the measurements of the TOMS, SBW, OMI, OMPS instruments. The research primarily focuses on two areas: Data analysis, including algorithm development and validation studies that will improve the quality of retrieved data products, in support for future field campaigns (to complement in situ and airborne campaigns with satellite measurements), and scientific analyses to be interfaced to atmospheric modeling studies.

SPHERES National Lab Facility

NASA Technical Reports Server (NTRS)

Benavides, Jose

2014-01-01

SPHERES is a facility of the ISS National Laboratory with three IVA nano-satellites designed and delivered by MIT to research estimation, control, and autonomy algorithms. Since Fall 2010, The SPHERES system is now operationally supported and managed by NASA Ames Research Center (ARC). A SPHERES Program Office was established and is located at NASA Ames Research Center. The SPHERES Program Office coordinates all SPHERES related research and STEM activities on-board the International Space Station (ISS), as well as, current and future payload development. By working aboard ISS under crew supervision, it provides a risk tolerant Test-bed Environment for Distributed Satellite Free-flying Control Algorithms. If anything goes wrong, reset and try again! NASA has made the capability available to other U.S. government agencies, schools, commercial companies and students to expand the pool of ideas for how to test and use these bowling ball-sized droids. For many of the researchers, SPHERES offers the only opportunity to do affordable on-orbit characterization of their technology in the microgravity environment. Future utilization of SPHERES as a facility will grow its capabilities as a platform for science, technology development, and education.

NASA Satellite Monitoring of Water Clarity in Mobile Bay for Nutrient Criteria Development

NASA Technical Reports Server (NTRS)

Blonski, Slawomir; Holekamp, Kara; Spiering, Bruce A.

2009-01-01

This project has demonstrated feasibility of deriving from MODIS daily measurements time series of water clarity parameters that provide coverage of a specific location or an area of interest for 30-50% of days. Time series derived for estuarine and coastal waters display much higher variability than time series of ecological parameters (such as vegetation indices) derived for land areas. (Temporal filtering often applied in terrestrial studies cannot be used effectively in ocean color processing). IOP-based algorithms for retrieval of diffuse light attenuation coefficient and TSS concentration perform well for the Mobile Bay environment: only a minor adjustment was needed in the TSS algorithm, despite generally recognized dependence of such algorithms on local conditions. The current IOP-based algorithm for retrieval of chlorophyll a concentration has not performed as well: a more reliable algorithm is needed that may be based on IOPs at additional wavelengths or on remote sensing reflectance from multiple spectral bands. CDOM algorithm also needs improvement to provide better separation between effects of gilvin (gelbstoff) and detritus. (Identification or development of such algorithm requires more data from in situ measurements of CDOM concentration in Gulf of Mexico coastal waters (ongoing collaboration with the EPA Gulf Ecology Division))

Global Soil Moisture from the Aquarius/SAC-D Satellite: Description and Initial Assessment

NASA Technical Reports Server (NTRS)

Bindlish, Rajat; Jackson, Thomas; Cosh, Michael; Zhao, Tianjie; O'Neil, Peggy

2015-01-01

Aquarius satellite observations over land offer a new resource for measuring soil moisture from space. Although Aquarius was designed for ocean salinity mapping, our objective in this investigation is to exploit the large amount of land observations that Aquarius acquires and extend the mission scope to include the retrieval of surface soil moisture. The soil moisture retrieval algorithm development focused on using only the radiometer data because of the extensive heritage of passive microwave retrieval of soil moisture. The single channel algorithm (SCA) was implemented using the Aquarius observations to estimate surface soil moisture. Aquarius radiometer observations from three beams (after bias/gain modification) along with the National Centers for Environmental Prediction model forecast surface temperatures were then used to retrieve soil moisture. Ancillary data inputs required for using the SCA are vegetation water content, land surface temperature, and several soil and vegetation parameters based on land cover classes. The resulting global spatial patterns of soil moisture were consistent with the precipitation climatology and with soil moisture from other satellite missions (Advanced Microwave Scanning Radiometer for the Earth Observing System and Soil Moisture Ocean Salinity). Initial assessments were performed using in situ observations from the U.S. Department of Agriculture Little Washita and Little River watershed soil moisture networks. Results showed good performance by the algorithm for these land surface conditions for the period of August 2011-June 2013 (rmse = 0.031 m(exp 3)/m(exp 3), Bias = -0.007 m(exp 3)/m(exp 3), and R = 0.855). This radiometer-only soil moisture product will serve as a baseline for continuing research on both active and combined passive-active soil moisture algorithms. The products are routinely available through the National Aeronautics and Space Administration data archive at the National Snow and Ice Data Center.

An analytic algorithm for global coverage of the revisiting orbit and its application to the CFOSAT satellite

NASA Astrophysics Data System (ADS)

Xu, Ming; Huang, Li

2014-08-01

This paper addresses a new analytic algorithm for global coverage of the revisiting orbit and its application to the mission revisiting the Earth within long periods of time, such as Chinese-French Oceanic Satellite (abbr., CFOSAT). In the first, it is presented that the traditional design methodology of the revisiting orbit for some imaging satellites only on the single (ascending or descending) pass, and the repeating orbit is employed to perform the global coverage within short periods of time. However, the selection of the repeating orbit is essentially to yield the suboptimum from the rare measure of rational numbers of passes per day, which will lose lots of available revisiting orbits. Thus, an innovative design scheme is proposed to check both rational and irrational passes per day to acquire the relationship between the coverage percentage and the altitude. To improve the traditional imaging only on the single pass, the proposed algorithm is mapping every pass into its ascending and descending nodes on the specified latitude circle, and then is accumulating the projected width on the circle by the field of view of the satellite. The ergodic geometry of coverage percentage produced from the algorithm is affecting the final scheme, such as the optimal one owning the largest percentage, and the balance one possessing the less gradient in its vicinity, and is guiding to heuristic design for the station-keeping control strategies. The application of CFOSAT validates the feasibility of the algorithm.

Vehicle detection and orientation estimation using the radon transform

NASA Astrophysics Data System (ADS)

Pelapur, Rengarajan; Bunyak, Filiz; Palaniappan, Kannappan; Seetharaman, Gunasekaran

2013-05-01

Determining the location and orientation of vehicles in satellite and airborne imagery is a challenging task given the density of cars and other vehicles and complexity of the environment in urban scenes almost anywhere in the world. We have developed a robust and accurate method for detecting vehicles using a template-based directional chamfer matching, combined with vehicle orientation estimation based on a refined segmentation, followed by a Radon transform based profile variance peak analysis approach. The same algorithm was applied to both high resolution satellite imagery and wide area aerial imagery and initial results show robustness to illumination changes and geometric appearance distortions. Nearly 80% of the orientation angle estimates for 1585 vehicles across both satellite and aerial imagery were accurate to within 15? of the ground truth. In the case of satellite imagery alone, nearly 90% of the objects have an estimated error within +/-1.0° of the ground truth.

An overview of Space Communication Artificial Intelligence for Link Evaluation Terminal (SCAILET) Project

NASA Technical Reports Server (NTRS)

Shahidi, Anoosh K.; Schlegelmilch, Richard F.; Petrik, Edward J.; Walters, Jerry L.

1991-01-01

A software application to assist end-users of the link evaluation terminal (LET) for satellite communications is being developed. This software application incorporates artificial intelligence (AI) techniques and will be deployed as an interface to LET. The high burst rate (HBR) LET provides 30 GHz transmitting/20 GHz receiving (220/110 Mbps) capability for wideband communications technology experiments with the Advanced Communications Technology Satellite (ACTS). The HBR LET can monitor and evaluate the integrity of the HBR communications uplink and downlink to the ACTS satellite. The uplink HBR transmission is performed by bursting the bit-pattern as a modulated signal to the satellite. The HBR LET can determine the bit error rate (BER) under various atmospheric conditions by comparing the transmitted bit pattern with the received bit pattern. An algorithm for power augmentation will be applied to enhance the system's BER performance at reduced signal strength caused by adverse conditions.

Remote Sensing of the Absorption Coefficients and Chlorophyll a Concentration in the U.S. Southern Middle Atlantic Bight from SeaWiFS and MODIS-Aqua

NASA Technical Reports Server (NTRS)

Pan, Xiaoju; Mannino, Antonio; Russ, Mary E.; Hooker, Stanford B.

2008-01-01

At present, satellite remote sensing of coastal water quality and constituent concentration is subject to large errors as compared to the capability of satellite sensors in oceanic waters. In this study, field measurements collected on a series of cruises within U.S. southern Middle Atlantic Bight (SMAB) were applied to improve retrievals of satellite ocean color products in order to examine the factors that regulate the bio-optical properties within the continental shelf waters of the SMAB. The first objective was to develop improvements in satellite retrievals of absorption coefficients of phytoplankton (a(sub ph)), colored dissolved organic matter (CDOM) (a(sub g)), non-pigmented particles (a(sub d)), and non-pigmented particles plus CDOM (a(sub dg)), and chlorophyll a concentration ([Chl_a]). Several algorithms were compared to derive constituent absorption coefficients from remote sensing reflectance (R(sub rs)) ratios. The validation match-ups showed that the mean absolute percent differences (MAPD) were typically less than 35%, although higher errors were found for a(sub d) retrievals. Seasonal and spatial variability of satellite-derived absorption coefficients and [Chl_a] was apparent and consistent with field data. CDOM is a major contributor to the bio-optical properties of the SMAB, accounting for 35-70% of total light absorption by particles plus CDOM at 443 nm, as compared to 30-45% for phytoplankton and 0-20% for non-pigmented particles. The overestimation of [Chl_a] from the operational satellite algorithms may be attributed to the strong CDOM absorption in this region. River discharge is important in controlling the bio-optical environment, but cannot explain all of the regional and seasonal variability of biogeochemical constituents in the SMAB.

Assessment of the global monthly mean surface insolation estimated from satellite measurements using global energy balance archive data

NASA Technical Reports Server (NTRS)

Li, Zhanqing; Whitlock, Charles H.; Charlock, Thomas P.

1995-01-01

Global sets of surface radiation budget (SRB) have been obtained from satellite programs. These satellite-based estimates need validation with ground-truth observations. This study validates the estimates of monthly mean surface insolation contained in two satellite-based SRB datasets with the surface measurements made at worldwide radiation stations from the Global Energy Balance Archive (GEBA). One dataset was developed from the Earth Radiation Budget Experiment (ERBE) using the algorithm of Li et al. (ERBE/SRB), and the other from the International Satellite Cloud Climatology Project (ISCCP) using the algorithm of Pinker and Laszlo and that of Staylor (GEWEX/SRB). Since the ERBE/SRB data contain the surface net solar radiation only, the values of surface insolation were derived by making use of the surface albedo data contained GEWEX/SRB product. The resulting surface insolation has a bias error near zero and a root-mean-square error (RMSE) between 8 and 28 W/sq m. The RMSE is mainly associated with poor representation of surface observations within a grid cell. When the number of surface observations are sufficient, the random error is estimated to be about 5 W/sq m with present satellite-based estimates. In addition to demonstrating the strength of the retrieving method, the small random error demonstrates how well the ERBE derives from the monthly mean fluxes at the top of the atmosphere (TOA). A larger scatter is found for the comparison of transmissivity than for that of insolation. Month to month comparison of insolation reveals a weak seasonal trend in bias error with an amplitude of about 3 W/sq m. As for the insolation data from the GEWEX/SRB, larger bias errors of 5-10 W/sq m are evident with stronger seasonal trends and almost identical RMSEs.

AeroADL: applying the integration of the Suomi-NPP science algorithms with the Algorithm Development Library to the calibration and validation task

NASA Astrophysics Data System (ADS)

Houchin, J. S.

2014-09-01

A common problem for the off-line validation of the calibration algorithms and algorithm coefficients is being able to run science data through the exact same software used for on-line calibration of that data. The Joint Polar Satellite System (JPSS) program solved part of this problem by making the Algorithm Development Library (ADL) available, which allows the operational algorithm code to be compiled and run on a desktop Linux workstation using flat file input and output. However, this solved only part of the problem, as the toolkit and methods to initiate the processing of data through the algorithms were geared specifically toward the algorithm developer, not the calibration analyst. In algorithm development mode, a limited number of sets of test data are staged for the algorithm once, and then run through the algorithm over and over as the software is developed and debugged. In calibration analyst mode, we are continually running new data sets through the algorithm, which requires significant effort to stage each of those data sets for the algorithm without additional tools. AeroADL solves this second problem by providing a set of scripts that wrap the ADL tools, providing both efficient means to stage and process an input data set, to override static calibration coefficient look-up-tables (LUT) with experimental versions of those tables, and to manage a library containing multiple versions of each of the static LUT files in such a way that the correct set of LUTs required for each algorithm are automatically provided to the algorithm without analyst effort. Using AeroADL, The Aerospace Corporation's analyst team has demonstrated the ability to quickly and efficiently perform analysis tasks for both the VIIRS and OMPS sensors with minimal training on the software tools.

Small satellite attitude determination based on GPS/IMU data fusion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Golovan, Andrey; Cepe, Ali

In this paper, we present the mathematical models and algorithms that describe the problem of attitude determination for a small satellite using measurements from three angular rate sensors (ARS) and aiding measurements from multiple GPS receivers/antennas rigidly attached to the platform of the satellite.

Automated Wildfire Detection Through Artificial Neural Networks

NASA Technical Reports Server (NTRS)

Miller, Jerry; Borne, Kirk; Thomas, Brian; Huang, Zhenping; Chi, Yuechen

2005-01-01

Wildfires have a profound impact upon the biosphere and our society in general. They cause loss of life, destruction of personal property and natural resources and alter the chemistry of the atmosphere. In response to the concern over the consequences of wildland fire and to support the fire management community, the National Oceanic and Atmospheric Administration (NOAA), National Environmental Satellite, Data and Information Service (NESDIS) located in Camp Springs, Maryland gradually developed an operational system to routinely monitor wildland fire by satellite observations. The Hazard Mapping System, as it is known today, allows a team of trained fire analysts to examine and integrate, on a daily basis, remote sensing data from Geostationary Operational Environmental Satellite (GOES), Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensors and generate a 24 hour fire product for the conterminous United States. Although assisted by automated fire detection algorithms, N O M has not been able to eliminate the human element from their fire detection procedures. As a consequence, the manually intensive effort has prevented NOAA from transitioning to a global fire product as urged particularly by climate modelers. NASA at Goddard Space Flight Center in Greenbelt, Maryland is helping N O M more fully automate the Hazard Mapping System by training neural networks to mimic the decision-making process of the frre analyst team as well as the automated algorithms.

Single frequency GPS measurements in real-time artificial satellite orbit determination

NASA Astrophysics Data System (ADS)

Chiaradia, orbit determination A. P. M.; Kuga, H. K.; Prado, A. F. B. A.

2003-07-01

A simplified and compact algorithm with low computational cost providing an accuracy around tens of meters for artificial satellite orbit determination in real-time and on-board is developed in this work. The state estimation method is the extended Kalman filter. The Cowell's method is used to propagate the state vector, through a simple Runge-Kutta numerical integrator of fourth order with fixed step size. The modeled forces are due to the geopotential up to 50th order and degree of JGM-2 model. To time-update the state error covariance matrix, it is considered a simplified force model. In other words, in computing the state transition matrix, the effect of J 2 (Earth flattening) is analytically considered, which unloads dramatically the processing time. In the measurement model, the single frequency GPS pseudorange is used, considering the effects of the ionospheric delay, clock offsets of the GPS and user satellites, and relativistic effects. To validate this model, real live data are used from Topex/Poseidon satellite and the results are compared with the Topex/Poseidon Precision Orbit Ephemeris (POE) generated by NASA/JPL, for several test cases. It is concluded that this compact algorithm enables accuracies of tens of meters with such simplified force model, analytical approach for computing the transition matrix, and a cheap GPS receiver providing single frequency pseudorange measurements.

A Dual-Channel Acquisition Method Based on Extended Replica Folding Algorithm for Long Pseudo-Noise Code in Inter-Satellite Links.

PubMed

Zhao, Hongbo; Chen, Yuying; Feng, Wenquan; Zhuang, Chen

2018-05-25

Inter-satellite links are an important component of the new generation of satellite navigation systems, characterized by low signal-to-noise ratio (SNR), complex electromagnetic interference and the short time slot of each satellite, which brings difficulties to the acquisition stage. The inter-satellite link in both Global Positioning System (GPS) and BeiDou Navigation Satellite System (BDS) adopt the long code spread spectrum system. However, long code acquisition is a difficult and time-consuming task due to the long code period. Traditional folding methods such as extended replica folding acquisition search technique (XFAST) and direct average are largely restricted because of code Doppler and additional SNR loss caused by replica folding. The dual folding method (DF-XFAST) and dual-channel method have been proposed to achieve long code acquisition in low SNR and high dynamic situations, respectively, but the former is easily affected by code Doppler and the latter is not fast enough. Considering the environment of inter-satellite links and the problems of existing algorithms, this paper proposes a new long code acquisition algorithm named dual-channel acquisition method based on the extended replica folding algorithm (DC-XFAST). This method employs dual channels for verification. Each channel contains an incoming signal block. Local code samples are folded and zero-padded to the length of the incoming signal block. After a circular FFT operation, the correlation results contain two peaks of the same magnitude and specified relative position. The detection process is eased through finding the two largest values. The verification takes all the full and partial peaks into account. Numerical results reveal that the DC-XFAST method can improve acquisition performance while acquisition speed is guaranteed. The method has a significantly higher acquisition probability than folding methods XFAST and DF-XFAST. Moreover, with the advantage of higher detection probability and lower false alarm probability, it has a lower mean acquisition time than traditional XFAST, DF-XFAST and zero-padding.

Two-Channel Satellite Retrievals of Aerosol Properties: An Overview

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.

1999-01-01

In order to reduce current uncertainties in the evaluation of the direct and indirect effects of tropospheric aerosols on climate on the global scale, it has been suggested to apply multi-channel retrieval algorithms to the full period of existing satellite data. This talk will outline the methodology of interpreting two-channel satellite radiance data over the ocean and describe a detailed analysis of the sensitivity of retrieved aerosol parameters to the assumptions made in different retrieval algorithms. We will specifically address the calibration and cloud screening issues, consider the suitability of existing satellite data sets to detecting short- and long-term regional and global changes, compare preliminary results obtained by several research groups, and discuss the prospects of creating an advanced retroactive climatology of aerosol optical thickness and size over the oceans.

LADEE Satellite Modeling and Simulation Development

NASA Technical Reports Server (NTRS)

Adams, Michael; Cannon, Howard; Frost, Chad

2011-01-01

As human activity on and around the Moon increases, so does the likelihood that our actions will have an impact on its atmosphere. The Lunar Atmosphere and Dust Environment Explorer (LADEE), a NASA satellite scheduled to launch in 2013, will orbit the Moon collecting composition, density, and time variability data to characterize the current state of the lunar atmosphere. LADEE will also test the concept of the "Modular Common Bus" spacecraft architecture, an effort to reduce both development time and cost by designing reusable, modular components for use in multiple missions with similar requirements. An important aspect of this design strategy is to both simulate the spacecraft and develop the flight code in Simulink, a block diagram-style programming language that allows easy algorithm visualization and performance testing. Before flight code can be tested, however, a realistic simulation of the satellite and its dynamics must be generated and validated. This includes all of the satellite control system components such as actuators used for force and torque generation and sensors used for inertial orientation reference. My primary responsibilities have included designing, integrating, and testing models for the LADEE thrusters, reaction wheels, star trackers, and rate gyroscopes.

A LEO Satellite Navigation Algorithm Based on GPS and Magnetometer Data

NASA Technical Reports Server (NTRS)

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

2000-01-01

The Global Positioning System (GPS) has become a standard method for low cost onboard satellite orbit determination. The use of a GPS receiver as an attitude and rate sensor has also been developed in the recent past. Additionally, focus has been given to attitude and orbit estimation using the magnetometer, a low cost, reliable sensor. Combining measurements from both GPS and a magnetometer can provide a robust navigation system that takes advantage of the estimation qualities of both measurements. Ultimately a low cost, accurate navigation system can result, potentially eliminating the need for more costly sensors, including gyroscopes.

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

NASA Astrophysics Data System (ADS)

Kit, Oleksandr; Lüdeke, Matthias

2013-09-01

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

The Joint Polar Satellite System (JPSS) Program's Algorithm Change Process (ACP): Past, Present and Future

NASA Technical Reports Server (NTRS)

Griffin, Ashley

2017-01-01

The Joint Polar Satellite System (JPSS) Program Office is the supporting organization for the Suomi National Polar Orbiting Partnership (S-NPP) and JPSS-1 satellites. S-NPP carries the following sensors: VIIRS, CrIS, ATMS, OMPS, and CERES with instruments that ultimately produce over 25 data products that cover the Earths weather, oceans, and atmosphere. A team of scientists and engineers from all over the United States document, monitor and fix errors in operational software code or documentation with the algorithm change process (ACP) to ensure the success of the S-NPP and JPSS 1 missions by maintaining quality and accuracy of the data products the scientific community relies on. This poster will outline the programs algorithm change process (ACP), identify the various users and scientific applications of our operational data products and highlight changes that have been made to the ACP to accommodate operating system upgrades to the JPSS programs Interface Data Processing Segment (IDPS), so that the program is ready for the transition to the 2017 JPSS-1 satellite mission and beyond.

Recent Progress on the Second Generation CMORPH: LEO-IR Based Precipitation Estimates and Cloud Motion Vector

NASA Astrophysics Data System (ADS)

Xie, Pingping; Joyce, Robert; Wu, Shaorong

2015-04-01

As reported at the EGU General Assembly of 2014, a prototype system was developed for the second generation CMORPH to produce global analyses of 30-min precipitation on a 0.05olat/lon grid over the entire globe from pole to pole through integration of information from satellite observations as well as numerical model simulations. The second generation CMORPH is built upon the Kalman Filter based CMORPH algorithm of Joyce and Xie (2011). Inputs to the system include rainfall and snowfall rate retrievals from passive microwave (PMW) measurements aboard all available low earth orbit (LEO) satellites, precipitation estimates derived from infrared (IR) observations of geostationary (GEO) as well as LEO platforms, and precipitation simulations from numerical global models. Key to the success of the 2nd generation CMORPH, among a couple of other elements, are the development of a LEO-IR based precipitation estimation to fill in the polar gaps and objectively analyzed cloud motion vectors to capture the cloud movements of various spatial scales over the entire globe. In this presentation, we report our recent work on the refinement for these two important algorithm components. The prototype algorithm for the LEO IR precipitation estimation is refined to achieve improved quantitative accuracy and consistency with PMW retrievals. AVHRR IR TBB data from all LEO satellites are first remapped to a 0.05olat/lon grid over the entire globe and in a 30-min interval. Temporally and spatially co-located data pairs of the LEO TBB and inter-calibrated combined satellite PMW retrievals (MWCOMB) are then collected to construct tables. Precipitation at a grid box is derived from the TBB through matching the PDF tables for the TBB and the MWCOMB. This procedure is implemented for different season, latitude band and underlying surface types to account for the variations in the cloud - precipitation relationship. At the meantime, a sub-system is developed to construct analyzed fields of cloud motion vectors from the GEO/LEO IR based precipitation estimates and the CFS Reanalysis (CFSR) precipitation fields. Motion vectors are first derived separately from the satellite IR based precipitation estimates and the CFSR precipitation fields. These individually derived motion vectors are then combined through a 2D-VAR technique to form an analyzed field of cloud motion vectors over the entire globe. Error function is experimented to best reflect the performance of the satellite IR based estimates and the CFSR in capturing the movements of precipitating cloud systems over different regions and for different seasons. Quantitative experiments are conducted to optimize the LEO IR based precipitation estimation technique and the 2D-VAR based motion vector analysis system. Detailed results will be reported at the EGU.

Geostationary Lightning Mapper for GOES-R

NASA Technical Reports Server (NTRS)

Goodman, Steven; Blakeslee, Richard; Koshak, William

2007-01-01

The Geostationary Lightning Mapper (GLM) is a single channel, near-IR optical detector, used to detect, locate and measure total lightning activity over the full-disk as part of a 3-axis stabilized, geostationary weather satellite system. The next generation NOAA Geostationary Operational Environmental Satellite (GOES-R) series with a planned launch in 2014 will carry a GLM that will provide continuous day and night observations of lightning from the west coast of Africa (GOES-E) to New Zealand (GOES-W) when the constellation is fully operational. The mission objectives for the GLM are to 1) provide continuous, full-disk lightning measurements for storm warning and Nowcasting, 2) provide early warning of tornadic activity, and 3) accumulate a long-term database to track decadal changes of lightning. The GLM owes its heritage to the NASA Lightning Imaging Sensor (1997-Present) and the Optical Transient Detector (1995-2000), which were developed for the Earth Observing System and have produced a combined 11 year data record of global lightning activity. Instrument formulation studies begun in January 2006 will be completed in March 2007, with implementation expected to begin in September 2007. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite, airborne science missions (e.g., African Monsoon Multi-disciplinary Analysis, AMMA), and regional test beds (e.g, Lightning Mapping Arrays) are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. Real time lightning mapping data now being provided to selected forecast offices will lead to improved understanding of the application of these data in the severe storm warning process and accelerate the development of the pre-launch algorithms and Nowcasting applications. Proxy data combined with MODIS and Meteosat Second Generation SEVERI observations will also lead to new applications (e.g., multi-sensor precipitation algorithms blending the GLM with the Advanced Baseline Imager, convective cloud initiation and identification, early warnings of lightning threat, storm tracking, and data assimilation).

The Geostationary Lightning Mapper (GLM) for the GOES-R Series Next Generation Operational Environmental Satellite Constellation

NASA Technical Reports Server (NTRS)

Goodman, Steven J.; Blakeslee, Richard; Koshak, William; Petersen, Walter; Carey, Larry; Mach, Douglas; Buechler, Dennis; Bateman, Monte; McCaul, Eugene; Bruning, Eric;

Optimised collision avoidance for an ultra-close rendezvous with a failed satellite based on the Gauss pseudospectral method

NASA Astrophysics Data System (ADS)

Chu, Xiaoyu; Zhang, Jingrui; Lu, Shan; Zhang, Yao; Sun, Yue

2016-11-01

This paper presents a trajectory planning algorithm to optimise the collision avoidance of a chasing spacecraft operating in an ultra-close proximity to a failed satellite. The complex configuration and the tumbling motion of the failed satellite are considered. The two-spacecraft rendezvous dynamics are formulated based on the target body frame, and the collision avoidance constraints are detailed, particularly concerning the uncertainties. An optimisation solution of the approaching problem is generated using the Gauss pseudospectral method. A closed-loop control is used to track the optimised trajectory. Numerical results are provided to demonstrate the effectiveness of the proposed algorithms.