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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

A Model-Based, Bayesian Solution for Characterization of Complex Damage Scenarios in Aerospace Composite Structures

Ultrasonic damage detection and characterization is commonly used in nondestructive evaluation (NDE) of aerospace composite components. In recent years there has been an increased development of guided wave based methods. In real materials and structures, these dispersive waves result in complicated behavior in the presence of complex damage scenarios. Model-based characterization methods utilize accurate three dimensional finite element models (FEMs) of guided wave interaction with realistic damage scenarios to aid in defect identification and classification. This work describes an inverse solution for realistic composite damage characterization by comparing the wavenumber-frequency spectra of experimental and simulated ultrasonic inspections. The composite laminate material properties are first verified through a Bayesian solution (Markov chain Monte Carlo), enabling uncertainty quantification surrounding the characterization. A study is undertaken to assess the efficacy of the proposed damage model and comparative metrics between the experimental and simulated output. The FEM is then parameterized with a damage model capable of describing the typical complex damage created by impact events in composites. The damage is characterized through a transdimensional Markov chain Monte Carlo solution, enabling a flexible damage model capable of adapting to the complex damage geometry investigated here. The posterior probability distributions of the individual delamination petals as well as the overall envelope of the damage site are determined.

H. Reed↗
NASA NTRS2009

Convective Weather Avoidance with Uncertain Weather Forecasts

Convective weather events have a disruptive impact on air traffic both in terminal area and in en-route airspaces. In order to make sure that the national air transportation system is safe and efficient, it is essential to respond to convective weather events effectively. Traffic flow control initiatives in response to convective weather include ground delay, airborne delay, miles-in-trail restrictions as well as tactical and strategic rerouting. The rerouting initiatives can potentially increase traffic density and complexity in regions neighboring the convective weather activity. There is a need to perform rerouting in an intelligent and efficient way such that the disruptive effects of rerouting are minimized. An important area of research is to study the interaction of in-flight rerouting with traffic congestion or complexity and developing methods that quantitatively measure this interaction. Furthermore, it is necessary to find rerouting solutions that account for uncertainties in weather forecasts. These are important steps toward managing complexity during rerouting operations, and the paper is motivated by these research questions. An automated system is developed for rerouting air traffic in order to avoid convective weather regions during the 20- minute - 2-hour time horizon. Such a system is envisioned to work in concert with separation assurance (0 - 20-minute time horizon), and longer term air traffic management (2-hours and beyond) to provide a more comprehensive solution to complexity and safety management. In this study, weather is dynamic and uncertain; it is represented as regions of airspace that pilots are likely to avoid. Algorithms are implemented in an air traffic simulation environment to support the research study. The algorithms used are deterministic but periodically revise reroutes to account for weather forecast updates. In contrast to previous studies, in this study convective weather is represented as regions of airspace that pilots are likely to avoid. The automated system periodically updates forecasts and reassesses rerouting decisions in order to account for changing weather predictions. The main objectives are to reroute flights to avoid convective weather regions and determine the resulting complexity due to rerouting. The eventual goal is to control and reduce complexity while rerouting flights during the 20 minute - 2 hour planning period. A three-hour simulation is conducted using 4800 flights in the national airspace. The study compares several metrics against a baseline scenario using the same traffic and weather but with rerouting disabled. The results show that rerouting can have a negative impact on congestion in some sectors, as expected. The rerouting system provides accurate measurements of the resulting complexity in the congested sectors. Furthermore, although rerouting is performed only in the 20-minute - 2-hour range, it results in a 30% reduction in encounters with nowcast weather polygons (100% being the ideal for perfectly predictable and accurate weather). In the simulations, rerouting was performed for the 20-minute - 2-hour flight time horizon, and for the en-route segment of air traffic. The implementation uses CWAM, a set of polygons that represent probabilities of pilot deviation around weather. The algorithms were implemented in a software-based air traffic simulation system. Initial results of the system's performance and effectiveness were encouraging. Simulation results showed that when flights were rerouted in the 20-minute - 2-hour flight time horizon of air traffic, there were fewer weather encounters in the first 20 minutes than for flights that were not rerouted. Some preliminary results were also obtained that showed that rerouting will also increase complexity. More simulations will be conducted in order to report conclusive results on the effects of rerouting on complexity. Thus, the use of the 20-minute - 2-hour flight time horizon weather avoidance teniques performed in the simulation is expected to provide benefits for short-term weather avoidance.

Karahan, Sinan↗
NASA NTRS1983

Software development predictors, error analysis, reliability models and software metric analysis

The use of dynamic characteristics as predictors for software development was studied. It was found that there are some significant factors that could be useful as predictors. From a study on software errors and complexity, it was shown that meaningful results can be obtained which allow insight into software traits and the environment in which it is developed. Reliability models were studied. The research included the field of program testing because the validity of some reliability models depends on the answers to some unanswered questions about testing. In studying software metrics, data collected from seven software engineering laboratory (FORTRAN) projects were examined and three effort reporting accuracy checks were applied to demonstrate the need to validate a data base. Results are discussed.

Basili, Victor↗
NASA NTRSDate not supplied

Proof-of-Concept for a Long-Term Health Metric to Quantify End of Mission Health Status in Astronauts

NASA has long used Probabilistic Risk Assessment (PRA) when high-stakes decisions need to be made about complex systems. For spaceflight medical risk, the Human Research Program’s Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) is a significant step towards robustly quantifying the risk to crew health during exploration missions. However, there remains a significant gap in the ability to comprehensively characterize and assess risk across the disparate functionalities and capabilities which comprise the entire Crew Health and Performance (CHP) system. To fill this gap, the Crew Health and Performance – Probabilistic Risk Assessment (CHP-PRA) project aims to perform risk characterization for the CHP system by assessing performance risk in addition to medical risk. This effort also includes quantifying Long-Term Health (LTH) risk in addition to in-mission risk outcomes within the CHP-PRA results. LTH risk encompasses the timeframe from immediately post-flight, through the rest of an astronaut’s career, through retirement, and until death. A proof-of-concept LTH risk metric is based on medical condition end-state, as defined by the Evidence Library, capturing the spaceflight specific medical impacts persisting into post-flight[1]. Condition outcomes in the Evidence Library progress through three Clinical Phases (CP): the diagnostic phase (CP1), the treatment/convalescent phase (CP2), and the end-state phase (CP3) which represents the detrimental effects of the condition after the crew member has recovered to the maximal extent. Each CP has an associated Task Impairment (TI), defined as the degree of crew incapacity due to experiencing the condition, and is quantified with a 0-1 range. Conditions with an associated CP3 (e.g. Sepsis, Traumatic Hypovolemic Shock, Sudden Cardiac Arrest, etc.) typically have serious consequences that can cause an astronaut to be fully or partially debilitated throughout the remainder of the mission. Consequently, the Cumulative CP3 TI End-of-Mission Health Status Metric is developed by CHP-PRA to quantify the cumulative effects of all conditions which progressed to the CP3 state throughout the entirety of the mission. Hence, this End-of-Mission Health Status Metric attempts to serve as an indicator of an astronaut’s health state at the time of landing. The severity of the lingering effects of in-mission medical events are dependent on mission activities and the level of available in-mission medical care. This allows the associated cumulative TI metric to be used in comparison with the crew’s end of mission health status for different levels of in-mission resources. This presentation provides the strategy for using CP3 as an LTH metric component, as well as a proof-of-concept demonstration of LTH risk characterization using this component.

long term health↗
NASA NTRS2020

ARCSTONE: Calibration of Lunar Spectral Reflectance from Space

Detecting and improving the scientific understanding of global trends in complex Earth systems, such as climate, increasingly depends on assimilating datasets from multiple instruments and platforms over decadal timescales. Calibration accuracy, stability, and inter-consistency among different instruments are key to developing reliable composite data records from sensors in low Earth and geostationary orbits, but achieving sufficiently low uncertainties for these performance metrics poses a significant challenge. Space-borne instruments commonly carry on-board references for calibration at various wavelengths, but these increase mass and mission complexity, and are subject to degradation in the space environment. The Moon can be considered a natural solar diffuser which can be observed as a calibration target by most spaceborne Earth-observing instruments. Since the lunar surface reflectance is effectively time-invariant, establishing the Moon as a high-accuracy calibration reference enables broad inter-calibration opportunities even between temporally non-overlapping instruments and provides an exo-atmospheric absolute radiometric standard. The ARCSTONE mission goal is to establish the Moon as a reliable reference for high-accuracy on-orbit calibration in the visible and near-infrared spectral region. The ARCSTONE instrument is a compact spectrometer, which will be packaged on a CubeSat intended for low Earth orbit. It will measure the lunar spectral reflectance with accuracy < 0.5% (k=1), sufficient to establish an SI-traceable absolute lunar calibration standard when referenced to the spectral solar irradiance across the 350 to 2300 nm spectral range. This lunar reference will help to enable high-accuracy absolute calibration and inter-calibration of past, current, and future Earth-observing sensors, meteorological imagers, and long-term climate monitoring satellite systems. The ARCSTONE team will present the development status of a full-spectral-range (FSR) instrument, the intended approach to calibration and characterization, and the planned path toward mission implementation.

calibration↗
NASA NTRSDate not supplied

ARCSTONE: Calibration of Lunar Spectral Reflectance from Space

Detecting and improving the scientific understanding of global trends in complex Earth systems, such as climate, increasingly depends on assimilating datasets from multiple instruments and platforms over decadal timescales. Calibration accuracy, stability, and inter-consistency among different instruments are key to developing reliable composite data records from sensors in low Earth and geostationary orbits, but achieving sufficiently low uncertainties for these performance metrics poses a significant challenge. Space-borne instruments commonly carry on-board references for calibration at various wavelengths, but these increase mass and mission complexity, and are subject to degradation in the space environment. The Moon can be considered a natural solar diffuser which can be observed as a calibration target by most spaceborne Earth-observing instruments. Since the lunar surface reflectance is effectively time-invariant, establishing the Moon as a high-accuracy calibration reference enables broad inter-calibration opportunities even between temporally non-overlapping instruments and provides an exo-atmospheric absolute radiometric standard. The ARCSTONE mission goal is to establish the Moon as a reliable reference for high-accuracy on-orbit calibration in the visible and near-infrared spectral region. The ARCSTONE instrument is a compact spectrometer, which will be packaged on a CubeSat intended for low Earth orbit. It will measure the lunar spectral reflectance with accuracy < 0.5% (k=1), sufficient to establish an SI-traceable absolute lunar calibration standard when referenced to the spectral solar irradiance across the 350 to 2300 nm spectral range. This lunar reference will help to enable high-accuracy absolute calibration and inter-calibration of past, current, and future Earth-observing sensors, meteorological imagers, and long-term climate monitoring satellite systems. The ARCSTONE team will present the development status of a full-spectral-range (FSR) instrument, the intended approach to calibration and characterization, and the planned path toward mission implementation.

Moon↗
NASA NTRS2013

Vehicle Integrated Prognostic Reasoner (VIPR) Metric Report

This document outlines a set of metrics for evaluating the diagnostic and prognostic schemes developed for the Vehicle Integrated Prognostic Reasoner (VIPR), a system-level reasoner that encompasses the multiple levels of large, complex systems such as those for aircraft and spacecraft. VIPR health managers are organized hierarchically and operate together to derive diagnostic and prognostic inferences from symptoms and conditions reported by a set of diagnostic and prognostic monitors. For layered reasoners such as VIPR, the overall performance cannot be evaluated by metrics solely directed toward timely detection and accuracy of estimation of the faults in individual components. Among other factors, overall vehicle reasoner performance is governed by the effectiveness of the communication schemes between monitors and reasoners in the architecture, and the ability to propagate and fuse relevant information to make accurate, consistent, and timely predictions at different levels of the reasoner hierarchy. We outline an extended set of diagnostic and prognostics metrics that can be broadly categorized as evaluation measures for diagnostic coverage, prognostic coverage, accuracy of inferences, latency in making inferences, computational cost, and sensitivity to different fault and degradation conditions. We report metrics from Monte Carlo experiments using two variations of an aircraft reference model that supported both flat and hierarchical reasoning.

Cornhill, Dennis↗
NASA NTRS1995

A relational metric, its application to domain analysis, and an example analysis and model of a remote sensing domain

An objective and quantitative method has been developed for deriving models of complex and specialized spheres of activity (domains) from domain-generated verbal data. The method was developed for analysis of interview transcripts, incident reports, and other text documents whose original source is people who are knowledgeable about, and participate in, the domain in question. To test the method, it is applied here to a report describing a remote sensing project within the scope of the Earth Observing System (EOS). The method has the potential to improve the designs of domain-related computer systems and software by quickly providing developers with explicit and objective models of the domain in a form which is useful for design. Results of the analysis include a network model of the domain, and an object-oriented relational analysis report which describes the nodes and relationships in the network model. Other products include a database of relationships in the domain, and an interactive concordance. The analysis method utilizes a newly developed relational metric, a proximity-weighted frequency of co-occurrence. The metric is applied to relations between the most frequently occurring terms (words or multiword entities) in the domain text, and the terms found within the contexts of these terms. Contextual scope is selectable. Because of the discriminating power of the metric, data reduction from the association matrix to the network is simple. In addition to their value for design. the models produced by the method are also useful for understanding the domains themselves. They can, for example, be interpreted as models of presence in the domain.

Mcgreevy, Michael W.↗
NASA NTRS2015

Quantifying Mapping Orbit Performance in the Vicinity of Primitive Bodies

Predicting and quantifying the capability of mapping orbits in the vicinity of primitive bodies is challenging given the complex orbit geometries that exist and the irregular shape of the bodies themselves. This paper employs various quantitative metrics to characterize the performance and relative effectiveness of various types of mapping orbits including terminator, quasi-terminator, hovering, pingpong, and conic-like trajectories. Metrics of interest include surface area coverage, lighting conditions, and the variety of viewing angles achieved. The metrics discussed in this investigation are intended to enable mission designers and project stakeholders to better characterize candidate mapping orbits during preliminary mission formulation activities.The goal of this investigation is to understand the trade space associated with carrying out remotesensing campaigns at small primitive bodies in the context of a robotic space mission. Specifically,this study seeks to understand the surface viewing geometries, ranges, etc. that are available fromseveral commonly proposed mapping orbits architectures.

Pavlak, Thomas A.↗
NASA NTRS2015

Quantifying Mapping Orbit Performance in the Vicinity of Primitive Bodies

Predicting and quantifying the capability of mapping orbits in the vicinity of primitive bodies is challenging given the complex orbit geometries that exist and the irregular shape of the bodies themselves. This paper employs various quantitative metrics to characterize the performance and relative effectiveness of various types of mapping orbits including terminator, quasi-terminator, hovering, ping pong, and conic-like trajectories. Metrics of interest include surface area coverage, lighting conditions, and the variety of viewing angles achieved. The metrics discussed in this investigation are intended to enable mission designers and project stakeholders to better characterize candidate mapping orbits during preliminary mission formulation activities. The goal of this investigation is to understand the trade space associated with carrying out remote sensing campaigns at small primitive bodies in the context of a robotic space mission. Specifically, this study seeks to understand the surface viewing geometries, ranges, etc. that are available from several commonly proposed mapping orbits architectures

Pavlak, Thomas A.↗
NASA NTRS1990

Pragmatic quality metrics for evolutionary software development models

Due to the large number of product, project, and people parameters which impact large custom software development efforts, measurement of software product quality is a complex undertaking. Furthermore, the absolute perspective from which quality is measured (customer satisfaction) is intangible. While we probably can't say what the absolute quality of a software product is, we can determine the relative quality, the adequacy of this quality with respect to pragmatic considerations, and identify good and bad trends during development. While no two software engineers will ever agree on an optimum definition of software quality, they will agree that the most important perspective of software quality is its ease of change. We can call this flexibility, adaptability, or some other vague term, but the critical characteristic of software is that it is soft. The easier the product is to modify, the easier it is to achieve any other software quality perspective. This paper presents objective quality metrics derived from consistent lifecycle perspectives of rework which, when used in concert with an evolutionary development approach, can provide useful insight to produce better quality per unit cost/schedule or to achieve adequate quality more efficiently. The usefulness of these metrics is evaluated by applying them to a large, real world, Ada project.

Royce, Walker↗
NASA NTRSDate not supplied

Verification of Viscous Goal-Based Anisotropic Mesh Adaptation

Adaptive unstructured mesh techniques have a limited, but growing impact on production analysis workflows where the control of discretization error is critical to obtaining reliable simulation results. Recent progress has matured a number of independent implementations of flow solvers, anisotropic metric construction methods, and anisotropic mesh adaptation mechanics. A key ingredient for the broader acceptance of unstructured mesh adaptation is the verification of these implementations. Anisotropic metric construction methods are evaluated with analytically defined primal fields and the corresponding entropy variables as adjoint fields. This allows the comparison of different metric formulations and different implementations of the same formulation without the complications of a flow and adjoint solution method. The convergence of the output associated with the entropy variable adjoint is studied for mesh adaptation to these fields and a manufactured solution. Mesh adapted drag output is studied for two simple wings in compressible laminar flow to show fine-mesh convergence of multiple metric construction methods to less than a single drag count. The documentation of these verification exercises helps to prepare these goal-based methods for routine use in more complex simulations for production workflows.

mesh adaptation↗
NASA NTRS1993

Space Station Facility government estimating

This new, unique Cost Engineering Report introduces the 800-page, C-100 government estimate for the Space Station Processing Facility (SSPF) and Volume IV Aerospace Construction Price Book. At the January 23, 1991, bid opening for the SSPF, the government cost estimate was right on target. Metric, Inc., Prime Contractor, low bid was 1.2 percent below the government estimate. This project contains many different and complex systems. Volume IV is a summary of the cost associated with construction, activation and Ground Support Equipment (GSE) design, estimating, fabrication, installation, testing, termination, and verification of this project. Included are 13 reasons the government estimate was so accurate; abstract of bids, for 8 bidders and government estimate with additive alternates, special labor and materials, budget comparison and system summaries; and comments on the energy credit from local electrical utility. This report adds another project to our continuing study of 'How Does the Low Bidder Get Low and Make Money?' which was started in 1967, and first published in the 1973 AACE Transaction with 18 ways the low bidders get low. The accuracy of this estimate proves the benefits of our Kennedy Space Center (KSC) teamwork efforts and KSC Cost Engineer Tools which are contributing toward our goals of the Space Station.

Brown, Joseph A.↗
NASA NTRS1993

Estimating and bidding for the Space Station Processing Facility

This new, unique Cost Engineering Report introduces the 800-page, C-100 government estimate for the Space Station Processing Facility (SSPF) and Volume IV Aerospace Construction Price Book. At the January 23, 1991, bid opening for the SSPF, the government cost estimate was right on target. Metric, Inc., Prime Contractor, low bid was 1.2 percent below the government estimate. This project contains many different and complex systems. Volume IV is a summary of the cost associated with construction, activation and Ground Support Equipment (GSE) design, estimating, fabrication, installation, testing, termination, and verification of this project. Included are 13 reasons the government estimate was so accurate; abstract of bids, for 8 bidders and government estimate with additive alternates, special labor and materials, budget comparison and system summaries; and comments on the energy credit from local electrical utility. This report adds another project to our continuing study of 'How Does the Low Bidder Get Low and Make Money?' which was started in 1967, and first published in the 1973 AACE Transaction with 10 more ways the low bidder got low. The accuracy of this estimate proves the benefits of our Kennedy Space Center (KSC) teamwork efforts and KSC Cost Engineer Tools which are contributing toward our goals of the Space Station.

Brown, Joseph A.↗
NASA NTRS2004

Autonomous Multi-Sensor Coordination: The Science Goal Monitor

Many dramatic earth phenomena are dynamic and coupled. In order to fully understand them, we need to obtain timely coordinated multi-sensor observations from widely dispersed instruments. Such a dynamic observing system must include the ability to Schedule flexibly and react autonomously to sciencehser driven events; Understand higher-level goals of a sciencehser defined campaign; Coordinate various space-based and ground-based resources/sensors effectively and efficiently to achieve goals. In order to capture transient events, such a 'sensor web' system must have an automated reactive capability built into its scientific operations. To do this, we must overcome a number of challenges inherent in infusing autonomy. The Science Goal Monitor (SGM) is a prototype software tool being developed to explore the nature of automation necessary to enable dynamic observing. The tools being developed in SGM improve our ability to autonomously monitor multiple independent sensors and coordinate reactions to better observe dynamic phenomena. The SGM system enables users to specify what to look for and how to react in descriptive rather than technical terms. The system monitors streams of data to identify occurrences of the key events previously specified by the scientisther. When an event occurs, the system autonomously coordinates the execution of the users' desired reactions between different sensors. The information can be used to rapidly respond to a variety of fast temporal events. Investigators will no longer have to rely on after-the-fact data analysis to determine what happened. Our paper describes a series of prototype demonstrations that we have developed using SGM and NASA's Earth Observing-1 (EO-1) satellite and Earth Observing Systems' Aqua/Terra spacecrafts' MODIS instrument. Our demonstrations show the promise of coordinating data from different sources, analyzing the data for a relevant event, autonomously updating and rapidly obtaining a follow-on relevant image. SGM was used to investigate forest fires, floods and volcanic eruptions. We are now identifying new Earth science scenarios that will have more complex SGM reasoning. By developing and testing a prototype in an operational environment, we are also establishing and gathering metrics to gauge the success of automating science campaigns.

Koratkar, Anuradha↗
NASA NTRS2004

Autonomous Multi-sensor Coordination: The Science Goal Monitor

Next-generation science and exploration systems will employ new observation strategies that will use multiple sensors in a dynamic environment to provide high quality monitoring, self-consistent analyses and informed decision making. The Science Goal Monitor (SGM) is a prototype software tool being developed to explore the nature of automation necessary to enable dynamic observing of earth phenomenon. The tools being developed in SGM improve our ability to autonomously monitor multiple independent sensors and coordinate reactions to better observe the dynamic phenomena. The SGM system enables users to specify events of interest and how to react when an event is detected. The system monitors streams of data to identify occurrences of the key events previously specified by the scientist/user. When an event occurs, the system autonomously coordinates the execution of the users desired reactions between different sensors. The information can be used to rapidly respond to a variety of fast temporal events. Investigators will no longer have to rely on after-the-fact data analysis to determine what happened. Our paper describes a series of prototype demonstrations that we have developed using SGM and NASA's Earth Observing-1 (EO-1) satellite and Earth Observing Systems Aqua/Terra spacecrafts MODIS instrument. Our demonstrations show the promise of coordinating data from different sources, analyzing the data for a relevant event, autonomously updating and rapidly obtaining a follow-on relevant image. SGM is being used to investigate forest fires, floods and volcanic eruptions. We are now identifying new earth science scenarios that will have more complex SGM reasoning. By developing and testing a prototype in an operational environment, we are also establishing and gathering metrics to gauge the success of automating science campaigns.

Koratkar, Anuradha↗
NASA NTRS2005

Reliability-Based Control Design for Uncertain Systems

This paper presents a robust control design methodology for systems with probabilistic parametric uncertainty. Control design is carried out by solving a reliability-based multi-objective optimization problem where the probability of violating design requirements is minimized. Simultaneously, failure domains are optimally enlarged to enable global improvements in the closed-loop performance. To enable an efficient numerical implementation, a hybrid approach for estimating reliability metrics is developed. This approach, which integrates deterministic sampling and asymptotic approximations, greatly reduces the numerical burden associated with complex probabilistic computations without compromising the accuracy of the results. Examples using output-feedback and full-state feedback with state estimation are used to demonstrate the ideas proposed.

Crespo, Luis G.↗
NASA NTRS2017

Information Theoretic Evaluation of Satellite Soil Moisture Retrievals

Microwave radiometry has a long legacy of providing estimates of remotely sensed near surfacesoil moisture measurements over continental and global scales. A consistent assessment of theerrors and uncertainties associated with these retrievals is important for their effective utilization in modeling, data assimilation and end-use application environments. This article presents an evaluationof soil moisture retrieval products from AMSR-E, ASCAT, SMOS, AMSR2 and SMAPinstruments using information theory-based metrics. These metrics rely on time series analysis ofsoil moisture retrievals for estimating the measurement error, level of randomness (entropy) andregularity (complexity) of the data. The results of the study indicate that the measurement errors inthe remote sensing retrievals are significantly larger than that of the ground soil moisture measurements.The SMAP retrievals, on the other hand, were found to have reduced errors (comparable to Preprint submitted to Remote Sensing of Environment October 1, 2017those of in-situ datasets), particularly over areas with moderate vegetation. The SMAP retrievals also demonstrate high information content relative to other retrieval products, with higher levelsof complexity and reduced entropy. Finally, a joint evaluation of the entropy and complexity ofremotely sensed soil moisture products indicates that the information content of the AMSR-E, ASCAT,SMOS and AMSR2 retrievals is low, whereas SMAP retrievals show better performance. The use of information theoretic assessments is effective in quantifying the required levels of improvements needed in the remote sensing soil moisture retrievals to enhance their utility and information content.

Information theory↗