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NASA NTRS2021

Architecture and Operations of the OSIRIS-REx Independent Navigation Team

The Origins, Spectral Interpretation, Resource Identification, Security-Regolith Explorer (OSIRIS-REx) GoddardSpace Flight Center (GSFC) Independent Navigation Team (INT) performs center-finding and landmark-basedOptical Navigation (OpNav), Orbit Determination (OD), maneuver verification, and additional analyses in support ofnavigation operations motivated by a stringent set of science requirements. The INT has adopted a streamlined andagile approach to navigation operations support via a virtual operations environment, known as "OREX-NAV",which leverages existing capabilities of the Space Science Mission Operations (SSMO) virtual Multi-MissionOperations Center (vMMOC). The virtual environment architecture of OREX-NAV enables the INT to perform dailyoperational tasks and seamlessly interface with external mission networks, regardless of physical location. Throughthe automation and process adopted, the INT is able to keep pace with the rapid cadence of required deliverables.

OSIRIS-REx↗
NASA NTRS2017

Qualitative Future Safety Risk Identification an Update

The purpose of this report is to document the results of a high-level qualitative study that was conducted to identify future aviation safety risks and to assess the potential impacts to the National Airspace System (NAS) of NASA Aviation Safety research on these risks. Multiple external sources (for example, the National Transportation Safety Board, the Flight Safety Foundation, the National Research Council, and the Joint Planning and Development Office) were used to develop a compilation of future safety issues risks, also referred to as future tall poles. The primary criterion used to identify the most critical future safety risk issues was that the issue must be cited in several of these sources as a safety area of concern. The tall poles in future safety risk, in no particular order of importance, are as follows: Runway Safety, Loss of Control In Flight, Icing Ice Detection, Loss of Separation, Near Midair Collision Human Fatigue, Increasing Complexity and Reliance on Automation, Vulnerability Discovery, Data Sharing and Dissemination, and Enhanced Survivability in the Event of an Accident.

future aviation safety risk↗
NASA NTRS2022

Natural Language Understanding and Extraction of Flight Constraints Recorded in Letters of Agreement

This paper presents an automated information extraction and inference technique using natural language processing for extracting flight operational procedures and constraints embedded in heritage air traffic management documents. The extracted flight constraints can be digitized and fit into existing airspace information exchange models such as the Aeronautical Information Exchange Model (AIXM). This approach offers a digitized solution to disseminate airspace operating conditions to diverse air users and stakeholders in the National Airspace System (NAS). Furthermore, the digitized flight procedures can provide operational flexibility for emerging advanced air mobility providers and reduce traffic controller workload while maintaining current safety standards. To demonstrate this process, 1,972 Letters of Agreement (LOAs) have been selected for processing, named entity extraction, constraint identification and extraction. This dataset is derived from a subset of documents related to Air Route Traffic Control Centers (ARTCC) operations. We experimented with various traditional information extraction techniques, state-of-the-art machine learning and deep learning models to perform named entity recognition and pattern recognition on our dataset. We present the results from our experiments and demonstrate 99.0% F-1 score for named entity recognition, and a 96.6% accuracy for our entire workflow up to named entity recognition. We also discuss constraint definitions using generic patterned templates and extensions to this work in applying entity linking to digitally extracting relevant constraints.

Natural Language Processing↗
NASA NTRSDate not supplied

Natural Language Understanding and Extraction of Flight Constraints Recorded in Letters of Agreement

This paper presents an automated information extraction and inference technique using natural language processing for extracting flight operational procedures and constraints embedded in heritage air traffic management documents. The extracted flight constraints can be digitized and fit into existing airspace information exchange models such as the Aeronautical Information Exchange Model (AIXM). This approach offers a digitized solution to disseminate airspace operating conditions to diverse air users and stakeholders in the National Airspace System (NAS). Furthermore, the digitized flight procedures can provide operational flexibility for emerging advanced air mobility providers and reduce traffic controller workload while maintaining current safety standards. To demonstrate this process, 1,972 Letters of Agreement (LOAs) have been selected for processing, named entity extraction, constraint identification and extraction. This dataset is derived from a subset of documents related to Air Route Traffic Control Centers (ARTCC) operations. We experimented with various traditional information extraction techniques, state-of-the-art machine learning and deep learning models to perform named entity recognition and pattern recognition on our dataset. We present the results from our experiments and demonstrate 99.0% F-1 score for named entity recognition, and a 96.6% accuracy for our entire workflow up to named entity recognition. We also discuss constraint definitions using generic patterned templates and extensions to this work in applying entity linking to digitally extracting relevant constraints.

Natural Language Processing↗
NASA NTRS2006

Real-Time Diagnosis of Faults Using a Bank of Kalman Filters

A new robust method of automated real-time diagnosis of faults in an aircraft engine or a similar complex system involves the use of a bank of Kalman filters. In order to be highly reliable, a diagnostic system must be designed to account for the numerous failure conditions that an aircraft engine may encounter in operation. The method achieves this objective though the utilization of multiple Kalman filters, each of which is uniquely designed based on a specific failure hypothesis. A fault-detection-and-isolation (FDI) system, developed based on this method, is able to isolate faults in sensors and actuators while detecting component faults (abrupt degradation in engine component performance). By affording a capability for real-time identification of minor faults before they grow into major ones, the method promises to enhance safety and reduce operating costs. The robustness of this method is further enhanced by incorporating information regarding the aging condition of an engine. In general, real-time fault diagnostic methods use the nominal performance of a "healthy" new engine as a reference condition in the diagnostic process. Such an approach does not account for gradual changes in performance associated with aging of an otherwise healthy engine. By incorporating information on gradual, aging-related changes, the new method makes it possible to retain at least some of the sensitivity and accuracy needed to detect incipient faults while preventing false alarms that could result from erroneous interpretation of symptoms of aging as symptoms of failures. The figure schematically depicts an FDI system according to the new method. The FDI system is integrated with an engine, from which it accepts two sets of input signals: sensor readings and actuator commands. Two main parts of the FDI system are a bank of Kalman filters and a subsystem that implements FDI decision rules. Each Kalman filter is designed to detect a specific sensor or actuator fault. When a sensor or actuator fault occurs, large estimation errors are generated by all filters except the one using the correct hypothesis. By monitoring the residual output of each filter, the specific fault that has occurred can be detected and isolated on the basis of the decision rules. A set of parameters that indicate the performance of the engine components is estimated by the "correct" Kalman filter for use in detecting component faults. To reduce the loss of diagnostic accuracy and sensitivity in the face of aging, the FDI system accepts information from a steady-state-condition-monitoring system. This information is used to update the Kalman filters and a data bank of trim values representative of the current aging condition.

Kobayashi, Takahisa↗
NASA NTRS2012

Rapid Analysis, Self-Calibrating Array for Air Monitoring

Human space missions have critical needs for monitoring and control for life support systems. These systems have monitoring needs that include feedback for closed loop processes and quality control for environmental factors. Sensors and monitoring technologies assure that the air environment and water supply for the astronaut crew habitat fall within acceptable limits, and that the life support system is functioning properly and efficiently. The longer the flight duration and the more distant the destination, the more critical it becomes to have carefully monitored and automated control systems for life support. Past experiments with the JPL ENose have demonstrated a lifetime of the sensor array, with the software, of around 18 months. The lifetime of the calibration, for some analytes, was as long as 24 months. We are working on a sensor array and new algorithms that will include sensor response time in the analysis. The preliminary array analysis for two analytes shows that the analysis time, of an event, can be dropped from 45 minutes to less than10 minutes and array training time can be cut substantially. We will describe the lifetime testing of an array and show lifetime data on individual sensors. This progress will lead to more rapid identification of analytes, and faster training time of the array.

Self Calibrating↗
NASA NTRS2023

Plant Disease Detection: Exploring Applications in Hyperspectral Imaging and Machine Learning for Agriculture

The threat of crop disease on food security and agriculture is projected to escalate, leading to reduced crop yields, global economic loss, and endangered food availability to vulnerable populations. Early identification of plant disease is crucial to combatting the crisis but traditional manual methods for disease detection are laborious and may miss early signs of infection. The proposed solution suggests equipping a drone with a hyperspectral camera to collect images and analyzing the data with neural networks trained to flag and classify infected plants. This approach offers a faster, more accurate, and potentially more cost-effective alternative to current practices. While the expensive and complex nature of hyperspectral imaging (HSI) may be an obstacle to the adoption of the drone, rapidly advancing technologies compounded with rental-based usage may make these tools simpler, cheaper, and more accessible to a wider audience. The research further discusses the potential for automated flight paths and the expansion of disease detection to a broader range of crops.

plant disease detection↗
NASA NTRS2013

Identification of Crew-Systems Interactions and Decision Related Trends

NASA Vehicle System Safety Technology (VSST) project management uses systems analysis to identify key issues and maintain a portfolio of research leading to potential solutions to its three identified technical challenges. Statistical data and published safety priority lists from academic, industry and other government agencies were reviewed and analyzed by NASA Aviation Safety Program (AvSP) systems analysis personnel to identify issues and future research needs related to one of VSST's technical challenges, Crew Decision Making (CDM). The data examined in the study were obtained from the National Transportation Safety Board (NTSB) Aviation Accident and Incident Data System, Federal Aviation Administration (FAA) Accident/Incident Data System and the NASA Aviation Safety Reporting System (ASRS). In addition, this report contains the results of a review of safety priority lists, information databases and other documented references pertaining to aviation crew systems issues and future research needs. The specific sources examined were: Commercial Aviation Safety Team (CAST) Safety Enhancements Reserved for Future Implementation (SERFIs), Flight Deck Automation Issues (FDAI) and NTSB Most Wanted List and Open Recommendations. Various automation issues taxonomies and priority lists pertaining to human factors, automation and flight design were combined to create a list of automation issues related to CDM.

Jones, Sharon Monica↗
NASA NTRS2007

Automated Rocket Propulsion Test Management

The Rocket Propulsion Test-Automated Management System provides a central location for managing activities associated with Rocket Propulsion Test Management Board, National Rocket Propulsion Test Alliance, and the Senior Steering Group business management activities. A set of authorized users, both on-site and off-site with regard to Stennis Space Center (SSC), can access the system through a Web interface. Web-based forms are used for user input with generation and electronic distribution of reports easily accessible. Major functions managed by this software include meeting agenda management, meeting minutes, action requests, action items, directives, and recommendations. Additional functions include electronic review, approval, and signatures. A repository/library of documents is available for users, and all items are tracked in the system by unique identification numbers and status (open, closed, percent complete, etc.). The system also provides queries and version control for input of all items.

Walters, Ian↗
NASA NTRS2001

New Data Source for Studying and Modelling the Topside Ionosphere

The existing uncertainties about density profiles in the topside ionosphere, i.e., in the height regime from hmF2 to approx. 2000 km, requires the search for new data sources. Millions of ionograms had been recorded by the ISIS and Alouette satellites in the sixties and seventies, that never were analyzed in terms of electron density profiles. In recent years an effort started to digitize the analog recordings to prepare the ionograms for computerized analysis. This paper shows how the digital ionograms are processed and the electron density profiles (from satellite orbit altitude, 1400 km for ISIS-2, down to the F peak) are calculated. The most difficult part of the task is the automatic scaling of the echo traces in the ISIS ionograms. Unlike the ionograms from modern ionosondes, the ISIS ionograms do not identify the wave polarization of the different echo traces, so physical logic must be applied to identify the ordinary ()) and extraordinary (X) traces, and this is not always successful. Characteristic resonance features seen in the topside ionograms occur at the gyro and plasma frequencies. An elaborate scheme was developed to identify these resonance frequencies in order to determine the local plasma and gyrofrequencies. This information helps in the identification of the O and X traces, and it provides the starting density of the electron density profile. The inversion of the echo traces into electron density profiles uses the same modified Chebyshev polynomial fitting technique that is successfully applied in the ground-based Digisonde network. The automatic topside ionogram scaler with true height algorithm TOPIST is successfully scaling approx. 70% of the ionograms. An 'editing process' is available to manually scale the more difficult ionograms. The home page for the ISIS project is at http://nssdc.gsfc.nasa.gov/space/isis/isis-status.html. It provides access to as of January 2001, 3000,000 digitized ISIS ionogram data and to related software. A search page lets users select data location, time, and a host of other search criteria. The automated processing of the ISIS ionograms will begin later this year and the electron density profiles will be made available from the project home page. The ISIS data restoration efforts are supported through NASA's Applied Systems and Information Research Program.

Huang, Xue-Qin↗
NASA NTRS2014

Automated Optical Meteor Fluxes and Preliminary Results of Major Showers

NASA's Meteoroid Environment Office (MEO) recently established a two‐station system to calculate daily automated meteor fluxes in the millimeter‐size‐range for both single‐station and double‐station meteors. The cameras each consist of a 17 mm focal length Schneider lens (f/0.95) on a Watec 902H2 Ultimate CCD video camera, producing a 21.7x15.5 degree field of view. This configuration sees meteors down to a magnitude of +6. This paper outlines the concepts of the system, the hardware and software, and results of 3,000+ orbits from the first 18 months of operations. Video from the cameras are run through ASGARD (All Sky and Guided Automatic Real‐time Detection), which performs the meteor detection/photometry, and invokes MILIG and MORB (Borovicka 1990) codes to determine the trajectory, speed, and orbit of the meteor. A subroutine in ASGARD allows for approximate shower identification in single‐station detections. The ASGARD output is used in routines to calculate the flux. Before a flux can be calculated, a weather algorithm indicates if sky conditions are clear enough to calculate fluxes, at which point a limiting magnitude algorithm is employed. The limiting stellar magnitude is found using astrometry.net (Lang et al. 2012) to identify stars and translated to the corresponding shower and sporadic limiting meteor magnitude. It is found every 10 minutes and is able to react to quickly changing sky conditions. The extensive testing of these results on the Geminids and Eta Aquariids is shown. The flux involves dividing the number of meteors by the collecting area of the system, over the time interval for which that collecting area is valid. The flux algorithm employed here differs from others currently in use in that it does not make the gross oversimplication of choosing a single height to calculate the collection area of the system. In the MEO system, the volume is broken up into a set of height intervals, with the collecting areas determined by the position of the active shower or sporadic source radiant. The flux per height interval is calculated and summed to obtain the total meteor flux. Both single station and double station fluxes are currently found daily. Geminid fluxes on the peak night in 2012 (12‐14‐2012) were 0.058 meteors/km2/hr as found with double‐station meteors and 0.057 meteors/ km2/hr as found with single‐station meteors, to a limiting magnitude of +6.5. Both of those numbers are in agreement with the well‐calibrated fluxes from the Canadian Meteor Orbit Radar. Along with flux algorithms and initial flux results, presented will be results from the first 18 months of operation, covering 3,000+ meteoroid orbits.

Blaauw, R.↗
NASA NTRS1996

Cloud identification using genetic algorithms and massively parallel computation

As a Guest Computational Investigator under the NASA administered component of the High Performance Computing and Communication Program, we implemented a massively parallel genetic algorithm on the MasPar SIMD computer. Experiments were conducted using Earth Science data in the domains of meteorology and oceanography. Results obtained in these domains are competitive with, and in most cases better than, similar problems solved using other methods. In the meteorological domain, we chose to identify clouds using AVHRR spectral data. Four cloud speciations were used although most researchers settle for three. Results were remarkedly consistent across all tests (91% accuracy). Refinements of this method may lead to more timely and complete information for Global Circulation Models (GCMS) that are prevalent in weather forecasting and global environment studies. In the oceanographic domain, we chose to identify ocean currents from a spectrometer having similar characteristics to AVHRR. Here the results were mixed (60% to 80% accuracy). Given that one is willing to run the experiment several times (say 10), then it is acceptable to claim the higher accuracy rating. This problem has never been successfully automated. Therefore, these results are encouraging even though less impressive than the cloud experiment. Successful conclusion of an automated ocean current detection system would impact coastal fishing, naval tactics, and the study of micro-climates. Finally we contributed to the basic knowledge of GA (genetic algorithm) behavior in parallel environments. We developed better knowledge of the use of subpopulations in the context of shared breeding pools and the migration of individuals. Rigorous experiments were conducted based on quantifiable performance criteria. While much of the work confirmed current wisdom, for the first time we were able to submit conclusive evidence. The software developed under this grant was placed in the public domain. An extensive user's manual was written and distributed nationwide to scientists whose work might benefit from its availability. Several papers, including two journal articles, were produced.

Buckles, Bill P.↗
NASA NTRS1986

Stability, reliability and cross-mode correlations of tests in a recommended 8-minute performance assessment battery

A need exists for an automated performance test system to study drugs, agents, treatments, and stresses of interest to the aviation, space, and environmental medical community. The purpose of this present study is to evaluate tests for inclusion in the NASA-sponsored Automated Performance Test System (APTS). Twenty-one subjects were tested over 10 replications with tests previously identified as good candidates for repeated-measure research. The tests were concurrently administered in paper-and-pencil and microcomputer modes. Performance scores for the two modes were compared. Data from trials 1 to 10 were examined for indications of test stability and reliability. Nine of the ten APT system tests achieved stability. Reliabilities were generally high. Cross-correlation of microbased tests with traditional paper-and-pencil versions revealed similarity of content within tests in the different modes, and implied at least three cognition and two motor factors. This protable, inexpensive, rugged, computerized battery of tests is recommended for use in repeated-measures studies of environmental and drug effects on performance. Identification of other tests compatible with microcomputer testing and potentially capable of tapping previously unidentified factors is recommended. Documentation of APTS sensitivity to environmental agents is available for more than a dozen facilities and is reported briefly. Continuation of such validation remains critical in establishing the efficacy of APTS tests.

Wilkes, R. L.↗
NASA NTRSDate not supplied

A Concept of Operations (ConOps) of an In-time Aviation Safety Management System (IASMS) for Advanced Air Mobility (AAM)

The growth of new emerging operations involving Advanced Air Mobility (AAM) necessitates developing a perspective for an In-time Aviation Safety Management System (IASMS). This perspective advances from the National Academies report on IASMS and its recommendation for developing a Concept of Operations (ConOps) for IASMS. A ConOps has been developed for In-time System-Wide Safety Assurance (ISSA) from which the IASMS ConOps pivots to provide a robust scope commensurate with the broad vision defined by the National Academies. The IASMS ConOps focuses on emerging operations and spans innovations in Unmanned Aircraft System (UAS) and an increasingly complex ecosystem comprised of a widening mix of vehicles and technologies, Urban Air Mobility (UAM) with industry-federated services, traditional operations, as well as new supersonic aircraft and space launch systems.The challenge for the IASMS ConOps is to be broad to encompass innovations in the coming years and decades while agile to ensure levels of safety compatible with operational and certification requirements of the National Airspace System (NAS). The IASMS ConOps interweaves increasing complexity of operational safety capabilities and unlocking UAS Maturity Levels (UMLs). The relationships between increased complexity of automation and automated systems, fewer operators who are not as traditionally higher skilled, more complex operational environments, and aviation operations management with mixed aircraft and equipage pose a multi-dimensional space for IASMS capabilities essential for safety assurance and risk management. Instantiating IASMS capabilities and how they would be integral to AAM operations and increasing maturity of UAM could be accomplished through a series of Safety Demonstrators. These Safety Demonstrators could provide increased understanding and insight into use of controls for risk mitigation, means of compliance for certification, and operational experience with safety services such as in relation to contingency management. The IASMS capabilities can be viewed as initially residing with the vehicle, airspace, and Supplemental Data Service Provider (SDSP). For example, vehicle capabilities include communications including the command and control link, Remote Identification (ID), conflict advisory/alerting, and UAS system monitoring. These capabilities monitor and assess data such as battery health, aircraft state, and human performance. Complexity of ISAMS capabilities depends on a number of factors. These factors are intendedonly as a notional categorization with the purpose being to reflect the complexity of the AAM ecosystem that would drive up the complexity of ISSA capabilities including systems, sensors, models, standards, and controls. Factors could include the Vehicle Flight Management, Environment, Airspace, and Contingency Management. Each of these factors can be comprised of multiple sub-factors that contribute to increasing complexity. For example, Airspace at a lower level of complexity could be dedicated to UTM operations that are unmonitored, and at a higher level of complexity could involve mixed UTM and ATM operations. The IASMS concept includes safety services that provide data and information to different participants in AAM. The roles and responsibilities of participants can be defined using the Responsible-Accountable-Consulted-Informed (RACI) analysis. For example, for the safety service involving the Remote ID, the Operator would be accountable for providing the data, the Vehicle would be responsible for transmitting it, and the USS, SDSP, Vertiports, FIMS (FAA), and Public Entities such as safety services would be informed by receiving the data. The IASMS ConOps identifies the capabilities needed for risk mitigation and safety assurance in the increasingly complex national airspace. The ConOps serves as a pathway for engaging with industry to gain operational experience including through the Safety Demonstrator series, the RACI analysis, and operational complexity factors. The ConOps serves to integrate these different perspectives to build a cohesive and cogent approach to an AAM safety management system.

In-Time Aviation Safety Management System↗
NASA NTRS2003

The NASA Smart Probe Project for real-time multiple microsensor tissue recognition

BACKGROUND: Remote surgery requires automated sensors, effectors and sensor-effector communication. The NASA Smart Probe Project has focused on the sensor aspect. METHODS: The NASA Smart Probe uses neural networks and data from multiple microsensors for a unique tissue signature in real time. Animal and human trials use several probe configurations: (1) 8-microsensor probe (2.5 mm in diameter) for rodent studies (normal and subcutaneous mammary tumor tissues), and (2) 21-gauge needle probe with 3 spectroscopic fibers and an impedance microelectrode for breast cancer diagnosis in humans. Multisensor data are collected in real time (update 100 times/s) using PCs. RESULTS: Human data (collected by NASA licensee BioLuminate) from 15 women undergoing breast biopsy distinguished normal tissue from both benign tumors and breast carcinoma. Tumor margins and necrosis are rapidly detected. CONCLUSION: Real-time tissue identification is achievable. Potential applications, including probes incorporating nanoelectrode arrays, are presented. Copyright 2003 S. Karger AG, Basel.

Biopsy/methods↗
NASA NTRS2006

Developing Formal Correctness Properties from Natural Language Requirements

This viewgraph presentation reviews the rationale of the program to transform natural language specifications into formal notation.Specifically, automate generation of Linear Temporal Logic (LTL)correctness properties from natural language temporal specifications. There are several reasons for this approach (1) Model-based techniques becoming more widely accepted, (2) Analytical verification techniques (e.g., model checking, theorem proving) significantly more effective at detecting types of specification design errors (e.g., race conditions, deadlock) than manual inspection, (3) Many requirements still written in natural language, which results in a high learning curve for specification languages, associated tools and increased schedule and budget pressure on projects reduce training opportunities for engineers, and (4) Formulation of correctness properties for system models can be a difficult problem. This has relevance to NASA in that it would simplify development of formal correctness properties, lead to more widespread use of model-based specification, design techniques, assist in earlier identification of defects and reduce residual defect content for space mission software systems. The presentation also discusses: potential applications, accomplishments and/or technological transfer potential and the next steps.

requirements engineering↗
NASA NTRSDate not supplied

Statistical Wind-Tunnel Experimentation Advancements for eVTOL Aircraft Aero-Propulsive Model Development

Compared to many conventional aircraft, electric vertical takeoff and landing (eVTOL) vehicle designs present greater aero-propulsive complexity and many interacting factors requiring development of novel testing and model development strategies. This paper describes several advances in statistically-rigorous experiment design methods for wind-tunnel testing of eVTOL aircraft enabling accurate aero-propulsive model development. The techniques are applied to a subscale tilt-rotor eVTOL aircraft configuration built at NASA Langley Research Center that has 24 independent control effectors. The general testing approach, leveraging design of experiments and response surface methodology, is outlined and followed by a detailed description of the experiment design and modeling approach employed for different phases of the wind-tunnel testing. A new approach for gravitational tare modeling is developed and validated, which reduces the required wind-tunnel test time by nearly 50%. A mostly automated trim envelope determination approach is formulated to rapidly determine the aircraft flight envelope to inform transition testing for aero-propulsive model development. Efficient powered-airframe characterization tests are conducted using a nested I-optimal design approach formulated in previous simulation-based testing. The collective wind-tunnel testing approach facilitates rapid characterization of eVTOL aircraft configurations and produces accurate aero-propulsive models that can be used in flight dynamics simulations.

design of experiments↗
NASA NTRS2017

Statistical Approaches for the Definition of Landslide Rainfall Thresholds and their Uncertainty Using Rain Gauge and Satellite Data

Models for forecasting rainfall-induced landslides are mostly based on the identification of empirical rainfall thresholds obtained exploiting rain gauge data. Despite their increased availability, satellite rainfall estimates are scarcely used for this purpose. Satellite data should be useful in ungauged and remote areas, or should provide a significant spatial and temporal reference in gauged areas. In this paper, the analysis of the reliability of rainfall thresholds based on rainfall remote sensed and rain gauge data for the prediction of landslide occurrence is carried out. To date, the estimation of the uncertainty associated with the empirical rainfall thresholds is mostly based on a bootstrap resampling of the rainfall duration and the cumulated event rainfall pairs (D,E) characterizing rainfall events responsible for past failures. This estimation does not consider the measurement uncertainty associated with D and E. In the paper, we propose (i) a new automated procedure to reconstruct ED conditions responsible for the landslide triggering and their uncertainties, and (ii) three new methods to identify rainfall threshold for the possible landslide occurrence, exploiting rain gauge and satellite data. In particular, the proposed methods are based on Least Square (LS), Quantile Regression (QR) and Nonlinear Least Square (NLS) statistical approaches. We applied the new procedure and methods to define empirical rainfall thresholds and their associated uncertainties in the Umbria region (central Italy) using both rain-gauge measurements and satellite estimates. We finally validated the thresholds and tested the effectiveness of the different threshold definition methods with independent landslide information. The NLS method among the others performed better in calculating thresholds in the full range of rainfall durations. We found that the thresholds obtained from satellite data are lower than those obtained from rain gauge measurements. This is in agreement with the literature, where satellite rainfall data underestimate the 'ground' rainfall registered by rain gauges.

landslide prediction↗