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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Applications of a Forward-Looking Interferometer for the On-board Detection of Aviation Weather Hazards

The Forward-Looking Interferometer (FLI) is a new instrument concept for obtaining measurements of potential weather hazards to alert flight crews. The FLI concept is based on high-resolution Infrared (IR) Fourier Transform Spectrometry (FTS) technologies that have been developed for satellite remote sensing, and which have also been applied to the detection of aerosols and gases for other purposes. It is being evaluated for multiple hazards including clear air turbulence (CAT), volcanic ash, wake vortices, low slant range visibility, dry wind shear, and icing, during all phases of flight. Previous sensitivity and characterization studies addressed the phenomenology that supports detection and mitigation by the FLI. Techniques for determining the range, and hence warning time, were demonstrated for several of the hazards, and a table of research instrument parameters was developed for investigating all of the hazards discussed above. This work supports the feasibility of detecting multiple hazards with an FLI multi-hazard airborne sensor, and for producing enhanced IR images in reduced visibility conditions; however, further research must be performed to develop a means to estimate the intensities of the hazards posed to an aircraft and to develop robust algorithms to relate sensor measurables to hazard levels. In addition, validation tests need to be performed with a prototype system.

West, Leanne↗
NASA NTRS1980

Assessment of the role of remote sensing in the study of inland and coastal waters

Several problems within Great Lakes, coastal, and continental shelf water were selected and organized under the topical headings of Productivity, Sedimentation, Water Dynamics, Eutrophication, and Hazardous Substances. The measurements required in the study of each of the problems were identified. An assessment was made of the present capability and the potential of remote sensing to make these measurements. The relevant remote-sensing technology for each of these classifications was discussed and needed advancements indicated.

Curfman, H. J.↗
NASA NTRS2023

Robustness of Gridded Precipitation Products for Vietnam Basins using the Comprehensive Assessment Framework of Rainfall

The use of satellite–based precipitation products (SPPs) have become increasingly prevalent as key inputs to provide regional rainfall for improving hydrological simulations in data–spare regions. This study introduces a new approach – Comprehensive Assessment Framework of Rainfall (CAFR) to evaluate six satellite–based precipitation products (SPPs) for eleven basins with different sizes across Vietnam (2007–2015). These SPPs include the Global Precipitation Mission (GPM) Integrated Multi-satellitE Retrievals for Global Precipitation Measurement Final run Version 6 (GPM IMERGF V6), Multi–Source Weighted–Ensemble Precipitation (MSWEP) V2.2, Soil Moisture to Rain (SM2RAIN) – Advanced SCATterometer (ASCAT) V1.5, Asian Precipitation–Highly–Resolved Observational Data Integration Towards Evaluation (APHRODITE) V1901, Climate Hazards group Infrared Precipitation with Stations (CHIRPS) V2.0, and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) – Climate Data Record (CDR) V1.0. With the proposed CAFR: (1) IMERGF is suggested to have the best performance overall, especially when simulating flood peaks; (2) SM2RAIN–ASCAT demonstrates the best skills in metrics related to the dry season; (3) For streamflow simulations, SPPs' performance is sensitive to basin size, with larger basins showing better performance skills. In this study, we demonstrate the capability of our proposed framework to better understand SPP applications in hydrological modeling.

Comprehensive Assessment Framework of Rainfall (CA↗
NASA NTRS2011

Lidar Systems for Precision Navigation and Safe Landing on Planetary Bodies

The ability of lidar technology to provide three-dimensional elevation maps of the terrain, high precision distance to the ground, and approach velocity can enable safe landing of robotic and manned vehicles with a high degree of precision. Currently, NASA is developing novel lidar sensors aimed at needs of future planetary landing missions. These lidar sensors are a 3-Dimensional Imaging Flash Lidar, a Doppler Lidar, and a Laser Altimeter. The Flash Lidar is capable of generating elevation maps of the terrain that indicate hazardous features such as rocks, craters, and steep slopes. The elevation maps collected during the approach phase of a landing vehicle, at about 1 km above the ground, can be used to determine the most suitable safe landing site. The Doppler Lidar provides highly accurate ground relative velocity and distance data allowing for precision navigation to the landing site. Our Doppler lidar utilizes three laser beams pointed to different directions to measure line of sight velocities and ranges to the ground from altitudes of over 2 km. Throughout the landing trajectory starting at altitudes of about 20 km, the Laser Altimeter can provide very accurate ground relative altitude measurements that are used to improve the vehicle position knowledge obtained from the vehicle navigation system. At altitudes from approximately 15 km to 10 km, either the Laser Altimeter or the Flash Lidar can be used to generate contour maps of the terrain, identifying known surface features such as craters, to perform Terrain relative Navigation thus further reducing the vehicle s relative position error. This paper describes the operational capabilities of each lidar sensor and provides a status of their development. Keywords: Laser Remote Sensing, Laser Radar, Doppler Lidar, Flash Lidar, 3-D Imaging, Laser Altimeter, Precession Landing, Hazard Detection

Amzajerdian, Farzin↗
NASA NTRSDate not supplied

Dissemination of Global Flood Information Through Nasa Disasters Program Global Initiative for Flood Forecasting and Alerting (GIFFT)

The Global Initiative for Flood Forecasting and Alerting (GIFFT) is an initiative to disseminate flood products from different sensors to global stakeholders via the Pacific Disaster Center’s (PDC) DisasterAWARE®, the NASA Disasters Mapping Portal and potentially other mechanisms. GIFFT will also generate an integrated product(s) using ensembled hydrologic models and Earth observation derived flood outputs to stakeholders globally. This initiative combines the results of several Disasters Program funded projects that focus on flood forecasting, flood severity estimation, post-event flood mapping, flooddepth estimation and resulting flood severity using remote sensing-based flood information derived from SAR and optical imagery. PDC’s DisasterAWARE platform is a global multi-hazard alerting platform that currently incorporatesModel of Models (MoM) outputs as flood “incidents,” visually depicting potential floods in the context ofpopulation and infrastructure that may become affected. Automated procedures are being developed tocategorize MoM outputs as DisasterAWARE “hazards,” allowing for their dissemination to users alongwith other flood products that assess potential impacts. PDC’s stakeholders include UN, DoD, FEMA andtheir equivalents around the world. Additionally, the DisasterALERT mobile platform has 2 million usersworldwide and is a fully functional and sustained platform used to disseminate alerts and analyticalproducts for 18 different hazard types. GIFFT has incorporated HydroSAR products that will bedistributed via DisasterAWARE.

remote sensing↗
NASA NTRS1988

Windshear detection and avoidance - Airborne systems perspective

The generalized windshear hazard index presently defined is derived from aircraft-position wind data and remotely sensed data obtained along the extended flight path by such candidate sensor technologies as microwave Doppler radar, Doppler lidar, and IR radiometry. Attention is given here to the results of a comparative evaluation of CO2 and Ho:YAG lidar sensor-employing windshear-detection systems, over a range 1-3 km ahead of the aircraft (corresponding to 15-45 sec of warning time). While the technology for a 10.6-micron CO2 lidar system is available, an optimum 2-micron REE laser crystal-based system remains to be developed.

Bowles, Roland L.↗
NASA NTRS1990

New remote sensing techniques facilitate study of earth's far-flung volcanos

The study of volcanos using remote sensing is discussed. The dynamics of volcanic eruptions and the interactions between volcanos and the atmosphere and ecosphere are examined. Remote sensing equipment can effectively detect mud flows, pyroclastic falls, debris avalanches, lava flows, and hazards to aircraft from eruption plumes. Consideration is given to the use of thermal IR imaging, weather satellites, and polar-orbiting satellites to study such features as lava flow, silica content, and SO2 distribution.

Mouginis-Mark, Peter J.↗
NASA NTRS1996

Size-Frequency Distributions of Rocks on Mars and Earth Analog Sites: Implications for Future Landed Missions

The size-frequency distribution of rocks and the Vicking landing sites and a variety of rocky locations on the Earth that formed from a number of geologic processes all have the general shape of simple exponential curves, which have been combined with remote sensing data and models on rock abundance to predict the frequency of boulders potentially hazardous to future Mars landers and rovers.

Mars rocks Viking landing sites Mars rock data↗
NASA NTRS2013

International Space Station Instmments Collect Imagery of Natural Disasters

A new focus for utilization of the International Space Station (ISS) is conducting basic and applied research that directly benefits Earth's citizenry. In the Earth Sciences, one such activity is collecting remotely sensed imagery of disaster areas and making those data immediately available through the USGS Hazards Data Distribution System, especially in response to activations of the International Charter for Space and Major Disasters (known informally as the "International Disaster Charter", or IDC). The ISS, together with other NASA orbital sensor assets, responds to IDC activations following notification by the USGS. Most of the activations are due to natural hazard events, including large floods, impacts of tropical systems, major fires, and volcanic eruptions and earthquakes. Through the ISS Program Science Office, we coordinate with ISS instrument teams for image acquisition using several imaging systems. As of 1 August 2013, we have successfully contributed imagery data in support of 14 Disaster Charter Activations, including regions in both Haiti and the east coast of the US impacted by Hurricane Sandy; flooding events in Russia, Mozambique, India, Germany and western Africa; and forest fires in Algeria and Ecuador. ISS‐based sensors contributing data include the Hyperspectral Imager for the Coastal Ocean (HICO), the ISERV (ISS SERVIR Environmental Research and Visualization System) Pathfinder camera mounted in the US Window Observational Research Facility (WORF), the ISS Agricultural Camera (ISSAC), formerly operating from the WORF, and high resolution handheld camera photography collected by crew members (Crew Earth Observations). When orbital parameters and operations support data collection, ISS‐based imagery adds to the resources available to disaster response teams and contributes to the publicdomain record of these events for later analyses.

Evans, C. A.↗
NASA NTRS2016

Precision Landing and Hazard Avoidance (PL&HA) Domain

The Precision Landing and Hazard Avoidance (PL&HA) domain addresses the development, integration, testing, and spaceflight infusion of sensing, processing, and GN&C (Guidance, Navigation and Control) functions critical to the success and safety of future human and robotic exploration missions. PL&HA sensors also have applications to other mission events, such as rendezvous and docking.

Robertson, Edward A.↗
NASA NTRSDate not supplied

Impact of Anthropogenic Activity, Climate Change, and Urbanization on Wetland Habitat in the Platte River Basin​

The Platte River Basin (PRB) is a dynamic ecosystem where wetlands play a pivotal role as essential habitats for various flora and fauna, including local and migratory birds. It provides many crucial ecosystem services that benefit humans directly and indirectly. However, anthropogenic activity, climate change, and urbanization have resulted in decline in wildlife habitat, elevated flood risk, and wetland loss. To address this issue, NASA DEVELOP partnered with Audubon Great Plains (AGP) to address the vital habitats within urban areas to protect bird species, reduce flood hazards, and analyze the potential impact of future development on wetlands. We utilized remotely sensed data from Landsat 8 Operational Land Imager (OLI), Sentinel-2 Multispectral Instrument (MSI), and Sentinel-1 Synthetic Aperture Radar (SAR) to assess land use and land cover (LULC) change. Nighttime lights data from Suomi National Polar-orbiting Partnership (NPP) Visible Infrared Imaging Radiometer Suite (VIIRS) as well as NASA Socioeconomic Data and Applications Center (SEDAC) population data were also used as inputs to simulate urban growth potential up to 2050 using the open-source FUTure Urban-Regional Environment Simulation (FUTURES) model. A broad scale analysis across 13 focal cities showed varied changes in land use patterns across the PRB, with the most notable being a decrease in agricultural land coverage and an increase in vegetation and grassland coverage. We overlaid a flood extent map with the LULC classifications in Grand Island to identify possible restoration sites under AGP’s Urban Woods and Prairies Initiative. The results for two proposed scenarios showed that at least 51 counties out of 81 in the PRB would experience growth by year 2050. The first scenario (all wetlands are protected) showed that there will be no loss of wetlands by 2050. However, the second scenario (no wetlands are protected) showed a decrease in wetland area and loss of habitat for bird conservation. The results will help AGP to lead awareness workshops for communities about wetland protection and to form impactful conservation strategies in the future.​

Nancee Uniyal↗
DOE OSTI2020

Autonomous Radiation Mapping and Quantification using an Unmanned Ground Vehicle. Part I - Environment Mapping

When characterizing facilities, advanced autonomous systems are safe, efficient, and cost-effective tools, which can safely deploy state-of-the-art instrumentation without exposing workers to radiation risks. One main focus of the research is the visual mapping of the environment.This paper presents a framework for the mapping aspect that utilizes lidar and SLAM technologies coupled with a monocular camera to create a point cloud of the environment. Upon completion, the present research work aims to provide an autonomous mobile robot the capability to localize itself and aid the user with visualizing the radiation data. Challenges: C++ node needs to properly synchronize image and point cloud data. 3D lidar has resolution of ± 3 cm. Proper camera calibration needed. Transforms need to be precise for proper alignment of image and point-cloud. Results: Voxelated point clouds. Accurate colors from calibrated cameras including details smaller than lidar resolution. Developed Robotics Operating System (ROS) package for ease of transfer to other robot platforms.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRSDate not supplied

Distributed Vision Sensing of Small Uncrewed Aircraft Systems in Urban Traffic Corridors

The NASA Advanced Air Mobility mission will enable widespread low altitude passenger travel, cargo delivery, and a variety of public services through the development of Uncrewed Aerial Systems (UAS) operations. Ensuring safe, autonomous operations in densely populated environments requires careful consideration towards hazards including other aircraft, infrastructure, and evolving weather. Small Uncrewed Aerial Systems (SUAS) present a unique hazard to UAS operations as they share airspace and may be readily operated in a non-cooperative fashion. This work investigates distributed sensing of SUAS traversing an air traffic corridor in an urban setting. This work develops a distributed vision detect and track strategy at NASA Langley Research Center. Three nodes, each with at least one global shutter camera, are distributed around a traffic corridor to surveil flight operations for two SUAS performing low altitude flight operations. Each node is equipped with a GPS and cellular modem to enable timestamping and remote control of acquisition. Node one faces a traffic roundabout with buildings in the background and achieves 99% surveillance coverage for two SUAS against building and tree backgrounds at ranges 50 to 130m. The second node points down Langley Boulevard with trees and buildings in the background and achieves 99% coverage at separation distances between 70 and 180m. The analysis for the second node is limited to ranges below 180m due to low contrast against dark, tree backgrounds. Finally, the third node points down Langley Boulevard from another perspective and achieves 99% coverage at ranges 60m to 200m against mostly building with a few sections of trees in the background.

Chester V Dolph↗
NASA NTRS2011

Comparison of In-Situ, Model and Ground Based In-Flight Icing Severity

As an aircraft flies through supercooled liquid water, the liquid freezes instantaneously to the airframe thus altering its lift, drag, and weight characteristics. In-flight icing is a contributing factor to many aviation accidents, and the reliable detection of this hazard is a fundamental concern to aviation safety. The scientific community has recently developed products to provide in-flight icing warnings. NASA's Icing Remote Sensing System (NIRSS) deploys a vertically--pointing Ka--band radar, a laser ceilometer, and a profiling multi-channel microwave radiometer for the diagnosis of terminal area in-flight icing hazards with high spatial and temporal resolution. NCAR s Current Icing Product (CIP) combines several meteorological inputs to produce a gridded, three-dimensional depiction of icing severity on an hourly basis. Pilot reports are the best and only source of information on in-situ icing conditions encountered by an aircraft. The goal of this analysis was to ascertain how the testbed NIRSS icing severity product and the operational CIP severity product compare to pilot reports of icing severity, and how NIRSS and CIP compare to each other. This study revealed that the icing severity product from the ground-based NASA testbed system compared very favorably with the operational model-based product and pilot reported in-situ icing.

Johnston, Christopher J.↗
NASA NTRSDate not supplied

Advanced Capabilities for Emergency Response Operations (ACERO)

The Advanced Capabilities for Emergency Response Operations (ACERO) project is expected to develop, integrate, demonstrate, and transition to operations, evolving aviation technologies from NASA and industry to identify, monitor, and suppress wildland fires as a means to enhance safety, improve operational efficiency, and prevent economic loss. Some of the concepts ACERO explores are: wildfire airspace mangement to improve safety and resource utilization during a disaster, applying new aviation technologies to improve safety and demonstrate new mission-support capabilities, second-shift operations to enable progress towards 24/7 aerial response, and the integration of capabilities across NASA's Aeronautics Research, Science, and Space Technology mission directorates to enable expanded and scalable operations. Realizing this vision is expected to bring positive impact to such areas as: consistency of technology adoption through a unified concept of operations, airspace coordination and deconfliction that integrates portable solutions and enables diverse operations, remote sensing and data fusion for modeling and predictions that support in-time decision making, aircraft technologies for hazard avoidance and state management, and increased response capabilities through persistent communications and surveillance. ACERO continues the research begun under the Scalable Traffic Management for Emergency Response Operations (STEReO) activity, which brings together several technologies in Unmanned Aircraft Systems (UAS) Traffic Management (UTM), Autonomy, Communications, Human Factors, and Domain Expertise & Tools, aimed at providing scalability and flexibility, as well as operational resiliency to dynamic changes during a disaster event. Some of the concepts STEReO explores are: collaborative tools to ingest remote sensing information and distribute a common mission operating picture, apply ad-hoc communication networks to facilitate timely information sharing and communication of changes, vehicle-to-vehicle and onboard autonomy technologies ensure the safety and resiliency of operations, and apply NASA’s UAS traffic management system (UTM) as a public safety UAS Service Supplier (USS) to access and coordinate use of the airspace by both manned and unmanned operations. The potential benefits of STEReO include: standardized, cross-platform communication means increased interoperability and ease of cooperation/collaboration, increased situation awareness and common operating picture allow for earlier detection and decision making, and scalable to size and complexity of environment, operations, and mission objectives. This presentation gives an informational overview of the ACERO and STEReO projects to the Council of Western State Foresters (CWSF) Western State Fire Managers (WSFM) Committee.

emergency response operations↗
NASA NTRS2010

Climate Change, Nutrition and Food Security in Sub-Saharan Africa

Food security and nutrition in sub-Saharan Africa have long been affected by variations in the weather. Vulnerability to these hazards, along with economic shocks and an adverse political environment, is often uneven in a community. Some individuals and households are more susceptible to emergencies or crises than others, and thus determining who is most vulnerable are and how they are responding to a shock or crises is essential to understand the impact on food security. Daily, quantitative and global observations derived from satellite remote sensing instruments can contribute to understanding how food production has declined due to drought, flood or other weather-related hazard, but it can say nothing about the likelihood that the people living in that area are suffering food insecurity as a result. As Amartya Sen argued, a famine can occur even when there is an absolute surplus of food in a region. Thus organizations like the US Agency for International Development's Famine Early Warning Systems Network (FEWS NET) work to integrate biophysical and socio-economic indicators together with on-the ground assessments to estimate the food security consequences of a variety of events. Climate change is likely to restructure local, regional and global agricultural systems and commodity markets. Although remote sensing information has been used to identify seasonal production declines for the past two decades, new ways of using the data will need to be developed in order to understand, document and respond to the impact of climate change on food security as it is manifested in shorter term shocks. In this article, the contribution of remote sensing is explained, along with the other factors that affect food security

Brown, Molly E.↗
NASA NTRS2011

Process Algebra Approach for Action Recognition in the Maritime Domain

The maritime environment poses a number of challenges for autonomous operation of surface boats. Among these challenges are the highly dynamic nature of the environment, the onboard sensing and reasoning requirements for obeying the navigational rules of the road, and the need for robust day/night hazard detection and avoidance. Development of full mission level autonomy entails addressing these challenges, coupled with inference of the tactical and strategic intent of possibly adversarial vehicles in the surrounding environment. This paper introduces PACIFIC (Process Algebra Capture of Intent From Information Content), an onboard system based on formal process algebras that is capable of extracting actions/activities from sensory inputs and reasoning within a mission context to ensure proper responses. PACIFIC is part of the Behavior Engine in CARACaS (Cognitive Architecture for Robotic Agent Command and Sensing), a system that is currently running on a number of U.S. Navy unmanned surface and underwater vehicles. Results from a series of experimental studies that demonstrate the effectiveness of the system are also presented.

process algebras↗