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The areas covering the meteorological hazards program are: severe storms and the hazards to flight generated by severe storms; clear air turbulence; icing; warm fog dissipation; and landing systems. Remote sensing of ozone by satellites, and the use of satellites as data relays is also discussed.
The present generalized windshear hazard index is formulated in terms of wind conditions at the given aircraft position and of remotely-sensed information obtained along the extended flight path. Overall system functional requirements are addressed by comparing microwave Doppler radar, Doppler lidar, and IR radiometry candidate techniques, giving attention to airborne CO2 and Ho:YAG lidar windshear-detection systems; these furnish pilots with data on the line-of-sight component of windshear threats over as much as 1-3 km, for a warning time of 15-45 sec. While the technology for a 10.6-micron, CO2 laser-based lidar is available, additional development is required for 2-micron, Ho:YAG laser-based systems.
Critical to the assessment of potential sites for the 1997 Pathfinder landing is estimation of general physical properties of the martian surface. Surface properties have been studied using a variety of spacecraft and earth-based remote sensing observations, plus in situ studies at the Viking lander sites. Because of their value in identifying landing hazards and defining scientific objectives, we focus this discussion on thermal inertia and rock abundance derived from middle-infrared (6 to 30 microns) observations. Used in conjunction with other datasets, particularly albedo and Viking orbiter images, thermal inertia and rock abundance provide clues about the properties of potential Mars landing sites.
Absorbing the electromagnetic radiation in several regions of the solar spectrum, CO2 plays an important role in the Earth radiation budget since it produces the greenhouse effect. Many natural processes in the Earth s system add and remove carbon dioxide. Overall, measurements of atmospheric carbon dioxide at different sites around the world show an increased carbon dioxide concentration in the atmosphere. At Mauna Loa Observatory (Hawaii) the measured carbon dioxide increased from 315 to 365 ppm, in the period 1958 2000 [Keeling et al., 2001]. While at the large scale, the relationship between CO2 increase and global warming is established [IPCC, 1996], at the local scale, many studies are still needed to understand regional and local sources of carbon dioxide, such as volcanoes. The volcanic areas are particularly rich in carbon dioxide; this is due to magma degassing in the summit craters region of active volcanoes, and to the presence of fractures and active faults [Giammanco et al., 1998]. Several studies estimate a global flux of volcanic CO2 (34+/-24)10(exp 6) tons/day from effusive volcanic emissions, such as the tropospheric volcanic plume (Table 1) [McClelland et al., 1989]. Plumes are a turbulent mixture of gases, solid particles and liquid droplets, emitted continuously at high temperature from summit craters, fumarolic fields or during eruptive episodes. Inside the plume, water vapour represents 70 90% of the volcanic gases. The main gaseous components are CO2, SO2, HCl, H2, H2S, HF, CO, N2 and CH4. Other plume components are volcanic ash, aqueous and acid droplets and solid sulphur-derived particles [Sparks et al., 1997]. Volcanic gases and aerosols are evidences of volcanic activity [Spinetti et al., 2003] and they have important climatic and environmental effects [Fiocco et al., 1994]. For example, Etna volcano is one of the world s major volcanic gas sources [Allard et al., 1991]. New studies on volcanic gaseous emissions have pointed out that a variation of the gas ratio CO2/SO2 is related to eruptive episodes [Caltabiano et al., 1994]. However, measurements and monitoring of volcanic carbon dioxide are difficult and often hazardous, due to the high background presence of atmospheric CO2 and the inaccessibility of volcanic sites. Hyperspectral remote sensing is a suitable technique to overcome the difficulties of ground measurement. It permits a rapid, comprehensive view of volcanic plumes and their evolution over time, detection of all gases with absorption molecular lines within the sensor s multispectral range and, in general, measurement of all the volatile components evolving from craters. The molecular and particle plume components scatter and absorb incident solar radiation. The integral of the radiation difference composes the signal measured by the remote spectrometer. The inversion technique consists of retrieving the plume component concentrations, hence decomposing the signal into the different contributions. The accuracy of remote sensing techniques depends primarily on the sensor capability and sensitivity.
Accurate estimates of snow water equivalent and other properties play an important role in weather, natural hazard, and hydrological forecasting and climate modeling over a range of scales in space and time. Remote sensing-derived estimates have traditionally been of the "snapshot" type, but techniques involving models with assimilation are also being explored. In both cases, forward emission models are useful to understand the observed passive microwave signatures and developing retrieval algorithms. However, mismatches between passive microwave sensor resolutions and the scales of processes controlling subpixel heterogeneity can affect the accuracy of the estimates. Improving the spatial resolution of new passive microwave satellite sensors is a major desire in order to (literally) resolve such subpixel heterogeneity, but limited spacecraft and mission resources impose severe constraints and tradeoffs. In order to maximize science return while mitigating risk for a satellite concept, it is essential to understand the scaling behavior of snow in terms of what the sensor sees (brightness temperature) as well as in terms of the actual variability of snow. NASA's Cold Land Processes Experiment-1 (CLPX-1: Colorado, 2002 and 2003) was designed to provide data to measure these scaling behaviors for varying snow conditions in areas with forested, alpine, and meadow/pasture land cover. We will use observations from CLPX-1 ground, airborne, and satellite passive microwave sensors to examine and evaluate the scaling behavior of observed and modeled brightness temperatures and observed and retrieved snow parameters across scales from meters to 10's of kilometers. The conclusions will provide direct examples of the appropriate spatial sampling scales of new sensors for snow remote sensing. The analyses will also illustrate the effects and spatial scales of the underlying phenomena (e.g., land cover) that control subpixel heterogeneity.
A Flash Lidar utilizing a novel Super-Resolution technique has been developed for providing Terrain Relative Navigation and Hazard Avoidance capabilities onboard landing vehicles.
A wireless sensor platform design and a single walled carbon nanotube/ionic liquid-based chemidosimeter system can incorporated into a highly sensitive and selective chemical hazard badge that can dosimetrically detect an analyte down to a sub parts-per-million concentration.
As the Autonomous Underwater Vehicle (AUV) and Autonomous Surface Vehicle (ASV) platforms mature in endurance and reliability, a natural evolution will occur towards longer, more remote autonomous missions. This evolution will require the development of key capabilities that allow these robotic systems to perform a high level of on-board decisionmaking, which would otherwise be performed by humanoperators. With more decision making capabilities, less a priori knowledge of the area of operations would be required, as these systems would be able to sense and adapt to changing environmental conditions, such as unknown topography, currents, obstructions, bays, harbors, islands, and river channels. Existing vehicle sensors would be dual-use; that is they would be utilized for the primary mission, which may be mapping or hydrographic reconnaissance; as well as for autonomous hazard avoidance, route planning, and bathymetric-based navigation. This paper describes a tightly integrated instantiation of an autonomous agent called CARACaS (Control Architecture for Robotic Agent Command and Sensing) developed at JPL (Jet Propulsion Laboratory) that was designed to address many of the issues for survivable ASV/AUV control and to provide adaptive mission capabilities. The results of some on-water tests with US Navy technology test platforms are also presented.
As part of its aircraft icing research program, the NASA Glenn Research Center is conducting a program to develop technologies for the remote sensing of atmospheric conditions. A suite of instruments, currently ground-based, are used to identify a region of supercooled liquid water which is labeled as hazardous if its liquid water content is sufficiently high. During the recently completed Alliance Icing Research Study (AIRS II), these instruments were deployed in conjunction with those of other U.S. and Canadian researchers at the Mirabel Airport near Montreal. As part of the study, balloonsondes were employed to provide in-situ measurement of the atmospheric conditions that were being concurrently remotely sensed. Balloonsonde launches occurred daily at 1200 GMT to provide AIRS forecasters with local data and additionally when research aircraft were present in the airspace. In this paper, we compare the processed data from the NASA remote sensing instruments, which included an X-band radar, lidar and two radiometers, to the data gathered from the 70 soundings conducted while the NASA instruments were active. Among the parameters compared are cloud upper and lower boundaries, temperature and humidity profiles and freezing levels.
The NASA Applied Sciences Program's public health initiative began in 2004 to illustratethe potential benefits for using remote sensing in public health applications. Objectives/Purpose: The CDC initiated a st udy with NASA through the National Center for Environmental Health (NCEH) to establish a pilot effort to use remote sensing data as part of its Environmental Public Health Tracking Network (EPHTN). As a consequence, the NCEH and NASA developed a project called HELIX-Atlanta (Health and Environment Linkage for Information Exchange) to demonstrate a process for developing a local environmental public health tracking and surveillance network that integrates non-infectious health and environment systems for the Atlanta metropolitan area. Methods: As an ongo ing, systematic integration, analysis and interpretation of data, an EPHTN focuses on: 1 -- environmental hazards; 2 -- human exposure to environmental hazards; and 3 -- health effects potentially related to exposure to environmental hazards. To satisfy the definition of a surveillance system the data must be disseminated to plan, implement, and evaluate environmental public health action. Results: A close working r elationship developed with NCEH where information was exchanged to assist in the development of an EPHTN that incorporated NASA remote sensing data into a surveillance network for disseminating public health tracking information to users. This project?s success provided NASA with the opportunity to work with other public health entities such as the University of Mississippi Medical Center, the University of New Mexico and the University of Arizona. Conclusions: HELIX-Atlanta became a functioning part of the national EPHTN for tracking environmental hazards and exposure, particularly as related to air quality over Atlanta. Learning Objectives: 1 -- remote sensing data can be integral to an EPHTN; 2 -- public tracking objectives can be enhanced through remote sensing data; 3 -- NASA's involvement in public health applications can have wider benefits in the future.
Near-surface seismic structure, particularly the shear wave velocity (V s ), can strongly affect local site response, and should be accurately estimated for ground motion prediction during seismic hazard assessment. The Imperial Valley (California), occupying the southern end of the Salton Trough, is a seismically active basin with thick surficial lacustrine sedimentary deposits. In this study, we utilize ambient noise records and local earthquake events for high-resolution near-surface characterization and site effect estimation with an unlit fiber-optic telecommunication infrastructure (dark fiber) in Imperial Valley by using the distributed acoustic sensing (DAS) technique. We apply ambient noise interferometry to retrieve coherent surface waves from DAS records, and evaluate performances of three different surface wave methods on DAS ambient noise dispersion imaging. We develop a quality control workflow to improve the dispersion measurement of noisy portions of the DAS data set by using a data selection strategy. Using the joint inversion of both the fundamental mode and higher overtones of Rayleigh waves, a high resolution two-dimensional (2D) V s structure down to 70 m depth is obtained. We successfully achieve an improved V s 30 (the time-averaged shear-wave velocity in the top 30 m) model with higher spatial-resolution and reliability compared to the existing community model for the area. We also explore the potential for utilizing DAS earthquake events for site amplification estimation. The preliminary results reveal a clear anti-correlation between the approximated site response and the V s 30 profile. In conclusion, our results indicate the potential utility of DAS deployed on dark fiber for near-surface characterization in appropriate contexts.
During and after the Persian Gulf war, hundreds of "oil lakes" were created in Kuwait by oil released from damaged wells. The lakes are a hazard to the Kuwait atmosphere, soil and ground water and must be carefully monitored. Boston University Center for Remote Sensing, assisted by other organizations, has accurately mapped the lakes using Landsat and Spot imagery. The war damage included the formation of over 300 oil lakes, oil pollution and sand dune movement. Total damage area is over 5,400 square kilometers - 30 percent of Kuwait's total surface area.
Accurate knowledge of soil moisture at the continental scale is important for improving predictions of weather, agricultural productivity and natural hazards, but observations of soil moisture at such scales are limited to indirect measurements, either obtained through satellite remote sensing or from meteorological networks. Land surface models simulate soil moisture processes, using observation-based meteorological forcing data, and auxiliary information about soil, terrain and vegetation characteristics. Enhanced estimates of soil moisture and other land surface variables, along with their uncertainty, can be obtained by assimilating observations of soil moisture into land surface models. These assimilation results are of direct relevance for the initialization of hydro-meteorological ensemble forecasting systems. The success of the assimilation depends on the choice of the assimilation technique, the nature of the model and the assimilated observations, and, most importantly, the characterization of model and observation error. Systematic differences between satellite-based microwave observations or satellite-retrieved soil moisture and their simulated counterparts require special attention. Other challenges include inferring root-zone soil moisture information from observations that pertain to a shallow surface soil layer, propagating information to unobserved areas and downscaling of coarse information to finer-scale soil moisture estimates. This chapter summarizes state-of-the-art solutions to these issues with conceptual data assimilation examples, using techniques ranging from simplified optimal interpolation to spatial ensemble Kalman filtering. In addition, operational soil moisture assimilation systems are discussed that support numerical weather prediction at ECMWF and provide value-added soil moisture products for the NASA Soil Moisture Active Passive mission.
Wildfires have a profound impact upon the biosphere and our society in general. They cause loss of life, destruction of personal property and natural resources and alter the chemistry of the atmosphere. In response to the concern over the consequences of wildland fire and to support the fire management community, the National Oceanic and Atmospheric Administration (NOAA), National Environmental Satellite, Data and Information Service (NESDIS) located in Camp Springs, Maryland gradually developed an operational system to routinely monitor wildland fire by satellite observations. The Hazard Mapping System, as it is known today, allows a team of trained fire analysts to examine and integrate, on a daily basis, remote sensing data from Geostationary Operational Environmental Satellite (GOES), Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensors and generate a 24 hour fire product for the conterminous United States. Although assisted by automated fire detection algorithms, N O M has not been able to eliminate the human element from their fire detection procedures. As a consequence, the manually intensive effort has prevented NOAA from transitioning to a global fire product as urged particularly by climate modelers. NASA at Goddard Space Flight Center in Greenbelt, Maryland is helping N O M more fully automate the Hazard Mapping System by training neural networks to mimic the decision-making process of the frre analyst team as well as the automated algorithms.
A second generation, compact, real-time, air-cooled 3-D imaging Flash Lidar sensor system, developed from a number of cutting-edge components from industry and NASA, is lab characterized and helicopter flight tested under the Autonomous Precision Landing and Hazard Detection and Avoidance Technology (ALHAT) project. The ALHAT project is seeking to develop a guidance, navigation, and control (GN&C) and sensing system based on lidar technology capable of enabling safe, precise crewed or robotic landings in challenging terrain on planetary bodies under any ambient lighting conditions. The Flash Lidar incorporates a 3-D imaging video camera based on Indium-Gallium-Arsenide Avalanche Photo Diode and novel micro-electronic technology for a 128 x 128 pixel array operating at a video rate of 20 Hz, a high pulse-energy 1.06 μm Neodymium-doped: Yttrium Aluminum Garnet (Nd:YAG) laser, a remote laser safety termination system, high performance transmitter and receiver optics with one and five degrees field-of-view (FOV), enhanced onboard thermal control, as well as a compact and self-contained suite of support electronics housed in a single box and built around a PC-104 architecture to enable autonomous operations. The Flash Lidar was developed and then characterized at two NASA-Langley Research Center (LaRC) outdoor laser test range facilities both statically and dynamically, integrated with other ALHAT GN&C subsystems from partner organizations, and installed onto a Bell UH-1H Iroquois "Huey" helicopter at LaRC. The integrated system was flight tested at the NASA-Kennedy Space Center (KSC) on simulated lunar approach to a custom hazard field consisting of rocks, craters, hazardous slopes, and safe-sites near the Shuttle Landing Facility runway starting at slant ranges of 750 m. In order to evaluate different methods of achieving hazard detection, the lidar, in conjunction with the ALHAT hazard detection and GN&C system, operates in both a narrow 1deg FOV raster-scanning mode in which successive, gimbaled images of the hazard field are mosaicked together as well as in a wider, 4.85deg FOV staring mode in which digital magnification, via a novel 3-D superresolution technique, is used to effectively achieve the same spatial precision attained with the more narrow FOV optics. The lidar generates calibrated and corrected 3-D range images of the hazard field in real-time and passes them to the ALHAT Hazard Detection System (HDS) which stitches the images together to generate on-the-fly Digital Elevation Maps (DEM's) and identifies hazards and safe-landing sites which the ALHAT GN&C system can then use to guide the host vehicle to a safe landing on the selected site. Results indicate that, for the KSC hazard field, the lidar operational range extends from 100m to 1.35 km for a 30 degree line-of-sight angle and a range precision as low as 8 cm which permits hazards as small as 25 cm to be identified. Based on the Flash Lidar images, the HDS correctly found and reported safe sites in near-real-time during several of the flights. A follow-on field test, planned for 2013, seeks to complete the closing of the GN&C loop for fully-autonomous operations on-board the Morpheus robotic, rocket-powered, free-flyer test bed in which the ALHAT system would scan the KSC hazard field (which was vetted during the present testing) and command the vehicle to landing on one of the selected safe sites.
Passive ambient noise monitoring is an emerging tool in environmental seismology, leveraging the ambient seismic field to assess temporal variations in shallow subsurface properties. This review focuses on the potential and challenges of using scattered coda waves from noise correlation functions to monitor critical zone dynamics. The sensitivity of seismic velocities to various environmental factors, including precipitation, snowmelt, atmospheric pressure, and groundwater fluctuations, underscores the method’s versatility. While coda waves excel in detecting subtle changes due to their scattered nature, ballistic waves provide higher spatial resolution, albeit with challenges in source stability. Advances in seismic sensing, including distributed acoustic sensing and low-cost geophone networks, have enabled high-resolution monitoring of hydrological processes, subsurface deformation, and seismic hazards. Integrating seismic data with hydrological models provides insights into water storage, pore pressure changes, and soil moisture dynamics. However, limitations in spatial resolution, calibration with ground truth data, and coupled effects between environmental factors remain key challenges. This review emphasizes the importance of interdisciplinary approaches in refining methodologies, enhancing sensor deployments, and addressing data gaps. Passive seismic monitoring offers opportunities to understand critical zone processes and their broader impacts on seismic hazards and environmental sustainability.
The methods of measuring the existence of erosion and the effects of sand stabilization control systems are described. The mechanics of sand movement, the nature of sand erosion, and the use of satellite data to measure these factors and their surrogates are discussed using the locational and control aspects of aeolian and litoral erosion zones along the sand beach of the Mississippi coast. The aeolian erosion is highlighted due to the redeposition of the sand which causes high cleanup costs, property damage, and safety and health hazards. The areas of differential erosion and the patterns of beach sand movement are illustrated and the use of remote sensing methods to identify the areas of erosion are evaluated.
The wearable environmental and physiological sensing unit (WEPS) is a prototype of systems to be worn by emergency workers (e.g., firefighters and members of hazardous-material response teams) to increase their level of safety. The WEPS includes sensors that measure a few key physiological and environmental parameters, a microcontroller unit that processes the digitized outputs of the sensors, and a radio transmitter that sends the processed sensor signals to a computer in a mobile command center for monitoring by a supervisor. The monitored parameters serve as real-time indications of the wearer s physical condition and level of activity, and of the degree and type of danger posed by the wearer s environment. The supervisor could use these indications to determine, for example, whether the wearer should withdraw in the face of an increasing hazard or whether the wearer should be rescued.