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Every day, emergency responders are confronted with worldwide natural and manmade disasters, including earthquakes, floods, hurricanes, landslides, tsunami, volcanoes, wildfires, terrorist attacks, and accidental oil spills.The U.S. Geological Survey (USGS) is ready to coordinate the provisioning and deployment of USGS staff, equipment, geospatial data, products, and services in support of national emergency response requirements.
The mission of the U.S. Geological Survey (USGS) Earthquake Science Center is to collect a wide range of data on earthquakes, faults, and crustal deformation; conduct research to increase our understanding of earthquake source processes, occurrence, and effects; and synthesize this knowledge into probabilistic seismic hazard assessments, aftershock forecasts, and ground-shaking scenarios for anticipated major earthquakes. We disseminate these data products, hazard assessments, and research discoveries to scientists, engineers, emergency managers, and the public. With university and State partners, we operate the California Integrated Seismic Network and the Pacific Northwest Seismic Network, as well as geodetic networks throughout the western United States. We also lead the National Strong Motion Project and the ShakeAlert earthquake early warning (EEW) system; house renowned rock mechanics laboratories and deep borehole geophysics facilities; and conduct extensive geophysical, geologic, and paleoseismic investigations along active faults. We are funded primarily by the USGS Earthquake Hazards Program, with additional support from the USGS Volcano Hazards and Energy Resources Programs, other Federal and State agencies, private foundations, and public and private utilities and corporations.
Technical outreach — distinct from general-interest and K-12 educational outreach — for volcanic hazards is aimed at providing usable scientific information about potential or ongoing volcanic activity to public officials, businesses, and individuals in support of their response, preparedness, and mitigation efforts. Within the context of a National Volcano Early Warning System (NVEWS) (Ewert et al., 2005), technical outreach is a critical process, transferring the benefits of enhanced monitoring and hazards research to key constituents who have to initiate actions or make policy decisions to lessen the hazardous impact of volcanic activity. This report discusses recommendations of the Technical-Information Products Working Group convened in 2006 as part of the NVEWS planning process. The basic charge to the Working Group was to identify a web-based, volcanological "product line" for NVEWS to meet the specific hazard-information needs of technical users. Members of the Working Group were: Marianne Guffanti (Chair), USGS, Reston VA Steve Brantley, USGS, Hawaiian Volcano Observatory HI Peter Cervelli, USGS, Alaska Volcano Observatory, Anchorage AK Chris Nye, Division of Geological and Geophysical Surveys and Alaska Volcano Observatory, Fairbanks AK George Serafino, National Oceanic and Atmospheric Administration, Camp Springs MD Lee Siebert, Smithsonian Institution, Washington DC Dina Venezky, USGS, Volcano Hazards Team, Menlo Park CA Lisa Wald, USGS, Earthquake Hazards Program, Golden CO
The potential for damaging earthquakes, landslides, floods, tsunamis, and wildfires is widely recognized in California. The same cannot be said for volcanic eruptions, despite the fact that they occur in the state about as frequently as the largest earthquakes on the San Andreas Fault. At least ten eruptions have taken place in the past 1,000 years, and future volcanic eruptions are inevitable. The U.S. Geological Survey’s (USGS) national volcanic threat assessment identifies eight young volcanic areas in California as moderate, high, or very high threat. Of the eight volcanic areas that exist in California, molten rock resides beneath at least seven of these—Medicine Lake volcano, Mount Shasta, Lassen Volcanic Center, Clear Lake volcanic field, the Long Valley volcanic region, Coso volcanic field, and Salton Buttes—and are therefore considered “active” volcanoes producing volcanic earthquakes, toxic gas emissions, hot springs, geothermal systems, and (or) ground movement. The USGS California Volcano Observatory in Menlo Park, California, monitors these potentially hazardous volcanoes to help communities and government authorities understand, prepare for, and respond to volcanic activity. Although volcanic activity can sometimes be forecast, eruptions, like earthquakes or tsunamis, cannot be prevented. Understanding the hazards and identifying what and who is in harm’s way is the first step in mitigating volcanic risk and building community resilience to volcanic hazards. This report, which was prepared in collaboration with the California Governor’s Office of Emergency Services and the California Geological Survey, provides a broad perspective on the state’s exposure to volcanic hazards by integrating volcanic hazard information with geospatial data on at-risk populations, infrastructure, and resources. This information is intended to prompt site- and sector-specific vulnerability analyses and preparation of hazard mitigation and response plans.
This is a collection of videos of unscripted interviews with Jake Lowenstern, who is the Scientist in Charge of the Yellowstone Volcano Observatory (YVO). YVO was created as a partnership among the U.S. Geological Survey (USGS), Yellowstone National Park, and University of Utah to strengthen the long-term monitoring of volcanic and earthquake unrest in the Yellowstone National Park region. Yellowstone is the site of the largest and most diverse collection of natural thermal features in the world and the first National Park. YVO is one of the five USGS Volcano Observatories that monitor volcanoes within the United States for science and public safety. These video presentations give insights about many topics of interest about this area. Title: Yes! Yellowstone is a Volcano An unscripted interview, January 2009, 7:00 Minutes Description: USGS Scientist-in-Charge of Yellowstone Volcano Observatory, Jake Lowenstern, answers the following questions to explain volcanic features at Yellowstone: 'How do we know Yellowstone is a volcano?', 'What is a Supervolcano?', 'What is a Caldera?','Why are there geysers at Yellowstone?', and 'What are the other geologic hazards in Yellowstone?' Title: Yellowstone Volcano Observatory An unscripted interview, January 2009, 7:15 Minutes Description: USGS Scientist-in-Charge of Yellowstone Volcano Observatory, Jake Lowenstern, answers the following questions about the Yellowstone Volcano Observatory: 'What is YVO?', 'How do you monitor volcanic activity at Yellowstone?', 'How are satellites used to study deformation?', 'Do you monitor geysers or any other aspect of the Park?', 'Are earthquakes and ground deformation common at Yellowstone?', 'Why is YVO a relatively small group?', and 'Where can I get more information?' Title: Yellowstone Eruptions An unscripted interview, January 2009, 6.45 Minutes Description: USGS Scientist-in-Charge of Yellowstone Volcano Observatory, Jake Lowenstern, answers the following questions to explain volcanic eruptions at Yellowstone: When was the last supereruption at Yellowstone?', 'Have any eruptions occurred since the last supereruption?', 'Is Yellowstone overdue for an eruption?', 'What does the magma below indicate about a possible eruption?', 'What else is possible?', and 'Why didn't you think the Yellowstone Lake earthquake swarm would lead to an eruption?'
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El McVCO es un generador de frecuencias basado en un microcontrolador que reemplaza al oscilador controlado por voltaje (VCO) utilizado en telemetría analógica de datos sísmicas. Acepta señales de baja potencia desde un sismómetro y produce una señal subportadora modulada en frecuencia adecuada para enlaces telefónicos o vía radio a un lugar remoto de recolección de datos. La frecuencia de la subportadora y la ganancia pueden ser seleccionadas mediante un interruptor. Tiene la opción de poder operar con dos canales para la observación con ganancia alta y baja. El McVCO fue diseñado con el propósito de mejorar la telemetría analógica de las señales dentro de la Pacific Northwest Seismograph Network (PNSN) (Red Sismográfica del Noroeste del Pacífico). Su desarrollo recibió el respaldo del Programa de Geofísica de la Universidad de Washington y del "Volcano Hazards and Earthquake Hazards programs of the United States Geological Survey (USGS) (Programa de Investigaciones de Riesgos Volcánicos y Programa de Investigaciones de Riesgos Sísmicos de los EEUU). Cientos de instrumentos se han construido e instalado. Además de utilizarlo el PNSN, el McVCO es usado por el Observatorio Vulcanológico de Alaska para monitorear los volcanes aleutianos y por el USGS Volcano Disaster Assistance Program (Programa de Ayuda en las Catástrofes Volcánicas del USGS) para responder a crisis volcánicas en otros países. Este manual cubre el funcionamiento del McVCO, es una referencia técnica para aquellos que necesitan saber con más detalle cómo funciona el McVCO, y cubre una serie de temas que requieren un trato explícito o que derivan del despliegue del instrumento.
Near‐field recordings of large earthquakes and volcano‐induced events using traditional seismological instrumentation often suffer from unaccounted effects of local tilt and saturation of signals. Recent hardware advances have led to the development of the blueSeis‐3A, a very broadband, highly sensitive rotational motion sensor. We installed this sensor in close proximity to permanently deployed classical instrumentation (i.e., translational seismometer, accelerometer, and tiltmeter) at the Hawaiian Volcano Observatory (USGS). There, we were able to record three ~Mw 5 earthquakes associated with large collapse events during the later phase of the 2018 Kīlauea summit eruption. Located less than 2 km from the origins of these sources, the combined six‐axis translational and rotational measurements revealed clear static rotations around all three coordinate axes. With these six component recordings, we have been able to reconstruct the complete time history of ground motion of a fixed point during an earthquake for the first time.
McVCO is a microcontroller-based frequency generator that replaces the voltage controlled oscillator (VCO) used in the analog telemetry of seismic data. It accepts low-level signals from a seismometer and produces a frequency modulated subcarrier suitable for radio or telephone links to a data collection site. McVCO was designed for the purpose of improving the analog telemetry of signals within the Pacific Northwest Seismograph Network (PNSN). Its development received support from the University of Washington Geophysics Program, and both the Volcano Hazards and Earthquake Hazards programs of the United States Geological Survey (USGS). This handbook covers operation of McVCO, provides a technical reference for those who require a closer look at how McVCO works, and covers a collection of topics that need explicit treatment or that spring from deployment of the instrument.
From the earliest times, people have been terrified yet fascinated by the workings of the Earth. Indeed records of earthquakes have been kept in China for over 3000 years and for 1500 years in Japan. because of the interior of the Earth is inaccessible, nothing about it could be known with any certainty. For thousands of years, thinkers and writers could base their conclusions on a limited number of observations, some of which were as follows; the Earth was not stable and sometimes shook violently; the earthquakes produced were more frequent in some localities than in others; they were sometimes accompanied by heavy rumblings, fissures in the ground, changes in the level of the land, and tidal waves. Oftentimes earthquakes were associated with volcanoes or "burning mountains."
The effects of earthquake shaking on the population and infrastructure across the State of Hawaii could be catastrophic, and the high seismic hazard in the region emphasizes the likelihood of such an event. Earthquake early warning (EEW) has the potential to give several seconds of warning before strong shaking starts, and thus reduce loss of life and damage to property. The two approaches to EEW are (1) a network approach (such as ShakeAlert or ElarmS) where the regional seismic network is used to detect the earthquake and distribute the alarm and (2) a local approach where a critical facility has a single seismometer (or small array) and a warning system on the premises. The network approach, also referred to here as ShakeAlert or ElarmS, uses the closest stations within a regional seismic network to detect and characterize an earthquake. Most parameters used for a network approach require observations on multiple stations (typically 3 or 4), which slows down the alarm time slightly, but the alarms are generally more reliable than with single-station EEW approaches. The network approach also benefits from having stations closer to the source of any potentially damaging earthquake, so that alarms can be sent ahead to anyone who subscribes to receive the notification. Thus, a fully implemented ShakeAlert system can provide seconds of warning for both critical facilities and general populations ahead of damaging earthquake shaking. The cost to implement and maintain a fully operational ShakeAlert system is high compared to a local approach or single-station solution, but the benefits of a ShakeAlert system would be felt statewide—the warning times for strong shaking are potentially longer for most sources at most locations. The local approach, referred to herein as “single station,” uses measurements from a single seismometer to assess whether strong earthquake shaking can be expected. Because of the reliance on a single station, false alarms are more common than when using a regional network of seismometers. Given the current network, a single-station approach provides more warning for damaging earthquakes that occur close to the station, but it would have limited benefit compared to a fully implemented ShakeAlert system. For Honolulu, for example, the single-station approach provides an advantage over ShakeAlert only for earthquakes that occur in a narrow zone extending northeast and southwest of O‘ahu. Instrumentation and alarms associated with the single-station approach are typically maintained and assessed within the target facility, and thus no outside connectivity is required. A single-station approach, then, is unlikely to help broader populations beyond the individuals at the target facility, but they have the benefit of being commercially available for relatively little cost. The USGS Hawaiian Volcano Observatory (HVO) is the Advanced National Seismic System (ANSS) regional seismic network responsible for locating and characterizing earthquakes across the State of Hawaii. During 2014 and 2015, HVO tested a network-based EEW algorithm within the current seismic network in order to assess the suitability for building a full EEW system. Using the current seismic instrumentation and processing setup at HVO, it is possible for a network approach to release an alarm a little more than 3 seconds after the earthquake is recorded on the fourth seismometer. Presently, earthquakes having M≥3 detected with the ElarmS algorithm have an average location error of approximately 4.5 km and an average magnitude error of -0.3 compared to the reviewed catalog locations from the HVO. Additional stations and upgrades to existing seismic stations would serve to improve solution precision and warning times and additional staffing would be required to provide support for a robust, network-based EEW system. For a critical facility on the Island of Hawaiʻi, such as the telescopes atop Mauna Kea, one phased approach to mitigate losses could be to immediately install a single station system to establish some level of warning. Subsequently, supporting the implementation of a full network-based EEW system on the Island of Hawaiʻi would provide additional benefit in the form of improved warning times once the system is fully installed and operational, which may take several years. Distributed populations across the Hawaiian Islands, including those outside the major cities and far from the likely earthquake source areas, would likely only benefit from a network approach such as ShakeAlert to provide warnings of strong shaking.
This U.S. Geological Survey (USGS), Hawaiian Volcano Observatory (HVO) summary presents seismic data gathered during January–March 2009. The seismic summary offers earthquake hypocenters without interpretation as a source of preliminary data and is complete in that most data for events of M≥1.5 are included. All latitude and longitude references in this report are stated in Old Hawaiian Datum. The HVO summaries have been published in various forms since 1956. Summaries prior to 1974 were issued quarterly, but cost, convenience of preparation and distribution, and the large quantities of data necessitated an annual publication, beginning with Summary 74 for the year 1974. Since 2004, summaries have been identified simply by year, rather than by summary number. Summaries originally issued as administrative reports were republished in 2007 as Open-File Reports. All the summaries since 1956 are available at http://pubs.usgs.gov/of/2007/1316-1345/ (last accessed 02/24/2010). In January 1986, HVO adopted CUSP ( C alifornia Institute of Technology U SGS S eismic P rocessing). Summary 86, available at http://pubs.er.usgs.gov/usgspubs/ofr/ofr92301 (last accessed 02/24/2010), includes a description of the seismic instrumentation, calibration, and processing used in recent years. The present summary includes background information about the seismic network to provide the end user with an understanding of the processing parameters and how the data were gathered. Earthworm software, documentation available at http://folkworm.ceri.memphis.edu/ew-doc/ (last accessed 02/24/2010), was first installed at HVO in 1999 as part of an upgrade to tsunami warning capabilities in the Pacific region. This improved and expanded data exchange with the Pacific Tsunami Warning Center in Ewa Beach, Oahu, that included not only seismic waveforms, but also parametric earthquake data. Although Earthworm does included modules for earthquake triggering and earthquake location, this software was never used to generate catalog hypocenter locations at HVO. During 2009, HVO migrated from CUSP to seismic processing software developed by the C alifornia I ntegrated S eismic N etwork or CISN. This software is now referred to as AQMS, for A dvanced National Seismic System Q uake M anagement S ystem. Summary data for this year will be presented in two reports; the first report includes earthquakes processed on the CUSP platform for January–March; earthquakes for the last three quarters, processed on the AQMS platform, will be published in a separate summary with a description of AQMS production parameters. A report by Klein and Koyanagi (USGS Open-File Report 80-302, 1980) tabulates instrumentation, calibration, and recording history of each seismic station in the network. It is designed as a reference for users of seismograms and phase data and includes and augments the information in the station table in this summary. Figures 11–14 are maps showing computer-located hypocenters. The maps were generated using the G eneric M apping T ools (GMT), found at http://gmt.soest.hawaii.edu/ (last accessed 01/22/2010), in place of traditional QPLOT maps.
For the past decade, the USGS has been monitoring deformation at various locations in the western United States using continuous GPS. The main focus of these measurements are estimates of displacement averaged over one day. Essentially, these consist of recording at 30 seconds intervals the carrier-frequency phase-data (equivalent to travel-time) between a GPS receiver and the GPS satellite network. In turn, these observations, which are converted to pseudo—ranges, are processed using one of the “research grade” programs (GIPSY, Zumberge et al., or GAMIT, wwwgpsg.mit.edu/~simon/gtgk) to estimate the position of the GPS receiver averaged over 24 hours. However, it is possible and desirable to estimate the position of the receiver (actually the antenna) more frequently and to do this within a few seconds of the time actual measurement (known as real-time). A recent example, the 2004 Magnitude 6, Parkfield, California earthquake, demonstrated that having GPS estimates of position more frequently than simply a daily average is required if one requires discrimination between co-seismic and post-seismic deformation (Langbein et al., 2006). The high-rate estimates of position obtained at Parkfield show that post-seismic deformation started less than one-hour after the mainshock and that this deformation was roughly the same magnitude as the co-seismic deformation. The high-rate solutions for Parkfield were done by others including Yehuda Bock at UCSD and Kristine Larson at U. of Colorado, but not the USGS. The Parkfield experience points out the need for an in-house capability by the USGS to be able to accurately measure co-seismic displacements and other rapid, deformation signals using GPS. This applies to both the Earthquake and Volcano Hazard programs. Although at many locations where we monitor deformation, we have strainmeters and tiltmeters in addition to GPS which, in principle, are far more sensitive to rapid deformation over periods of less than a day (Langbein and Bock, 2004). But, not all locales include strain and tiltmeters. Thus, having the capability to extract signals with periods of less than a day is desirable since the distribution of GPS is more extensive than strain and tilt. At both Parkfield and Long Valley, the USGS has been using other software packages to process the GPS data at sub-daily intervals and in real-time. The underlying goal of these types of measurements is to detect any deformation event as it evolves; the 24 hour processing might not provide timely results if such a deformation event is precursory to a geologic hazard (an earthquake for Parkfield and either a volcanic event or an earthquake for Long Valley). In Long Valley, We use the software package called 3DTracker (http://www.3dtracker.com, http://www.condorearth.com) to estimate the changes of in position of a remote site relative to a “fixed” site. The 3DTracker software uses double difference GPS code measurements and receiversatellite-time triple differences from one epoch to the next of the GPS phase data (a proxy for travel-time measurements) and employs a Kalman filter to obtain stability in the estimate of position. That is, the estimate of the current position depends upon the estimate of the prior position. Hence, a time series of position looks fairly smooth depending upon the coefficient selected for the Kalman filter. With triple differences, the sometimes troublesome initial integer cycle ambiguity terms cancel (number of wavelengths between the receiver and each satellite), but only the incremental change in position is calculated. This triple difference Kalman filter solution is slow to converge and less accurate than a double difference (e.g., RTD, Track) solution, but it is robust and computationally efficient (Remondi and Brown, 2000). 3D-Tracker allows use of various single-frequency and dual-frequency GPS phase and code observables including the ionospheric-free combinations (known as LC or L3 and P(L3)) formed from an linear combination of the L1 and L2 carrier phase and code data. The lowest noise observable is the L1 carrier, but it is biased by ionospheric refraction that has amplitudes of about 1 to 10 ppm. This results in a systematic scale error in the relative positions. The L3 phase noise is about 3 times greater than the L1 phase noise, but it is generally used to solve for all but the shortest baselines (< 5 km). In addition, the software does output the position changes is a standard format that can be used for other analysis. At Parkfield, we use the software package called RTD (http://www.geodetics.com). The RTD software has been described in the literature (Bock et al., 2000) but basically, it estimates the position without the constraint of a Kalman filter. It uses double differences (in our studies the LC or ionospheric free observable is used) and the integer ambiguities are resolved independently for each 1-second measurement; Most GPS software that use double-differences require several epochs of measurements to resolve the integer ambiguities. The data files use a proprietary format and can not be read by me or others; rather, Yehuda Bock at UCSD (and author of RTD) translates these files into a standard format that can be read by me. Recently, Tom Herring of MIT has modified the GAMIT software to process kinematically GPS data (www-gpsg.mit.edu/~simon/gtgk/tutorial/Lecture_13.pdf). At this time, the software, known as TRACK, does not process the observations in real-time. Consequently, the latency between the time of the observation and the time when a position estimate is available depends upon the frequency that the data are downloaded and the speed of actually processing the observations; there could be a delay of an hour or two before the a position estimates are available. Unlike RTD and 3DTracker, TRACK comes with GAMIT (which is distributed freely) and is currently operating in a test mode at the USGS office in Pasadena. The LC or ionosphere free observable is used in our TRACK solutions. JPL has a version of their GIPSY software called “Real-time GIPSY (RTG)” (gipsy.jpl.nasa.gov/orms/rtg), which, like TRACK, can process the pseudo-range data “off—line”. However, this software is not freely distributed. Instead, at least one company, NAVCOM, has teamed with JPL to integrate RTG with GPS receivers and telemetry that yields positions in realtime. Kristine Larson of University of Colorado has modified the original GIPSY to estimate positions kinematically. Again, like TRACK, the positions are estimated off—line. Much of her research is described in Larson et al. (2003), and Choi et al. (2004). For Long Valley, out of the 17 GPS sites, we monitor 5 baselines within the caldera at 5 second intervals relative to the Bald Mountain site at the edge of the caldera using 3DTracker. The baseline measurement using 3DTracker consists of determination of the 3 dimensional positions of the 5 remote points (GPS receivers) relative to a GPS site at Bald. A second, independent system collects and downloads once a day the 30-second data used for the 24-hour solutions for the 12 sites not monitored with 3DTracker. For the sites monitored with 3DTracker, the pseudo—range data are decimated to 30 seconds and converted to a form used for the 24-hour solutions. Both sets of telemetry employ 900 MHz spread spectrum radios which require line of site between all of the links. The telemetry for the 3DTracker sites require a dedicated radios at each end and intermediate repeaters as needed, while the telemetry required for the other sites use a single master radio, repeaters as needed, and a radio at each remote site. (The 5 sites being monitored with 3DTracker require 13 radios.) At Parkfield, RTD is used to measure the position changes all 12 baselines at 1 second intervals relative to a site, Pomm, adjacent to the San Andreas Fault. The complete RTD package (hardware and software) collects all of the data and determines the position of each site relative to Pomm. In addition, the system stores both the 1-second and 30-second pseudo-range data for later downloading which are ultimately used in the 24-hour solutions. To do this, each site has a 2.4 GHz radio and a telemetry buffer. The telemetry buffer holds 24-hours of data (in the event that the telemetry link is broken) and converts the RS232 data stream from the GPS receiver into a form compatible with an IP (Internet protocol) network connection. In contrast with the Long Valley system, the telemetry link for GPS at Parkfield consists of a single radio at each remote sites and a single radio at the central site. Although position estimates are produced within 1-second of the observations, these results are not immediately available because there is no high speed Internet connection to Parkfield. Instead, the data are stored on a removable disk and sent to UCSD once per month. Below, I describe the results of a simple experiment to examine the response of some of these systems to simulated deformation that could be an analogue of a tectonic or volcanic event. In many engineering applications, the system response is tested by inputting a step to the system and measuring the output of the system. Essentially, this is what I've done. The experiment described below moves the GPS antenna from its original position to a new position within 1 second; the software tracks the translation. These measurements were conducted in August 2004 with the RTD software at Parkfield, and twice in Long Valley. The first Long Valley test was conducted in September 2004 using 3DTracker on a single baseline. The test was repeated in September 2005 using 3DTracker on two baselines and, importantly, saving the RINEX files of the data so that the data could be replayed through 3DTracker using other options in the program and, using other software packages including TRACK. In addition, we observed a short-term event at the Three Sisters volcano in Oregon. This event was snow melt at a remote GPS site which gave an apparent 15 cm displacement in vertical in less than one-day. 3DTracker is used to monitor this site, and the event was captured with this software. In addition, with the assistance of others, I got additional estimates of position using other software packages; those results are presented. Finally, the precision of both 3DTracker and RTD are compared using a power spectrum. Those results would suggest that 3DTracker using appropriate Kalman filter coefficients would have better precision than RTD; instead, the lower noise level from 3DTracker is a result of smoothing from the Kalman filter. Given the results described in this report, high-rate GPS is certainly capable of accurately measuring displacements of 1 centimeter with a high degree of statistical confidence. Plotting these results show that the time of the displacement can be visually determined to that of the sampling interval of the data. However, especially with small amplitude signals, any of the software packages can yield erroneous deformation “signals” that are either due excess travel-time of the GPS carrier frequency from multipath or a limitation in the software. Thus, the time series of displacements must be viewed with caution and knowledge of external circumstances that might cause a change in position. The casual reader should continue with the next section describing the methods then jump to the last two sections for the discussion and conclusions. I have made some recommendations there.
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In 2002, the U. S. Geological Survey (USGS) launched a program to enhance the acquisition, preservation, and use of remotely sensed data for USGS science programs, as well as for those of cooperators and customers. Remotely sensed data are fundamental tools for studying the Earth's land surface, including coastal and near-shore environments. For many decades, the USGS has been a leader in providing remotely sensed data to the national and international communities. Acting on its historical topographic mapping mission, the USGS has archived and distributed aerial photographs of the United States for more than half a century. Since 1972, the USGS has acquired, processed, archived, and distributed Landsat and other satellite and airborne remotely sensed data products to users worldwide. Today, the USGS operates and manages the Landsats 5 and 7 missions and cooperates with the National Aeronautics and Space Administration (NASA) to define and implement future satellite missions that will continue and expand the collection of moderate-resolution remotely sensed data. In addition to being a provider of remotely sensed data, the USGS is a user of these data and related remote sensing technology. These data are used in natural resource evaluations for energy and minerals, coastal environmental surveys, assessments of natural hazards (earthquakes, volcanoes, and landslides), biological surveys and investigations, water resources status and trends analyses and studies, and geographic and cartographic applications, such as wildfire detection and tracking and as a source of information for The National Map. The program furthers these distinct but related roles by leading the USGS activities in providing remotely sensed data while advancing applications of such data for USGS programs and a wider user community.