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The Alaska earthquake, March 27, 1964: Lessons and conclusions

One of the greatest earthquakes of all time struck south-central Alaska on March 27, 1964. Strong motion lasted longer than for most recorded earthquakes, and more land surface was dislocated, vertically and horizontally, than by any known previous temblor. Never before were so many effects on earth processes and on the works of man available for study by scientists and engineers over so great an area. The seismic vibrations, which directly or indirectly caused most of the damage, were but surface manifestations of a great geologic event-the dislocation of a huge segment of the crust along a deeply buried fault whose nature and even exact location are still subjects for speculation. Not only was the land surface tilted by the great tectonic event beneath it, with resultant seismic sea waves that traversed the entire Pacific, but an enormous mass of land and sea floor moved several tens of feet horizontally toward the Gulf of Alaska. Downslope mass movements of rock, earth, and snow were initiated. Subaqueous slides along lake shores and seacoasts, near-horizontal movements of mobilized soil (“landspreading”), and giant translatory slides in sensitive clay did the most damage and provided the most new knowledge as to the origin, mechanics, and possible means of control or avoidance of such movements. The slopes of most of the deltas that slid in 1964, and that produced destructive local waves, are still as steep or steeper than they were before the earthquake and hence would be unstable or metastable in the event of another great earthquake. Rockslide avalanches provided new evidence that such masses may travel on cushions of compressed air, but a widely held theory that glaciers surge after an earthquake has not been substantiated. Innumerable ground fissures, many of them marked by copious emissions of water, caused much damage in towns and along transportation routes. Vibration also consolidated loose granular materials. In some coastal areas, local subsidence was superimposed on regional tectonic subsidence to heighten the flooding damage. Ground and surface waters were measurably affected by the earthquake, not only in Alaska but throughout the world. Expectably, local geologic conditions largely controlled the extent of structural damage, whether caused directly by seismic vibrations or by secondary effects such as those just described. Intensity was greatest in areas underlain by thick saturated unconsolidated deposits, least on indurated bedrock or permanently frozen ground, and intermediate on coarse well-drained gravel, on morainal deposits, or on moderately indurated sedimentary rocks. Local and even regional geology also controlled the distribution and extent of the earthquake's effects on hydrologic systems. In the conterminous United States, for example, seiches in wells and bodies of surface water were controlled by geologic structures of regional dimension. Devastating as the earthquake was, it had many long-term beneficial effects. Many of these were socioeconomic or engineering in nature; others were of scientific value. Much new and corroborative basic geologic and hydrologic information was accumulated in the course of the earthquake studies, and many new or improved investigative techniques were developed. Chief among these, perhaps, were the recognition that lakes can be used as giant tiltmeters, the refinement of methods for measuring land-level changes by observing displacements of barnacles and other sessile organisms, and the relating of hydrology to seismology by worldwide study of hydroseisms in surface-water bodies and in wells. The geologic and hydrologic lessons learned from studies of the Alaska earthquake also lead directly to better definition of the research needed to further our understanding of earthquakes and of how to avoid or lessen the effects of future ones. Research is needed on the origins and mechanisms of earthquakes, on crustal structure, and on the generation of tsunamis and local waves. Better earthquake-hazard maps, based on improved knowledge of regional geology, fault behavior, and earthquake mechanisms, are needed for the entire country. Their preparation will require the close collaboration of engineers, seismologists, and geologists. Geologic maps of all inhabited places in earthquake-prone parts of the country are also needed by city planners and others, because the direct relationship between local geology and potential earthquake damage is now well understood. Improved and enlarged nets of earthquake-sensing instruments, sited in relation to known geology, are needed, as are many more geodetic and hydrographic measurements. Every large earthquake, wherever located, should be regarded as a full-scale laboratory experiment whose study can give scientific and engineering information unobtainable from any other source. Plans must be made before the event to insure staffing, funding, and coordination of effort for the scientific and engineering study of future earthquakes. Advice of earth scientists and engineers should be used in the decision-making processes involved in reconstruction after any future disastrous earthquake, as was done after the Alaska earthquake. The volume closes with a selected bibliography and a comprehensive index to the entire series of U.S. Geological Survey Professional Papers 541-546. This is the last in a series of six reports that the U.S. Geological Survey published on the results of a comprehensive geologic study that began, as a reconnaissance survey, within 24 hours after the March 27, 1964, Magnitude 9.2 Great Alaska Earthquake and extended, as detailed investigations, through several field seasons. The 1964 Great Alaska earthquake was the largest earthquake in the U.S. since 1700. Professional Paper 546, in 1 part, describes Lessons and Conclusions.

Alaska↗

National wildlife refuge visitor survey 2012--Individual refuge results

The National Wildlife Refuge System (Refuge System), established in 1903 and managed by the U.S. Fish and Wildlife Service (Service), is the leading network of protected lands and waters in the world dedicated to the conservation of fish, wildlife and their habitats. There are 560 national wildlife refuges and 38 wetland management districts nationwide, encompassing more than 150 million acres. The Refuge System attracts nearly 45 million visitors annually, including 34.8 million people who observe and photograph wildlife, 9.6 million who hunt and fish, and nearly 675,000 teachers and students who use refuges as outdoor classrooms. Understanding visitor perceptions of refuges and characterizing their experiences on refuges are critical elements of managing these lands and meeting the goals of the Refuge System. The Service collaborated with the U.S. Geological Survey to conduct a national survey of visitors regarding their experiences on national wildlife refuges. The purpose of the survey was to better understand visitor experiences and trip characteristics, to gauge visitors’ levels of satisfaction with existing recreational opportunities, and to garner feedback to inform the design of programs and facilities. The survey results will inform performance, planning, budget, and communications goals. Results will also inform Comprehensive Conservation Plans (CCPs), visitor services, and transportation planning processes. This Data Series consists of 25 separate data files. Each file describes the results of the survey for an individual refuge and contains the following information: • Introduction: An overview of the Refuge System and the goals of the national surveying effort. • Methods: The procedures for the national surveying effort, including selecting refuges, developing the survey instrument, contacting visitors, and guidance for interpreting the results.• Refuge Description: A brief description of the refuge location, acreage, purpose, recreational activities, and visitation statistics, including a map (where available) and refuge website link. • Sampling at This Refuge: The sampling periods, locations, and response rate for the refuge. • Selected Survey Results: Key findings for the refuge, including: o Visitor and trip characteristics o Visitor spending in the local communities o Visitors opinions about the refuge o Visitor opinions about National Wildlife Refuge System topics • Conclusion • References Cited • Survey Frequencies (Appendix A): The survey instrument with frequency results for the refuge. • Visitor Comments (Appendix B): The verbatim responses to the open-ended survey questions for the refuge.Individual-refuge results for the 53 participating refuges in the 2010-2011 national effort are available at http://pubs.usgs.gov/ds/643/ as part of USGS Data Series 643. Combined results for the 53 participating refuges in the 2010-2011 national effort are available at http://pubs.usgs.gov/ds/685/ as part of USGS Data Series 685.

Data Series↗

Combined effects of tectonic and landslide-generated Tsunami Runup at Seward, Alaska during the Mw 9.2 1964 earthquake

We apply a recently developed and validated numerical model of tsunami propagation and runup to study the inundation of Resurrection Bay and the town of Seward by the 1964 Alaska tsunami. Seward was hit by both tectonic and landslide-generated tsunami waves during the M W "> M W MW 9.2 1964 megathrust earthquake. The earthquake triggered a series of submarine mass failures around the fjord, which resulted in landsliding of part of the coastline into the water, along with the loss of the port facilities. These submarine mass failures generated local waves in the bay within 5 min of the beginning of strong ground motion. Recent studies estimate the total volume of underwater slide material that moved in Resurrection Bay to be about 211 million m 3 (Haeussler et al. in Submarine mass movements and their consequences, pp 269–278, 2007 ). The first tectonic tsunami wave arrived in Resurrection Bay about 30 min after the main shock and was about the same height as the local landslide-generated waves. Our previous numerical study, which focused only on the local landslide-generated waves in Resurrection Bay, demonstrated that they were produced by a number of different slope failures, and estimated relative contributions of different submarine slide complexes into tsunami amplitudes (Suleimani et al. in Pure Appl Geophys 166:131–152, 2009 ). This work extends the previous study by calculating tsunami inundation in Resurrection Bay caused by the combined impact of landslide-generated waves and the tectonic tsunami, and comparing the composite inundation area with observations. To simulate landslide tsunami runup in Seward, we use a viscous slide model of Jiang and LeBlond (J Phys Oceanogr 24(3):559–572, 1994 ) coupled with nonlinear shallow water equations. The input data set includes a high resolution multibeam bathymetry and LIDAR topography grid of Resurrection Bay, and an initial thickness of slide material based on pre- and post-earthquake bathymetry difference maps. For simulation of tectonic tsunami runup, we derive the 1964 coseismic deformations from detailed slip distribution in the rupture area, and use them as an initial condition for propagation of the tectonic tsunami. The numerical model employs nonlinear shallow water equations formulated for depth-averaged water fluxes, and calculates a temporal position of the shoreline using a free-surface moving boundary algorithm. We find that the calculated tsunami runup in Seward caused first by local submarine landslide-generated waves, and later by a tectonic tsunami, is in good agreement with observations of the inundation zone. The analysis of inundation caused by two different tsunami sources improves our understanding of their relative contributions, and supports tsunami risk mitigation in south-central Alaska. The record of the 1964 earthquake, tsunami, and submarine landslides, combined with the high-resolution topography and bathymetry of Resurrection Bay make it an ideal location for studying tectonic tsunamis in coastal regions susceptible to underwater landslides.

Alaska↗

California State Waters Map Series: Offshore of Refugio Beach, California

In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within California’s State Waters. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath sonar data, acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow (to about 100 m) subsurface geology. The Offshore of Refugio Beach map lies within the western Santa Barbara Channel region of the Southern California Bight. This geologically complex region forms a major biogeographic transition zone, separating the cold-temperate Oregonian province north of Point Conception from the warm-temperate California province to the south. The map area is in the southern part of the Western Transverse Ranges geologic province, which is north of the California Continental Borderland. Significant clockwise rotation—at least 90°—since the early Miocene has been proposed for the Western Transverse Ranges province, and geodetic studies indicate that the region is presently undergoing north-south shortening. Uplift rates (as much as 0.5 mm/yr) that are based on studies of onland marine terraces provide further evidence of significant shortening. The coastal zone of this map area lies at the steep flank of the Santa Ynez Mountains. The crest of the range, which lies about 8 km from the shoreline (north of the map area), has a maximum elevation of about 780 m. This area is largely open space, partly used for livestock grazing, with no significant towns or population centers. Highway 101 crosses the map area, adjacent to and within a few hundred meters of the shoreline. The most significant developments are the recreational state beaches at El Capitan Beach and Refugio Beach. The beaches are subject to erosion each winter during storm-wave attack, and then they undergo gradual recovery or accretion during the more gentle wave climate of the late spring, summer, and fall months. The Offshore of Refugio Beach map area lies in the west-central part of the Santa Barbara littoral cell, which is characterized by west-to-east transport of sediment from Point Arguello on the northwest to Hueneme and Mugu Canyons on the southeast. Longshore drift rates have been reported to range from about 160,000 to 800,000 tons/yr, averaging 400,000 tons/yr. Sediment supply to the western and central part of the littoral cell, including the map area, is mainly from relatively small coastal watersheds. Within the map area, these coastal watersheds include (from east to west) Cañada del Capitan, Tajiquas Creek, Arroyo Hondo, Cañada del Molino, and several unnamed canyons and creeks. The Santa Ynez and Santa Maria Rivers, the mouths of which are 80 to 120 km northwest of the map area, are not considered significant sediment sources because Point Conception and Point Arguello provide obstacles to downcoast sediment transport and also because much of their sediment load is trapped in dams. The Ventura and Santa Clara Rivers, the mouths of which are about 70 km to the southeast of the map area, are not sediment sources for the map area. The offshore part of the map area consists of relatively flat and shallow continental shelf, which dips gently seaward (about 0.8° to 1.0°) so that water depths at the shelf break, roughly coincident with the California’s State Waters limit, are about 80 to 100 m. This part of the Santa Barbara Channel is relatively well protected from large Pacific swells from the north and northwest by Point Conception and from the south and southwest by offshore islands and banks. The shelf is underlain by variable amounts of upper Quaternary marine and fluvial sediments deposited as sea level fluctuated in the late Pleistocene. In the map area, the shelf break is at depths of about 90 m and lies about 5.6 to 6.4 km offshore. Beyond the shelf break, the slope is steep (as much as about 7°) and unstable. Several submarine landslides, including the large (130 km 2 ) Goleta landslide complex, have been documented offshore of Goleta, a few kilometers east of the map area. This compound slump complex may have been initiated more than 200,000 year ago, but it also includes three recent failures that may have been generated 8,000 to 10,000 years ago. A local, 10-m-high tsunami may have been generated from these failure events. Small folds related to local faulting are superimposed on the homocline that makes up the south flank of the Santa Ynez Mountains. One of these superimposed anticlines hosts the Molino gas field, which was discovered in 1962 and subsequently developed through directional drilling from onshore wells. The Oligocene Sespe and Vaqueros Formations are the reservoirs in the Molino gas field, and the map area includes numerous seafloor hydrocarbon seeps. Seafloor habitats in the broad Santa Barbara Channel region consist of significant amounts of soft, unconsolidated sediment interspersed with isolated areas of rocky habitat that support kelp-forest communities nearshore and rocky-reef communities in deep water. The potential marine benthic habitat types mapped in the Offshore of Refugio Beach map area are directly related to its Quaternary geologic history, geomorphology, and active sedimentary processes. These potential habitats, which lie primarily within the Shelf (continental shelf) but also partly within the Flank (basin flank or continental slope) megahabitats, primarily are composed of soft sediment interrupted by a few carbonate mounds. This homogeneous seafloor of sediment and low-relief bedrock provides promising habitat for groundfish, crabs, shrimp, and other marine benthic organisms.

California↗

Irrigated areas of India derived using MODIS 500 m time series for the years 2001-2003

The overarching goal of this research was to develop methods and protocols for mapping irrigated areas using a Moderate Resolution Imaging Spectroradiometer (MODIS) 500 m time series, to generate irrigated area statistics, and to compare these with ground- and census-based statistics. The primary mega-file data-cube (MFDC), comparable to a hyper-spectral data cube, used in this study consisted of 952 bands of data in a single file that were derived from MODIS 500 m, 7-band reflectance data acquired every 8-days during 2001-2003. The methods consisted of (a) segmenting the 952-band MFDC based not only on elevation-precipitation-temperature zones but on major and minor irrigated command area boundaries obtained from India's Central Board of Irrigation and Power (CBIP), (b) developing a large ideal spectral data bank (ISDB) of irrigated areas for India, (c) adopting quantitative spectral matching techniques (SMTs) such as the spectral correlation similarity (SCS) R 2 -value, (d) establishing a comprehensive set of protocols for class identification and labeling, and (e) comparing the results with the National Census data of India and field-plot data gathered during this project for determining accuracies, uncertainties and errors. The study produced irrigated area maps and statistics of India at the national and the subnational (e.g., state, district) levels based on MODIS data from 2001-2003. The Total Area Available for Irrigation (TAAI) and Annualized Irrigated Areas (AIAs) were 113 and 147 million hectares (MHa), respectively. The TAAI does not consider the intensity of irrigation, and its nearest equivalent is the net irrigated areas in the Indian National Statistics. The AIA considers intensity of irrigation and is the equivalent of "irrigated potential utilized (IPU)" reported by India's Ministry of Water Resources (MoWR). The field-plot data collected during this project showed that the accuracy of TAAI classes was 88% with a 12% error of omission and 32% of error of commission. Comparisons between the AIA and IPU produced an R 2 -value of 0.84. However, AIA was consistently higher than IPU. The causes for differences were both in traditional approaches and remote sensing. The causes of uncertainties unique to traditional approaches were (a) inadequate accounting of minor irrigation (groundwater, small reservoirs and tanks), (b) unwillingness to share irrigated area statistics by the individual Indian states because of their stakes, (c) absence of comprehensive statistical analyses of reported data, and (d) subjectivity involved in observation-based data collection process. The causes of uncertainties unique to remote sensing approaches were (a) irrigated area fraction estimate and related sub-pixel area computations and (b) resolution of the imagery. The causes of uncertainties common in both traditional and remote sensing approaches were definitions and methodological issues. ?? 2009 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS).

ISPRS Journal of Photogrammetry and Remote Sensing↗

California State Waters Map Series — Monterey Canyon and vicinity, California

Introduction In 2007, the California Ocean Protection Council initiated the California Seafloor Mapping Program (CSMP), designed to create a comprehensive seafloor map of high-resolution bathymetry, marine benthic habitats, and geology within the 3-nautical-mile limit of California’s State Waters. The CSMP approach is to create highly detailed seafloor maps through collection, integration, interpretation, and visualization of swath bathymetry data, acoustic backscatter, seafloor video, seafloor photography, high-resolution seismic-reflection profiles, and bottom-sediment sampling data. The map products display seafloor morphology and character, identify potential marine benthic habitats, and illustrate both the surficial seafloor geology and shallow subsurface geology. The Monterey Canyon and Vicinity map area lies within Monterey Bay in central California. Monterey Bay is one of the largest embayments along the west coast of the United States, spanning 36 km from its northern to southern tips (in Santa Cruz and Monterey, respectively) and 20 km along its central axis. Not only does it contain one of the broadest sections of continental shelf along California’s coast, it also contains Monterey Canyon, one of the largest and deepest submarine canyons in the world. Note that the California’s State Waters limit extends farther offshore between Santa Cruz and Monterey so that it encompasses all of Monterey Bay. The coastal area within the map area is lightly populated. The community of Moss Landing (population, 204) hosts the largest commercial fishing fleet in Monterey Bay in its harbor. The map area also includes parts of the cities of Marina (population, about 20,000) and Castroville (population, about 6,500). Fertile lowlands of the Salinas River and Pajaro River valleys largely occupy the inland part of the map area, and land use is primarily agricultural. The offshore part of the map area lies completely within the Monterey Bay National Marine Sanctuary. The map area also includes Portuguese Ledge and Soquel Canyon State Marine Conservation Areas. Designated conservation and (or) recreation areas in the onshore part of the map area include Salinas River National Wildlife Refuge, Elkhorn Slough State Marine Conservation Area, Elkhorn Slough State Marine Reserve, Moss Landing Wildlife Area, Zmudowski and Salinas River State Beaches, and Marina Dunes Preserve. Monterey Bay, a geologically complex area within a tectonically active continental margin, lies between two major, converging strike-slip faults. The northwest-striking San Andreas Fault lies about 34 km east of Monterey Bay; this section of the fault ruptured in both the 1989 M6.9 Loma Prieta earthquake and the 1906 M7.8 great California earthquake. The northwest-striking San Gregorio Fault crosses Monterey Canyon west of Monterey Bay. Between these two regional faults, strain is accommodated by the northwest-striking Monterey Bay Fault Zone. Deformation associated with these major regional faults and related structures has resulted in uplift of the Santa Cruz Mountains, as well as the granitic highlands of the Monterey peninsula. Monterey Canyon begins in the nearshore area directly offshore of Moss Landing and Elkhorn Slough, and it can be traced for more than 400 km seaward, out to water depths of more than 4,000 m. Within the map area, the canyon can be traced for about 42 km to a water depth of about 1,520 m. The head of the canyon consists of three branches that begin about 150 m offshore of Moss Landing Harbor. At 500 m offshore, the canyon is already 70 m deep and 750 m wide. Large sand waves, which have heights from 1 to 3 m and wavelengths of about 50 m, are present along the channel axis in the upper 4 km of the canyon. Soquel Canyon is the most prominent tributary of Monterey Canyon within the map area. The head of Soquel Canyon is isolated from coastal watersheds and, thus, is considered inactive as a conduit for coarse sediment transport. North and south of Monterey and Soquel Canyons, the relatively flat continental shelf contains only a few rocky outcrop exposures. Bedrock is covered largely by sediment derived from the Salinas and Pajaro Rivers. North of Monterey Canyon, the broad and flat continental shelf dips gently seaward, to water depths of about 95 m. To the south, the shelf also dips slightly, to water depths of as much as 150 m along the canyon edge. In the map area, Monterey Canyon splits the Santa Cruz littoral cell (north of the canyon) and the southern Monterey littoral cell (south of the canyon). It is estimated that about 400,000 m 3 /yr of sand on average enters Monterey Canyon from both of these littoral cells. In the Santa Cruz littoral cell, sand generally travels east and south. Sand is supplied through sea cliff erosion, as well as from the San Lorenzo River, the Pajaro River, and several other smaller coastal watersheds. About 152,911 m 3 /yr of sand is dredged from the entrance channel of the Santa Cruz Small Craft Harbor north of the map area and then placed on beaches to the east (downdrift) of it. This sand feeds the beaches in the southeastern reach of the Santa Cruz littoral cell and (or) is eventually trapped and lost by Monterey Canyon. The southern Monterey Bay littoral cell in the map area consists of two subcells. From the head of Monterey Canyon to the Salinas River, littoral drift is dominantly to the north; sand entering the ocean from the Salinas River either is deposited offshore or travels north in the littoral zone, nourishing the beaches until it is transported down Monterey Canyon. From south of the Salinas River to the southern extent of the map area, coastal sediment is moved mainly to the south; dune erosion is the only significant source of sand in this subcell.

California↗

Hydrology of area 54, northern Great Plains, and Rocky Mountain coal provinces, Colorado and Wyoming

A nationwide need for information characterizing hydrologic conditions in mined and potential mine areas has become paramount with the enactment of the Surface Mining Control and Reclamation Act of 1977. This report, one in a series covering the coal provinces nationwide, presents information thematically by describing single hydrologic topics through the use of brief texts and accompanying maps, graphs, or other illustrations. The summation of the topical discussions provides a description of the hydrology of the area. Area 54, in north-central Colorado and south-central Wyoming, is 1 of 20 hydrologic reporting areas of the Northern Great Plains and Rocky Mountain coal provinces. Part of the Southern Rocky Mountains and Wyoming Basin physiographic provinces, the 8,380-square-mile area is one of contrasting geology, topography, and climate. This results in contrasting hydrologic characteristics. The major streams, the North Platte, Laramie, and Medicine Bow Rivers, and their principal tributaries, all head in granitic mountains and flow into and through sedimentary basins between the mountain ranges. Relief averages 2,000 to 3,000 feet. Precipitation in the mountains may exceed 40 inches annually, much of it during the winter, which produces deep snowpacks. Snowmelt in spring and summer provides most streamflow. Precipitation in the basins averages 10 to 16 inches annually, insufficient for sustained streamflow; thus, streams originating in the basins are ephemeral. Streamflow quality is best in the mountains where dissolved-solids concentrations generally are least. These concentrations increase as streams flow through sedimentary basins. The increases are mainly natural, but some may be due to irrigation in and adjacent to the flood plains. In the North Platte River, dissolved-solids concentrations are usually less than 300 milligrams per liter; in the Laramie and the Medicine Bow Rivers, the concentrations may average 500 to 850 milligrams per liter. However, water-quality stations on the Laramie and the Medicine Bow Rivers are farther removed from the mountain sources than the stations in the North Platte drainage. Because of the semiarid climate of the basins, soils are not adequately leached. Consequently, flow in ephemeral streams usually has a larger concentration of dissolved solids than that in perennial streams, averaging 1,000 to 1,600 milligrams per liter. Aquifers containing usable ground water are combined into three groups: (1) consolidated and unconsolidated non-coal-bearing Quaternary and Upper Tertiary deposits, (2) Mesozoic and Paleozoic sedimentary rocks, and (3) Lower Tertiary and Upper Cretaceous sedimentary rocks containing coal. These aquifers are used for municipal, domestic, irrigation, and stock supplies. Well yields range from about 5 to 1,000 gallons per minute, and depend on type of aquifer, saturated thickness, and degree of fracturing. The best quality ground water usually comes from the non-coal-bearing Quaternary and Upper Tertiary rocks or the Mesozoic and Paleozoic rocks; often it is dominated by calcium and bicarbonate ions. The coal-bearing formations have a large variability in water chemistry; dominant ions may be bicarbonate or sulfate and sodium, calcium, or magnesium. Dissolved-solids concentrations are generally larger than in the former two groups. The U.S. Geological Survey operates a network of hydrologic stations to observe the streamflow and groundwater conditions. This network currently includes 31 surface-water stations and 35 observation wells; information is available for many other sites observed in the past. Data available include rate of flow, water levels, and water quality; much of the data are available in published reports or from computer storage through the National Water Data Exchange (NAWDEX) or the National Water Data Storage and Retrieval System (WATSTORE). Five formations of Late Cretaceous and early Tertiary age contain coal.

Colorado, Wyoming↗

Geologic map of the MTM-15182 and MTM-15187 quadrangles, Gusev Crater-Ma'adim Vallis region, Mars

This map is one of a series of large-scale (1:500,000) geologic maps of Mars initiated by the National Aeronautics and Space Administration to investigate areas of high scientific interest. The Gusev crater–Ma’adim Vallis region includes several potential landing sites for future Mars missions, including those with a focus on exobiology studies and sample return. Channels in the map area span a long age range, cut ancient rocks that may contain important biogenic information, and funneled water into exobiologically important lacustrine basins. The map area is characterized by diverse geologic units representing a variety of endogenic and exogenic processes. The geologic history of this region spans the entire history of the planet. The base map was compiled from controlled pho-tomosaic maps of the Mars Transverse Mercator (MTM) –15182 and –15187 quadrangles (U.S. Geological Survey, 1992a, b). The map area is in the Aeolis re-gion, which was first mapped from Mariner 9 images at 1:5,000,000 scale (Scott and others, 1978) and at 1:25,000,000 scale (Scott and Carr, 1978). On the basis of Viking data, the area was later mapped at 1:15,000,000 scale (Greeley and Guest, 1987) and in part at 1:5,000,000 scale (Scott and Chapman, 1995). Recently, the area was mapped at 1:1,000,000 scale by Landheim (1995). This 1:500,000-scale map shows a great diversity of geologic materials and demonstrates a more complete understanding of fluvial processes in the highland plains, the evolution of Ma’adim Vallis, and sedimentation in Gusev crater and in de Vaucou-leurs, an ancient 300-km-diameter impact structure west of Gusev crater. Standard photogeologic mapping techniques elucidated by Wilhelms (1990) were used in this work. Viking Orbiter images used to map the area range in resolution from 63 to 70 m/pixel, with small patches at 225 m/pixel.

IMAP↗

Streamflow and Endangered Species Habitat in the Lower Isleta Reach of the Middle Rio Grande

San Acacia Dam is located in a reach of the Rio Grande that has been designated as critical habitat for two endangered species, the Rio Grande silvery minnow (Hybognathus amarus) and the southwestern willow flycatcher (Empidonax traillii extimus). Under present operations, the Rio Grande upstream from the dam is used to convey irrigation water to the Socorro main canal at San Acacia Dam. In order to increase operational flexibility and improve irrigation delivery efficiency, the 'Bernardo Siphon' has been proposed to intercept up to 150 cubic feet per second from the Lower San Juan Riverside Drain on the east side of the Rio Grande and transport it under the river into a drainage canal on the west side. Irrigation deliveries to the Socorro main canal would be conveyed by way of the drainage canal rather than the Rio Grande. The objective of this study was to provide the Bureau of Reclamation (BOR) and other stakeholders with a tool to evaluate the effects of different operational modes of the Bernardo siphon on habitat for H. amarus and E. t. extimus in this section of river. We used a two-dimensional hydraulic simulation model to simulate hydraulic conditions for a range of discharges at three study sites in the Rio Grande between the proposed siphon location and San Acacia Dam. Suitable habitat characteristics were defined for H. amarus by consensus of a panel of experts and for E. t. extimus on the basis of a study conducted in 2003 by BOR. Habitat suitability maps for each targeted life stage and simulated discharge were constructed using a Geographic Information System (ArcGIS) and the results compiled into tables relating discharge to areas of suitable habitat. A separate analysis was conducted to calculate an index of connectivity among habitat patches at low flows. A hydrologic model was constructed to synthesize flows, by reach, without the siphon, which was used as a baseline for comparison with similarly-synthesized discharges with the siphon under different operating rules. Results from the hydrologic time series were combined with the discharge-habitat relations to develop habitat time series models, statistics, and scoring metrics for comparisons of alternative rules of operation for the Bernardo siphon. Suitable habitat for H. amarus was defined as areas having suitable hydraulic conditions alone and as areas having suitable hydraulics in association with large woody debris. Suitable hydraulic habitat for adults was maximized at discharges between 40 and 80 cubic feet per second, and declined rapidly at discharges larger than 150 cubic feet per second. When large woody debris was included in the definition of suitable habitat, discharges between 40 and 200 cubic feet per second provided maximum suitable habitat for adults. Juvenile hydraulic habitat was maximized at discharges between 20 and 80 cubic feet per second, and hydraulic habitat associated with large woody debris was largest at flows between 40 and 150 cubic feet per second. Nesting habitat area for E. t. extimus increased monotonically at discharges larger than 5 ft3/s, but decreased rapidly below that flow.

Open-File Report↗

Mapping spatial resources with GPS animal telemetry: foraging manatees locate seagrass beds in the Ten Thousand Islands, Florida, USA

Turbid water conditions make the delineation and characterization of benthic habitats difficult by traditional in situ and remote sensing methods. Here, we develop and validate modeling and sampling methodology for detecting and characterizing seagrass beds by analyzing GPS telemetry records from radio-tagged manatees. Between October 2002 and October 2005, 14 manatees were tracked in the Ten Thousand Islands (TTI) in southwest Florida (USA) using Global Positioning System (GPS) tags. High density manatee use areas were found to occur off each island facing the open, nearshore waters of the Gulf of Mexico. We implemented a spatially stratified random sampling plan and used a camera-based sampling technique to observe and record bottom observations of seagrass and macroalgae presence and abundance. Five species of seagrass were identified in our study area: Halodule wrightii, Thalassia testudinum, Syringodium filiforme, Halophila engelmannii, and Halophila decipiens. A Bayesian model was developed to choose and parameterize a spatial process function that would describe the observed patterns of seagrass and macroalgae. The seagrasses were found in depths <2 m and in the higher manatee use strata, whereas macroalgae was found at moderate densities at all sampled depths and manatee use strata. The manatee spatial data showed a strong association with seagrass beds, a relationship that increased seagrass sampling efficiency. Our camera-based field sampling proved to be effective for assessing seagrass density and spatial coverage under turbid water conditions, and would be an effective monitoring tool to detect changes in seagrass beds.

Florida↗

Geospatial compilation and digital map of centerpivot irrigated areas in the mid-Atlantic region, United States

To evaluate water availability within the Northern Atlantic Coastal Plain, the U.S. Geological Survey, in cooperation with the University of Delaware Agricultural Extension, created a dataset that maps the number of acres under center-pivot irrigation in the Northern Atlantic Coastal Plain study area. For this study, the extent of the Northern Atlantic Coastal Plain falls within areas of the States of New York, New Jersey, Delaware, Maryland, Virginia, and North Carolina. The irrigation dataset maps about 271,900 acres operated primarily under center-pivot irrigation in 57 counties. Manual digitizing was performed against aerial imagery in a process where operators used observable center-pivot irrigation signatures&mdash;such as irrigation arms, concentric wheel paths through cropped areas, and differential colors&mdash;to identify and map irrigated areas. The aerial imagery used for digitizing came from a variety of sources and seasons. The imagery contained a variety of spatial resolutions and included online imagery from the U.S. Department of Agriculture National Agricultural Imagery Program, Microsoft Bing Maps, and the Google Maps mapping service. The dates of the source images ranged from 2010 to 2012 for the U.S. Department of Agriculture imagery, whereas maps from the other mapping services were from 2013. Most of the irrigation in the study area is on the Delmarva Peninsula, where about 75 percent of the total acreage was delineated and where corn and soy bean are the main crops. The methods used to develop this dataset focused primarily on identifying center-pivot irrigation systems. In some instances (such as in in Suffolk County, New York), irrigated rectangular fields were observed through the aerial imagery, and these were included within the dataset. Other irrigation methods included subsurface drip and flood irrigation, which are commonly used on vegetable crops such as peppers and tomatoes and forage crops such as alfalfa in parts the western United States. Some fruit and nursery stock crops also use subsurface drip and flood irrigation. Drip irrigation is especially apparent in New Jersey where large plantings of truck crops are common. Subsurface drip and flood irrigation methods were not accounted for in this dataset. The U.S. Geological Survey collected these data to enhance the understanding of irrigation water demand and associated groundwater withdrawals for the Northern Atlantic Coastal Plain. The digitized acreage totals were compared with the irrigation estimates provided by the U.S. Department of Agriculture farm and ranch irrigation survey, which is the most comprehensive source of information on irrigation water use within the agricultural industry. This survey collects information on a wide range of topics, including the amount of water used, total acres irrigated, crop specific data, and even energy costs. The U.S. Department of Agriculture samples data for both entire States and individual counties.

Data Series↗

Moderate Resolution Imaging Spectroradiometer (MODIS) Overview

The Moderate Resolution Imaging Spectroradiometer (MODIS) is an instrument that collects remotely sensed data used by scientists for monitoring, modeling, and assessing the effects of natural processes and human actions on the Earth's surface. The continual calibration of the MODIS instruments, the refinement of algorithms used to create higher-level products, and the ongoing product validation make MODIS images a valuable time series (2000-present) of geophysical and biophysical land-surface measurements. Carried on two National Aeronautics and Space Administration (NASA) Earth Observing System (EOS) satellites, MODIS acquires morning (EOS-Terra) and afternoon (EOS-Aqua) views almost daily. Terra data acquisitions began in February 2000 and Aqua data acquisitions began in July 2002. Land data are generated only as higher-level products, removing the burden of common types of data processing from the user community. MODIS-based products describing ecological dynamics, radiation budget, and land cover are projected onto a sinusoidal mapping grid and distributed as 10- by 10-degree tiles at 250-, 500-, or 1,000-meter spatial resolution. Some products are also created on a 0.05-degree geographic grid to support climate modeling studies. All MODIS products are distributed in the Hierarchical Data Format-Earth Observing System (HDF-EOS) file format and are available through file transfer protocol (FTP) or on digital video disc (DVD) media. Versions 4 and 5 of MODIS land data products are currently available and represent 'validated' collections defined in stages of accuracy that are based on the number of field sites and time periods for which the products have been validated. Version 5 collections incorporate the longest time series of both Terra and Aqua MODIS data products.

Fact Sheet↗

Quantifying drought’s influence on moist soil seed vegetation in California’s Central Valley through time-series remote sensing

Californias Central Valley, USA is a critical component of the Pacific Flyway despite loss of more than 90% of its wetlands. Moist soil seed (MSS) wetland plants are now produced by mimicking seasonal flooding in managed wetlands to provide an essential food resource for waterfowl. Managers need MSS plant area and productivity estimates to support waterfowl conservation, yet this remains unknown at the landscape scale. Also the effects of recent drought on MSS plants have not been quantified. We generated Landsat-derived estimates of extents and productivity (seed yield or its proxy, the green chlorophyll index) of major MSS plants including watergrass (Echinochloa crusgalli) and smartweed (Polygonum spp.) (WGSW), and swamp timothy (Crypsis schoenoides) (ST) in all Central Valley managed wetlands from 20072017. We tested the effects of water year, land ownership and region on plant area and productivity with a multifactor nested analysis of variance. For the San Joaquin Valley we explored the association between water year and water supply, and we developed metrics to support management decisions. MSS plant area maps were based on a support vector machine classification of Landsat phenology metrics (2017 map overall accuracy: 89%). ST productivity maps were created with a linear regression model of seed yield (n=68, R2 = 0.53, normalized RMSE = 10.5%). The Central Valley-wide estimated area for ST in 2017 was 32,369 ha 2,524 ha (95% C.I.), and 13,012 ha 1,384 ha for WGSW. Mean ST seed yield ranged from 577 kg/ha in the Delta Basin to 365 kg/ha in the San Joaquin Basin. WGSW area and ST seed yield decreased while ST area increased in critical drought years compared to normal water years (Scheffes test, p<0.05). Greatest ST area increases occurred in the Sacramento Valley (~75%). Voluntary water deliveries increased in normal water years, and ST seed yield increased with water supply. Z-scores of ST seed yield can be used to evaluate wetland performance and aid resource allocation decisions. Updated maps will support habitat monitoring, conservation planning and water management in future years, which are likely to face greater uncertainty in water availability with climate change.

California↗

Understanding and documenting the scientific basis of selenium ecological protection in support of site-specific guidelines development for Lake Koocanusa, Montana, U.S.A., and British Columbia, Canada

Modeling of ecosystems is a part of the U.S. Environmental Protection Agency’s protocol for developing site-specific selenium guidelines for protection of aquatic life. Selenium as an environmental contaminant is known to bioaccumulate and cause reproductive effects in fish and wildlife. Here we apply a modeling methodology—ecosystem-scale selenium modeling—to understand and document the scientific basis for predicting and validating ecological protection for Lake Koocanusa, a transboundary reservoir between Montana and British Columbia. A comprehensive set of site-specific data compiled from public databases (Federal, State, and Provincial) and reports by Teck Coal Ltd., is available in a companion U.S. Geological Survey data release. The tissue guideline used within modeling here to assess protection is the U.S. Environmental Protection Agency’s national selenium guideline for whole-body fish (dry weight); however, other numeric values for a whole-body guideline or other tissue types may be assumed if applicable tissue-to-tissue conversion factors are available. We consider the report assembled here as a working document that presents a model that can effectively address and structure the needs of (1) scientific understanding in representing the lake’s ecosystem and selenium biodynamics and (2) policy and management development during a decision-making process, but it is open to modification and updating as more ecologically detailed data become available. The approach brings together the main concerns involved in selenium toxicity: likelihood of high exposure, inherent species sensitivity, and close connectivity of ecosystem characteristics and behavioral ecology of predators. Detailed site-specific modeling equations are provided to document the linked factors that determine the responses of ecosystems to selenium. A series of scenarios quantifies the implications of choices of site-specific variables including food-web species, bioavailability of particulate material, and partitioning between the dissolved and particulate phases at the base of food webs. A gradient mapping tool applied to Lake Koocanusa provides a precedent for ecosystem-scale modeling of lakes by recognizing the importance of lake strata and hydrodynamics as components of modeling. Data requirements for ecosystem modeling, including ecological and hydrological process information fundamental to the dietary biodynamics of selenium in site-specific food webs, were assessed as a precursor to model validation for Lake Koocanusa. Understanding these relationships is necessary to connect modeling outcomes to reproductive effects and establish boundaries, in the case of Lake Koocanusa, for the influences of dam operation, fish-community viability, and its Clean Water Act impaired 303(d)-listing status on ecosystem function. We find that an assemblage of conditions affects the representation of Lake Koocanusa’s ecosystem within modeling scenarios but that the constructed gradient maps, mechanistic model, and associated bioaccumulation potentials portray and quantify the variables that are determinative to protection of predator species. Ecological and hydrological sorting of compiled individual data points on a site- and species-specific basis helps identify and address model uncertainties. Sources of uncertainty include (1) the scarcity of data for some environmental media compartments across time and locations, (2) the complexity of hydrodynamic conditions that can lead to seasonal ecological disconnects such as in selenium partitioning from water into particulates, and (3) the functional status of Lake Koocanusa’s ecosystem because of cumulative effects of various environmental stresses (for example, fish-community changes, flow regime changes, parasites, gonadal dysfunction, and increasing mining input-selenium concentrations since 1984). To this last point, it is important to determine where Lake Koocanusa is in an impairment-restoration cycle so as not to base protection on survivor bias, the maintenance of a currently degraded ecosystem, or normalized toxicity. In a broader context, one of the overall consequences of revised selenium regulations is that their derivation is now dependent on being able to define and understand the status of the ecosystem on which protection is based.

Montana, British Columbia↗

Topographic map of Mars M 25M RKN

NOTES ON BASE This map is based on data from the Mars Orbiter Laser Altimeter (MOLA) (Smith and others, 2001), an instrument on NASA's Mars Global Surveyor (MGS) spacecraft (Albee and others, 2001). The image used for the base of this map represents more than 600 million measurements gathered between 1999 and 2001, adjusted for consistency (Neumann and others, 2001, 2002) and converted to planetary radii. These have been converted to elevations above the areoid as determined from a martian gravity field solution GMM2 (Lemoine and others, 2001), truncated to degree and order 50, and oriented according to current standards (see below). The average accuracy of each point is originally ~100 meters in horizontal position, and ~1 meter in radius (Neumann, 2001). However, the total elevation uncertainty is at least +3 m due to the global error in the areoid (+1.8 meters according to Lemoine and others, 2001) and regional uncertainties in its shape (communication from Neumann, 2002). The measurements were converted into a digital elevation model (DEM) (communication from Neumann, 2002; Neumann and others, 2001; Smith and others, 2001) using Generic Mapping Tools software (Wessel and Smith, 1998), with a resolution of 0.015625 degrees per pixel or 64 pixels per degree. In projection, the pixels are 926.17 meters in size at the equator. PROJECTION The Mercator projection is used between latitudes +57°, with a central meridian at 0° and latitude equal to the nominal scale at 0°. The Polar Stereographic projection is used for the polar regions north of the +55° parallel and south of the –55° parallel with a central meridian set for both at 0°. The adopted equatorial radius is 3,396.19 km (Duxbury and others 2002; Seidelmann and others 2002). COORDINATE SYSTEM The MOLA data were initially referenced to an internally consistent inertial coordinate system, derived from tracking of the MGS spacecraft. By adopting appropriate values for the orientation of Mars as defined by the International Astronomical Union (IAU) and the International Association of Geodesy (IAG) (Seidelmann and others, 2002), these inertial coordinates were converted into the planet-fixed coordinates (longitude and latitude) used on this map. These values include the orientation of the north pole of Mars (including the effects of precession), the rotation rate of Mars, and a value for W0 of 176.630°, where W0 is the angle along the equator to the east, between the 0° meridian and the equator's intersection with the celestial equator at the standard epoch J2000.0 (Seidelmann and others, 2002). This value of W0 was chosen (Duxbury and others, 2002) in order to place the 0° meridian through the center of the small (~500 m) crater Airy-0, located in the crater Airy (de Vaucouleurs and others, 1973; Seidelmann and others, 2002). Longitude increases to the east, and latitude is planetocentric as allowed by IAU/IAG standards (Seidelmann and others, 2002) and in accordance with current NASA and USGS standards (Duxbury and others, 2002). A secondary grid (printed in red) has been added to the map as a reference to the west longitude/planetographic latitude system that is also allowed by IAU/IAG standards (Seidelmann and others, 2002) and has also been used for Mars. The figure adopted to compute this secondary grid is an oblate spheroid with an equatorial radius of 3,396.19 km and a polar radius of 3,376.2 km (Duxbury and others, 2002; Seidelmann and others, 2002). MAPPING TECHNIQUES To create the topographic base image, the original DEM produced by the MOLA team in Simple Cylindrical projection with a resolution of 64 pixels per degree was projected into the Mercator and Polar Stereographic pieces. A shaded relief was generated from each DEM with a sun angle of 30° from horizontal and a sun azimuth of 270°, as measured clockwise from north, and a vertical exaggeration of 100%. Illumination is from the west, which follows a long-standing USGS tradition for planetary maps. This allows for continuity in the shading between maps and quadrangles, and most closely resembles lighting conditions found on imagery. The DEM values were then mapped to a smooth global color look-up table. Note that the chosen color scheme simply represents elevation changes and is not intended to imply anything about surface characteristics (e.g., past or current presence of water or ice). These two files were then merged and scaled to 1:25 million for the Mercator portion and 1:15,196,708 for the two Polar Stereographic portions, with a resolution of 300 dots per inch. The projections have a common scale of 1:13,923,113 at +56° latitude. NOMENCLATURE Names on this sheet are approved by the IAU and have been applied for features clearly visible at the scale of this map. For a complete list of the IAU-approved nomenclature for Mars, see the Gazetteer of Planetary Nomenclature at http://planetarynames.wr.usgs.gov/. Font color was chosen for readability. Names followed by an asterisk are provisionally approved. *M 25M RKN: Abbreviation for Mars, 1:25,000,000 series, shaded relief (R), with color (K) and nomenclature (N) (Greeley and Batson, 1990)

Open-File Report↗

An Automated Cropland Classification Algorithm (ACCA) for Tajikistan by combining Landsat, MODIS, and secondary data

The overarching goal of this research was to develop and demonstrate an automated Cropland Classification Algorithm (ACCA) that will rapidly, routinely, and accurately classify agricultural cropland extent, areas, and characteristics (e.g., irrigated vs. rainfed) over large areas such as a country or a region through combination of multi-sensor remote sensing and secondary data. In this research, a rule-based ACCA was conceptualized, developed, and demonstrated for the country of Tajikistan using mega file data cubes (MFDCs) involving data from Landsat Global Land Survey (GLS), Landsat Enhanced Thematic Mapper Plus (ETM+) 30 m, Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m time-series, a suite of secondary data (e.g., elevation, slope, precipitation, temperature), and in situ data. First, the process involved producing an accurate reference (or truth) cropland layer (TCL), consisting of cropland extent, areas, and irrigated vs. rainfed cropland areas, for the entire country of Tajikistan based on MFDC of year 2005 (MFDC2005). The methods involved in producing TCL included using ISOCLASS clustering, Tasseled Cap bi-spectral plots, spectro-temporal characteristics from MODIS 250 m monthly normalized difference vegetation index (NDVI) maximum value composites (MVC) time-series, and textural characteristics of higher resolution imagery. The TCL statistics accurately matched with the national statistics of Tajikistan for irrigated and rainfed croplands, where about 70% of croplands were irrigated and the rest rainfed. Second, a rule-based ACCA was developed to replicate the TCL accurately (∼80% producer’s and user’s accuracies or within 20% quantity disagreement involving about 10 million Landsat 30 m sized cropland pixels of Tajikistan). Development of ACCA was an iterative process involving series of rules that are coded, refined, tweaked, and re-coded till ACCA derived croplands (ACLs) match accurately with TCLs. Third, the ACCA derived cropland layers of Tajikistan were produced for year 2005 (ACL2005), same year as the year used for developing ACCA, using MFDC2005. Fourth, TCL for year 2010 (TCL2010), an independent year, was produced using MFDC2010 using the same methods and approaches as the one used to produce TCL2005. Fifth, the ACCA was applied on MFDC2010 to derive ACL2010. The ACLs were then compared with TCLs (ACL2005 vs. TCL2005 and ACL2010 vs. TCL2010). The resulting accuracies and errors from error matrices involving about 152 million Landsat (30 m) pixels of the country of Tajikistan (of which about 10 million Landsat size, 30 m, cropland pixels) showed an overall accuracy of 99.6% (k hat = 0.97) for ACL2005 vs. TCL2005. For the 3 classes (irrigated, rainfed, and others) mapped in ACL2005, the producer’s accuracy was >86.4% and users accuracy was >93.6%. For ACL2010 vs. TCL2010, the error matrix showed an overall accuracy on 96.2% (k hat = 0.96). For the 3 classes (irrigated, rainfed, and others) mapped in ACL2010, the producer’s and user’s accuracies for the irrigated areas were ≥82.9%. Any intermixing was overwhelmingly between irrigated and rainfed croplands, indicating that croplands (irrigated plus rainfed areas) as well as irrigated areas were mapped with high levels of accuracies (∼90% or higher) even for the independent year. The ACL2005 and ACL2010, each, were produced using ACCA algorithm in ∼30 min using a Dell Precision desktop T7400 computer for the entire country of Tajikistan once the MFDCs for the years were ready. The ACCA algorithm for Tajikistan is made available through US Geological Survey’s ScienceBase: http://www.sciencebase.gov/catalog/folder/4f79f1b7e4b0009bd827f548 or at: https://powellcenter.usgs.gov/globalcroplandwater/content/models-algorithms . The research contributes to the efforts of global food security through research on global croplands and their water use (e.g., https://powellcenter.usgs.gov/globalcroplandwater/ ). The above results clearly demonstrated the ability of a rule-based ACCA to rapidly and accurately produce cropland data layer year after year (hindcast, nowcast, forecast) for the country it was developed using MFDCs that consist of combining multiple sensor data and secondary data. It needs to be noted that the ACCA is applicable to the area (e.g., country, region) for which it is developed. In this case, ACCA is applicable for the Country of Tajikistan to hindcast, nowcast, and forecast agricultural cropland extent, areas, and irrigated vs. rainfed. The same fundamental concept of ACCA applies to other areas of the World where ACCA codes need to be modified to suite the area/region of interest. ACCA can also be expanded to compute other crop characteristics such as crop types, cropping intensities, and phenologies.

Remote Sensing↗

EAARL Topography-Vicksburg National Military Park 2007: First Surface

These remotely sensed, geographically referenced elevation measurements of Lidar-derived first-surface (FS) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the National Park Service (NPS), Gulf Coast Network, Lafayette, LA; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the Vicksburg National Military Park in Mississippi, acquired on September 12, 2007. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first surface topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

Data Series↗

EAARL topography: Jean Lafitte National Historical Park and Preserve 2006

These remotely sensed, geographically referenced elevation measurements of Lidar-derived first surface (FS) and bare earth (BE) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the National Park Service (NPS), Gulf Coast Network, Lafayette, LA; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the Jean Lafitte National Historical Park and Preserve in Louisiana, acquired on September 22, 2006. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of Lidar data in an interactive or batch mode. Modules for presurvey flight line definition, flight path plotting, Lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or first surface topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation from a point cloud of last return elevations.

Louisiana↗