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USGS1987

Computer simulations of large asteroid impacts into oceanic and continental sites--Preliminary results on atmospheric, cratering and ejecta dynamics

Computer simulations have been completed that describe passage of a 10-km-diameter asteroid through the Earth's atmosphere and the subsequent cratering and ejecta dynamics caused by impact of the asteroid into both oceanic and continental sites. The asteroid was modeled as a spherical body moving vertically at 20 km/s with a kinetic energy of 2.6 × 10 30 ergs (6.2 × 10 7 Mt ). Detailed material modeling of the asteroid, ocean, crustal units, sedimentary unit, and mantle included effects of strength and fracturing, generic asteroid and rock properties, porosity, saturation, lithostatic stresses, and geothermal contributions, each selected to simulate impact and geologic conditions that were as realistic as possible. Calculation of the passage of the asteroid through a U.S. Standard Atmosphere showed development of a strong bow shock wave followed by a highly shock compressed and heated air mass. Rapid expansion of this shocked air created a large low-density region that also expanded away from the impact area. Shock temperatures in air reached ∼20, 000K near the surface of the uplifting crater rim and were as high as ∼2000K at more than 30 km range and 10 km altitude. Calculations to 30 s showed that the shock fronts in the air and in most of the expanding shocked air mass preceded the formation of the crater, ejecta, and rim uplift and did not interact with them. As cratering developed, uplifted rim and target material were ejected into the very low density, shock-heated air immediately above the forming crater, and complex interactions could be expected. Calculations of the impact events showed equally dramatic effects on the oceanic and continental targets through an interval of 120 s. Despite geologic differences in the targets, both cratering events developed comparable dynamic flow fields and by ∼29s had formed similar-sized transient craters ∼39km deep and ∼62km across. Transient-rim uplift of ocean and crust reached a maximum altitude of nearly 40 km at ∼30s and began to decay at velocities of 500 m/s to develop large-tsunami conditions. After ∼30s, strong gravitational rebound drove both craters toward broad flat-floored shapes. At 120 s, transient crater diameters were ∼80km (continental) and ∼105km (oceanic) and transient depths were ∼27km; crater floors consisting of melted and fragmented hot rock were rebounding rapidly upward. By 60 s, the continental crater had ejected ∼2 × 10 14 t, about twice the mass ejected from the oceanic crater. By 120 s, ∼70, 000km 3 (continental) and ∼90, 000km 3 (oceanic) target material were excavated (no mantle) and massive ejecta blankets were formed around the craters. We estimate that in excess of ∼70% of the ejecta would finally lie within ∼3 crater diameters of the impact, and the remaining ejecta (∼10 13 t), including the vaporized asteroid, would be ejected into the atmosphere to altitudes as high as the ionosphere. Effects of secondary volcanism and return of the ocean over hot oceanic crater floor could also be expected to contribute substantial material to the atmosphere.

International Journal of Impact Engineering↗

USGS1994

The 1989-1990 eruption of Redoubt Volcano, Alaska: impacts on aircraft operations

The December 1989–June 1990 eruption of Redoubt Volcano affected commercial and military air operations in the vicinity of Anchorage, Alaska. These effects were due to the direct impact of volcanic ash on jet aircraft, as well as to the rerouting and cancellations of flight operations owing to eruptive activity. Between December and February, five commercial jetliners were damaged from ash encounters. The most serious incident took place on December 15, 1989 when a Boeing 747-400 aircraft temporarily lost power of all four engines after encountering an ash cloud as the airplane descended for a landing in Anchorage. While there were no injuries to passengers, the damage to engines, avionics, and aircraft structure from this encounter is estimated at $80 million. Four additional encounters between jet aircraft and Redoubt ash clouds occurred in the Anchorage area on December 15 and 16, 1989 and February 21, 1990; none resulted in engine failure. Two additional encounters took place on December 17, 1989 when jet airliners encountered the Redoubt cloud over west Texas. At the time of these encounters, the cloud was up to 55 hours old and had traveled in excess of 2,900 nautical miles (5,300 km). Following the December 15 encounters, Anchorage International Airport remained open, however, most airline companies canceled operations for up to several days. As communications between Federal agencies and airlines improved, and as a better understanding of the nature and behavior of ash-rich eruption clouds was achieved, most airlines resumed normal service by early January 1990. The resulting loss of revenue at Anchorage International Airport during several months following the eruption is estimated to total $2.6 million. The impact on general aviation and military operations consisted mostly of cancellation and rerouting of flights.

Alaska↗

USGS2010

EAARL coastal topography-western Florida, post-Hurricane Charley, 2004: seamless (bare earth and submerged.

Project Description These remotely sensed, geographically referenced elevation measurements of lidar-derived seamless (bare-earth and submerged) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Coastal and Marine Geology Program (CMGP), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the western Florida coastline beachface, acquired post-Hurricane Charley on August 17 and 18, 2004. 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 multispectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter 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 sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website. Selected References Brock, J.C., Wright, C.W., Sallenger, A.H., Krabill, W.B., and Swift, R.N., 2002, Basis and methods of NASA airborne topographic mapper Lidar surveys for coastal studies: Journal of Coastal Research, v. 18, no. 1, p. 1-13. Crane, Michael, Clayton, Tonya, Raabe, Ellen, Stoker, Jason, Handley, Larry, Bawden, Gerald, Morgan, Karen, and Queija, Vivian, 2004, Report of the U.S. Geological Survey Lidar workshop sponsored by the Land Remote Sensing Program and held in St. Petersburg, FL, November 2002: U.S. Geological Survey Open-File Report 2004-1456, 72 p. Nayegandhi, Amar, Brock, J.C., and Wright, C.W., 2009, Small-footprint, waveform-resolving Lidar estimation of submerged and sub-canopy topography in coastal environments: International Journal of Remote Sensing, v. 30, no. 4, p. 861-878. Sallenger, A.H., Wright, C.W., and Lillycrop, Jeff, 2005, Coastal impacts of the 2004 hurricanes measured with airborne Lidar; initial results: Shore and Beach, v. 73, nos. 2-3, p. 10-14. Resources Included Readme.txt File

Data Series↗

USGS2024

Enhanced microplastic fragmentation along human built structures in an urban waterway

Plastic pollution and microplastic (MP, 1 µm to 5 mm) generation are growing problems affecting the global community and a wide range of natural and disturbed environments. Urban and suburban waterways are directly impacted by plastic pollution due to their proximity to population centers and many different types single use plastic waste sources. In this study, plastic waste accumulation and fragmentation was investigated along the Cooper River in Camden County, NJ. Polymer composition was identified for individual plastic waste particles collected along the Cooper River using Fourier transform infrared (FTIR) spectrometry. Multiple human-built structures (Wallworth Lake, Evans Pond and Hopkins Pond dams) along the Cooper River were found to accumulate different types of plastic waste. The accumulation of plastic waste along these structures resulted in the initial stages of plastic fragmentation and the identification of large MP particles (1 to 5 mm). Quantitative analysis revealed that fragmented polystyrene (PS) particles constituted 82.8% of the total plastic fragments identified, most of which were identified at the Wallworth Lake dam. Many other types of fragmented plastic litter, including polyethylene and polypropylene, were identified at the Wallworth Lake dam, as well. This research demonstrates that engineered structures within urban and suburban aquatic ecosystems serve as significant aggregators of plastic debris, thereby catalyzing its breakdown into microplastics. Considering the escalating ecological and human health ramifications of microplastic proliferation, the fragmentation of plastic waste in an urban and suburban waterway observed in this study can also result in potentially toxic smaller MP particles, and increased exposure to aquatic organisms and humans.

New Jersey↗

USGS2011

Monitoring of urban subsidence with SAR interferometric point target analysis: A case study in Suzhou, China

Ground subsidence, mainly caused by over exploitation of groundwater and other underground resources, such as oil, gas and coal, occurs in many cities in China. The annual direct loss associated with subsidence across the country is estimated to exceed 100 million US dollar. Interferometric SAR (InSAR) is a powerful tool to map ground deformation at an unprecedented level of spatial detail. It has been widely used to investigate the deformation resulting from earthquakes, volcanoes and subsidence. Repeat-pass InSAR, however, may fail due to impacts of spatial decorrelation, temporal decorrelation and heterogeneous refractivity of atmosphere. In urban areas, a large amount of natural stable radar reflectors exists, such as buildings and engineering structures, at which radar signals can remain coherent during a long time interval. Interferometric point target analysis (IPTA) technique, also known as persistent scatterers (PS) InSAR is based on these reflectors. It overcomes the shortfalls in conventional InSAR. This paper presents a procedure for urban subsidence monitoring with IPTA. Calculation of linear deformation rate and height residual, and the non-linear deformation estimate, respectively, are discussed in detail. Especially, the former is highlighted by a novel and easily implemented 2-dimensional spatial search algorithm. Practically useful solutions that can significantly improve the robustness of IPTA, are recommended. Finally, the proposed procedure is applied to mapping the ground subsidence in Suzhou city, Jiangsu province, China. Thirty-four ERS-1/2 SAR scenes are analyzed, and the deformation information over 38,881 point targets between 1992 and 2000 are generated. The IPTA-derived deformation estimates correspond well with leveling measurements, demonstrating the potential of the proposed subsidence monitoring procedure based on IPTA technique. Two shortcomings of the IPTA-based procedure, e.g., the requirement of large number of SAR images and assumed linear plus non-linear deformation model, are discussed as the topics of further research.

Jaingsu Province↗

USGS2019

Mapping cropland extent of Southeast and Northeast Asia using multi-year time-series Landsat 30-m data using Random Forest classifier on Google Earth Engine

Cropland extent maps are useful components for assessing food security. Ideally, such products are a useful addition to countrywide agricultural statistics since they are not politically biased and can be used to calculate cropland area for any spatial unit from an individual farm to various administrative unites (e.g., state, county, district) within and across nations, which in turn can be used to estimate agricultural productivity as well as degree of disturbance on food security from natural disasters and political conflict. However, existing cropland extent maps over large areas (e.g., Country, region, continent, world) are derived from coarse resolution imagery (250 m to 1 km pixels) and have many limitations such as missing fragmented and\or small farms with mixed signatures from different crop types and\or farming practices that can be, confused with other land cover. As a result, the coarse resolution maps have limited useflness in areas where fields are small (<1 ha), such as in Southeast Asia. Furthermore, coarse resolution cropland maps have known uncertainties in both geo-precision of cropland location as well as accuracies of the product. To overcome these limitations, this research was conducted using multi-date, multi-year 30-m Landsat time-series data for 3 years chosen from 2013 to 2016 for all Southeast and Northeast Asian Countries (SNACs), which included 7 refined agro-ecological zones (RAEZ) and 12 countries (Indonesia, Thailand, Myanmar, Vietnam, Malaysia, Philippines, Cambodia, Japan, North Korea, Laos, South Korea, and Brunei). The 30-m (1 pixel = 0.09 ha) data from Landsat 8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper (ETM+) were used in the study. Ten Landsat bands were used in the analysis (blue, green, red, NIR, SWIR1, SWIR2, Thermal, NDVI, NDWI, LSWI) along with additional layers of standard deviation of these 10 bands across 1 year, and global digital elevation model (GDEM)-derived slope and elevation bands. To reduce the impact of clouds, the Landsat imagery was time-composited over four time-periods (Period 1: January- April, Period 2: May-August, and Period 3: September-December) over 3-years. Period 4 was the standard deviation of all 10 bands taken over all images acquired during the 2015 calendar year. These four period composites, totaling 42 band data-cube, were generated for each of the 7 RAEZs. The reference training data (N = 7849) generated for the 7 RAEZ using sub-meter to 5-m very high spatial resolution imagery (VHRI) helped generate the knowledge-base to separate croplands from non-croplands. This knowledge-base was used to code and run a pixel-based random forest (RF) supervised machine learning algorithm on the Google Earth Engine (GEE) cloud computing environment to separate croplands from non-croplands. The resulting cropland extent products were evaluated using an independent reference validation dataset (N = 1750) in each of the 7 RAEZs as well as for the entire SNAC area. For the entire SNAC area, the overall accuracy was 88.1% with a producer’s accuracy of 81.6% (errors of omissions = 18.4%) and user’s accuracy of 76.7% (errors of commissions = 23.3%). For each of the 7 RAEZs overall accuracies varied from 83.2 to 96.4%. Cropland areas calculated for the 12 countries were compared with country areas reported by the United Nations Food and Agriculture Organization and other national cropland statistics resulting in an R 2 value of 0.93. The cropland areas of provinces were compared with the province statistics that showed an R 2 = 0.95 for South Korea and R 2 = 0.94 for Thailand. The cropland products are made available on an interactive viewer at www.croplands.org and for download at National Aeronautics and Space Administration’s (NASA) Land Processes Distributed Active Archive Center (LP DAAC): https://lpdaac.usgs.gov/node/1281 .

International Journal of Applied Earth Observation↗

USGS2014

Methane hydrates in nature - Current knowledge and challenges

Recognizing the importance of methane hydrate research and the need for a coordinated effort, the United States Congress enacted the Methane Hydrate Research and Development Act of 2000. At the same time, the Ministry of International Trade and Industry in Japan launched a research program to develop plans for a methane hydrate exploratory drilling project in the Nankai Trough. India, China, the Republic of Korea, and other nations also have established large methane hydrate research and development programs. Government-funded scientific research drilling expeditions and production test studies have provided a wealth of information on the occurrence of methane hydrates in nature. Numerous studies have shown that the amount of gas stored as methane hydrates in the world may exceed the volume of known organic carbon sources. However, methane hydrates represent both a scientific and technical challenge, and much remains to be learned about their characteristics and occurrence in nature. Methane hydrate research in recent years has mostly focused on: (1) documenting the geologic parameters that control the occurrence and stability of methane hydrates in nature, (2) assessing the volume of natural gas stored within various methane hydrate accumulations, (3) analyzing the production response and characteristics of methane hydrates, (4) identifying and predicting natural and induced environmental and climate impacts of natural methane hydrates, (5) analyzing the methane hydrate role as a geohazard, (6) establishing the means to detect and characterize methane hydrate accumulations using geologic and geophysical data, and (7) establishing the thermodynamic phase equilibrium properties of methane hydrates as a function of temperature, pressure, and gas composition. The U.S. Department of Energy (DOE) and the Consortium for Ocean Leadership (COL) combined their efforts in 2012 to assess the contributions that scientific drilling has made and could continue to make to advance our understanding of methane hydrates in nature. COL assembled a Methane Hydrate Project Science Team with members from academia, industry, and government. This Science Team worked with COL and DOE to develop and host the Methane Hydrate Community Workshop, which surveyed a substantial cross section of the methane hydrate research community for input on the most important research developments in our understanding of methane hydrates in nature and their potential role as an energy resource, a geohazard, and/or as an agent of global climate change. Our understanding of how methane hydrates occur in nature is still growing and evolving, and it is known with certainty that field, laboratory, and modeling studies have contributed greatly to our understanding of hydrates in nature and will continue to be a critical source of the information needed to advance our understanding of methane hydrates.

Journal of Chemical and Engineering Data↗