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At least 1,495 records · Page 83Linked to original sources
USGS1993

Digital recordings of aftershocks of the April 25 and 26, 1992, Cape Mendocino, California, earthquakes

On April 25 and 26, 1992, three large earthquakes occurred near Cape Mendocino, Calif. The mainshock occurred on April 25 with M s = 7.1, the next day followed by two powerful aftershocks of M s = 6.6 and M s = 6.7. The permanent seismographic network operated by the U.S. Geological Survey located 197 aftershocks, greater than magnitude 3 during the following 3 weeks (Andrew Michael, personal commun., 1992). Most of them were located offshore (Michael, 1992, fig. 1). On April 27,1992, the author began operation of five portable digital seismographs located in a rough semi-circle approximately 50-90 km from the aftershock (fig. 1). The seismographs were operated for 12 days. The primary research goal was to contribute to aftershock locations with P- and S-arrival times and to record data to improve focal mechanism studies of the aftershocks. These goals were particularly important because the earthquakes originated in an especially complex, poorly understood tectonic regime. This report is intended to facilitate the use of the digital seismograms by other researchers. Tables 1A and B give the location and sensor specifications for each recording station. Appendix A is a narrative of road directions to the recording stations should they need to be reoccupied. Appendix B lists all of the trigger times of seismograms recorded by the network. Appendix C contains plots of the seismograms of earthquakes recorded by three or more seismographs. Appendix D is an example data file showing the format (DR-100). The data set is available directly from the author on 9-track tape.

California↗
USGS1995

Selected meteorological data for an arid site near Beatty, Nye County, Nevada, calendar years 1990 and 1991

Selected meteorological data were collected at a study site adjacent to a low-level radioactive-waste burial facility near Beatty, Nevada, for calendar years 1990 and 1991. Data were collected in support of ongoing studies to estimate the potential for downward movement of radionuclides into the unsaturated sediments beneath waste-burial trenches at the facility. The data include air temperature, relative humidity, vapor pressure, incident solar radiation, windspeed, wind direction, barometric pressure, and precipitation. The data are summarized in tables and graphs. Instrumentation used at the site is discussed. The discussion includes the type, reported accuracy, and mounting height of each sensor. In 1990, the average hourly air temperatures ranged from -16.2 degrees Celsius, in December, to 44.2 degrees Celsius, in July. Hourly averaged relative humidity ranged from 6 percent to more than 90 percent. Hourly vapor pressures ranged from 0.08 to 1.84 kilopascals. Daily maximum incident solar radiation values ranged from 192 to 1,028 watts per square meter. Daily mean windspeed ranged from less than 1 to 8.7 meters per second. Wind direction was primarily from the northwest in fall, winter, and spring and varied from southeast, southwest, or northwest during the summer. Hourly barometric pressures ranged from 99.47 to 103.12 kilopascals. Total precipitation for 1990 was 32.4 millimeters; almost 45 percent was in September. In 1991, the average hourly air temperatures ranged from -9.2 degrees Celsius, in January, to 43.7 degrees Celsius, in July. Hourly averaged relative humidity ranged from 3 percent to more than 95 percent. Hourly vapor pressures ranged from 0.07 to 2.22 kilopascals. Daily maximum incident solar radiation values ranged from 143 to 1,041 watts per square meter. Daily mean windspeed ranged from 1.2 to 8.4 meters per second. Wind direction was primarily from the northwest in fall, winter, and spring and varied from southeast, southwest, or northwest during the summer. Hourly barometric pressures ranged from 99.52 to 103.40 kilopascals. Total precipitation for 1991 was 103.6 millimeters; almost 60 percent was in March.

Nevada↗
USGS1995

Meteorological and associated data collected over agricultural fields in Pinal County, Arizona, 1989 and 1990

Data were collected at temporary meteorological stations installed in agricultural fields in Pinal County, Arizona, to evaluate the spatial and temporal variability of point data and to examine how station location affects ground-based meteorological data and the resulting values of evapotranspiration calculated using remotely sensed multispectral data from satellites. Time-specific data were collected to correspond with satellite overpasses from April to October 1989, and June 27-28, 1990. Meteorological data consisting of air temperature, relative humidity, wind speed, solar radiation, and net radiation were collected at each station during all periods of the project. Supplementary measurements of soil temperature, soil heat flux density, and surface or canopy temperature were obtained at some locations during certain periods of the project. Additional data include information on data-collection periods, station positions, instrumentation, sensor heights, and field dimensions. Other data, which correspond to the extensive field measurements made in con- junction with satellite overpasses in 1989 and 1990, include crop type, canopy cover, canopy height, irrigation, cultivation, and orientation of rows. Field boundaries and crop types were mapped in a 2- to 3-square-kilometer area surrounding each meteorological station. Field data are presented in tabular and graphic form. Meteorological and supplementary data are available, upon request, in digital form.

Open-File Report↗
USGS1995

Measurements of salinity, temperature, and tides in south San Francisco Bay, California, at Dumbarton Bridge: 1990-93 water years

The U.S. Geological Survey measures salinity, temperature, and water levels (tides) in southern San Francisco Bay at Dumbarton Bridge as part of a cooperative program with the California State Department of Water Resources. During water years 1990-93, measurements were made at 15-minute intervals with electonic sensors located approximately one meter above the substrate in approximately six meters of water (at mean water level). During March and April of 1991 and 1992, salinity and temperature also were measured with a self-contained system floating one meter below the surface of the water. Sections of the data set were selected to illustrate influences of tidal currents, weather events, and seasonal and interannual variations in climate on salinity, temperature, and water levels at this location. The edited data are provided on high-density disks in comma-delimited, ASCII text files.

California↗
USGS1996

Selected meteorological and micrometeorological data for an arid site near Beatty, Nye County, Nevada, calendar year 1992

il-heat-flux data were collected at a study site adjacent to a low-level radioactive-waste burial facility near Beatty, Nevada, for calendar year 1992. Data were collected in support of ongoing studies to estimate the potential for downward movement of radionuclides into the unsaturated sediments beneath waste-burial trenches at the arid facility. Data collected for the whole year include air temperature, relative humidity, vapor pressure, incident solar radiation, windspeed, wind direction, barometric pressure, and precipitation. Net radiation, soil temperature, and soil-heat flux data also were collected for part of the year. The data are summarized in tables and graphs. Instrumentation used at the site is discussed. The discussion includes the type, reported accuracy, and the mounting height of each sensor. During 1992, the hourly and 20-minute mean air temperatures ranged from -8.6 degrees Celsius, in January, to 42.3 degrees Celsius, in July. Hourly and 20-minute mean relative humidity ranged from 2 percent to 100 percent. Hourly and 20-minute mean vapor pressures ranged from 0.07 to 2.47 kilopascals. Daily maximum incident solar radiation values ranged from 115 to 1,021 watts per square meter. Daily maximum net radiation values ranged from 195 to 632 watts per square meter. Daily mean windspeed ranged from 0.6 to 8.1 meters per second. Wind direction was primarily from the northwest in fall, winter, and spring and was from the southeast, southwest, or northwest during the summer. Barometric pressures ranged from 100.16 kilopascals to 103.38 kilopascals. Total precipitation for 1992 was 165.3 millimeters, with more than 50 percent in February and March. Daily mean soil temperatures at a depth from 2 to 6 centimeters ranged from 10.7 to 39.1 degrees Celsius between June and October. Daily mean soil-heat flux at a dep*h of 8 centimeters ranged from -13.4 to 12.2 watts per square meter during the same period.

Nevada↗
USGS1998

Geometeorological data collected by the USGS Desert Winds Project at Desert Wells, Sonoran Desert, central-west Arizona, 1981 - 1996

The data in this report were obtained by instruments deployed on a GOES-satellite data collection station operated by the U.S. Geological Survey Desert Winds Project at Desert Wells (latitude 33° 42' 08" N, longitude 113° 48' 40" W), La Paz County, west-central Arizona. The elevation is 344 m (1,130 ft). From January 9, 1981 through May 31, 1995 the station recorded eight parameters: wind direction, wind speed, peak gust, air temperature, precipitation, humidity, barometric pressure, and soil temperature. On June 1, 1995, the station was upgraded by adding a SENSIT sand-flux sensor, which records grain impacts concurrently with wind speed and wind direction measurements. Included with the data is descriptive text on the geology, soils, climate, vegetation, and land use at the site, as well as text on data format, date retrieval software and instructions, and metadata

Arizona↗
USGS2008

Seismicity and infrasound associated with explosions at Mount St. Helens, 2004-2005

Six explosions occurred during 2004-5 in association with renewed eruptive activity at Mount St. Helens, Washington. Of four explosions in October 2004, none had precursory seismicity and two had explosion-related seismic tremor that marked the end of the explosion. However, seismicity levels dropped following each of the October explosions, providing the primary instrumental means for explosion detection during the initial vent-clearing phase. In contrast, explosions on January 16 and March 8, 2005, produced noticeable seismicity in the form of explosion-related tremor, infrasonic signals, and, in the case of the March 8 explosion, an increase in event size ~2 hours before the explosion. In both 2005 cases seismic tremor appeared before any infrasonic signals and was best recorded on stations located within the crater. These explosions demonstrated that reliable explosion detection at volcanoes like Mount St. Helens requires seismic stations within 1-2 km of the vent and stations with multiple acoustic sensors.

Washington↗
USGS2008

Seismic-monitoring changes and the remote deployment of seismic stations (seismic spider) at Mount St. Helens, 2004-2005

The instruments in place at the start of volcanic unrest at Mount St. Helens in 2004 were inadequate to record the large earthquakes and monitor the explosions that occurred as the eruption developed. To remedy this, new instruments were deployed and the short-period seismic network was modified. A new method of establishing near-field seismic monitoring was developed, using remote deployment by helicopter. The remotely deployed seismic sensor was a piezoelectric accelerometer mounted on a surface-coupled platform. Remote deployment enabled placement of stations within 250 m of the active vent.

Washington↗
USGS2010

The 2006 eruption of Augustine Volcano, Alaska

Augustine Volcano, the most historically active volcano in Alaska’s Cook Inlet region, again showed signs of life in April 2005. Escalating seismic unrest, ground deformation, and gas emissions culminated in an eruption from January 11 to mid-March of 2006, the fifth major eruption in 75 years. The eruption began with a series of 13 short-lived blasts over 20 days that sent pyroclastic flows; snow, rock, and ice avalanches; and lahars down the volcano’s snow clad flanks; ash clouds drifted hundreds of kilometers downwind. Punctuated explosive activity gave way to effusion of lava and emplacement of thick block-and-ash flows on the volcano’s north flank that continued through mid-February. In mid-March renewed extrusion resulted in the building of a new, higher summit lava dome and two blocky lava flows on the north and northeast flanks of the cone. The eruption resulted in ash fall on many south-central Alaskan communities and disrupted air traffic in the region. Augustine’s frequent eruptions and relatively easy access have long drawn volcanologists to study the accumulation, ascent, and eruption of andesitic to dacitic magma. Studies of the most recent activity before 2006, in 1976 and 1986, revealed that the volcano lately produces explosive eruptions that are preceded by months of unrest and injection of new magma into a storage region in the upper several kilometers of the crust. Each of these eruptions then followed a similar progression from explosive to effusive behavior over several months. Petrologic and geophysical observations suggest that these three eruptions were triggered by similar magma mixing events and that the subsequent ascent and eruption of magma was governed by processes that were roughly constant from one eruption to the next. Geologic studies of the island show that in the more distant past parts of Augustine’s edifice have failed repeatedly, resulting in debris avalanches that entered the sea and, at least once, in 1883, caused a tsunami that hit surrounding Cook Inlet coastlines. Such edifice failures and resultant local tsunamis should be expected in the future. Recognition of Augustine’s frequent activity and hazardous nature led to the installation of a network of telemetered seismometers beginning in 1971, the establishment of a geodetic network in 1988, and the installation of other new instrumentation such as pressure sensors, broadband seismometers, and cameras by the Alaska Volcano Observatory (AVO), and the selection of Augustine for geodetic instrumentation through the EarthScope/Plate Boundary Observatory program in 2004. In addition, remote sensing techniques, such as airborne thermal imaging and the advanced spaceborne thermal emission and reflection radiometer (ASTER), provided novel and often critical information as the 2006 eruption progressed. The combination of a long-term seismic network and an array of new monitoring techniques has provided a breadth and depth of understanding of Augustine’s most recent activity that was not possible in the past. This volume contains 28 chapters reporting on a diverse suite of new scientific observations and investigations that were motivated by the 2006 eruption. Understanding the magmatic processes that drive eruptions, identifying eruptive events, tracking the movement of ash clouds, and communicating the resultant hazards to other government agencies and the public are all critical tasks for AVO, and chapters touch upon all of these topics. One goal in this compilation is to synthesize the diverse information into as complete an understanding of the magmatic and eruptive processes as possible. An equally important goal is to provide a framework for diagnosing periods of unrest and formulating forecasts of eruptions that will certainly take place at Augustine in the future. This latter goal is especially important, as Augustine’s frequent eruptive activity suggests that another eruption can be expected within the next several decades. Consequently, the investigations in this volume are intended to provide both a means to better forecast future eruptive episodes and also an opportunity to formulate and test future hypotheses for magmatic and eruptive processes. Future eruptions may follow a course similar to those observed in 1976, 1986, and 2006. However, a major perturbation that upsets conditions within the magmatic system could occur, owing perhaps to the rise of a much larger or different parental magma or to a large edifice failure similar to the 1883 sector collapse. In such events, the comprehensive study of past eruptions will provide data critical to assessing the current state of the magmatic system. In assembling this volume we have sought as consistent and accurate a portrayal of the 2006 eruption as possible. We have asked all authors to refer to the same basic eruption chronology, unless their observations and data require alternative explanations. Naturally, not all techniques or methodologies produce a completely consistent set of observations, nor do the precise conclusions in every paper support one another. We have grouped chapters on the basis of discipline. Papers that focus on specific techniques, methodology, or instrumentation are placed throughout the volume where they best fit with others that rely on their results.

Alaska↗
USGS2012

An economic value of remote-sensing information—Application to agricultural production and maintaining groundwater quality

Does remote-sensing information provide economic benefits to society, and can a value be assigned to those benefits? Can resource management and policy decisions be better informed by coupling past and present Earth observations with groundwater nitrate measurements? Using an integrated assessment approach, the U.S. Geological Survey (USGS) applied an established conceptual framework to answer these questions, as well as to estimate the value of information (VOI) for remote-sensing imagery. The approach uses moderate-resolution land-imagery (MRLI) data from the Landsat and Advanced Wide Field Sensor satellites that has been classified by the National Agricultural Statistics Service into the Cropland Data Layer (CDL). Within the constraint of the U.S. Environmental Protection Agency's public health threshold for potable groundwater resources, the USGS modeled the relation between a population of the CDL's land uses and dynamic nitrate (NO3-) contamination of aquifers in a case study region in northeastern Iowa. Employing various multiscaled, multitemporal geospatial datasets with MRLI to maximize the value of agricultural production, the approach develops and uses multiple environmental science models to address dynamic nitrogen loading and transport at specified distances from specific sites (wells) and at landscape scales (for example, across 35 counties and two aquifers). In addition to the ecosystem service of potable groundwater, this effort focuses on the use of MRLI for the management of the major land uses in the study region-the production of corn and soybeans, which can impact groundwater quality. Derived methods and results include (1) economic and dynamic nitrate-pollution models, (2) probabilities of the survival of groundwater, and (3) a VOI for remote sensing. For the northeastern Iowa study region, the marginal benefit of the MRLI VOI (in 2010 dollars) is $858 million ±$197 million annualized, which corresponds to a net present value of $38.1 billion ±$8.8 billion for that flow of benefits in perpetuity. Given that these economic estimates are derived from one case study in a part of only one State, the estimates provide a lower estimate related to the potential value of the Landsat Data Continuity Mission.

Professional Paper↗
USGS2021

Global cropland-extent product at 30-m resolution (GCEP30) derived from Landsat satellite time-series data for the year 2015 using multiple machine-learning algorithms on Google Earth Engine cloud

Executive Summary Global food and water security analysis and management require precise and accurate global cropland-extent maps. Existing maps have limitations, in that they are (1) mapped using coarse-resolution remote-sensing data, resulting in the lack of precise mapping location of croplands and their accuracies; (2) derived by collecting and collating national statistical data that are often subjective, leading to substantial uncertainties in cropland-area estimates, as well as their locations; and (3) extracted from one or more classes of a land use–land cover product in which cropland classes are not the focus of mapping, leading to their mixing with other classes and creating significant errors of omission and commission. These limitations can be overcome by producing high-resolution cropland-extent maps using satellite-sensor data, such as Landsat 30-m resolution or higher. The most fundamental cropland product is the high-resolution cropland-extent map because all higher level cropland products, such as crop-watering method (that is, whether crops are irrigated or rainfed), crop types, cropping intensities, cropland fallows, crop productivity, and crop-water productivity, are dependent on a precise and accurate cropland-extent product. Given these realities, the overarching goal of this study was to produce a Landsat satellite-derived global cropland-extent product at 30-m resolution. The work, which involved a paradigm shift in how global cropland-extent maps are produced, involved the following five key steps: (1) petabyte-scale computing that involved multiyear, 8- to 16-day, time-series Landsat 30-m resolution data for the global land surface; (2) composition of analysis-ready data (ARD) cubes; (3) creation of a large global-reference data hub for machine learning; (4) use of multiple machine-learning algorithms (MLAs) by writing software and computing in the cloud; and (5) Google Earth Engine (GEE) cloud computing. The five key steps involved nine distinct phases. First, the world was segmented into 74 agroecological zones (AEZs). Second, Landsat 8- to 16-day data were used to time-composite 10-band (blue, green, red, near-infrared, short-wave infrared band 1, short-wave infrared band 2, thermal infrared, enhanced vegetation index, normalized difference water index, and normalized difference vegetation index) Landsat 30-m resolution data cubes for every 2- to 4-month time period during 3- to 4-year periods (stated as nominal-year 2015 or, simply, 2015), along with two additional 30-m resolution bands (Shuttle Radar Topography Mission elevation, and slope) in each of the 74 AEZs. Third, more than 100,000 reference-training data samples were collected using ground data (some of which were collected using a mobile application), as well as submeter- to 5-m-resolution, very high-resolution imagery sourced from other reliable sources. Fourth, reference-training data were used to create a knowledge base for separating cropland from noncropland. Fifth, MLAs such as the pixel-based supervised random forest and support-vector machines were written on the GEE using Python and JavaScript. Sixth, object-based recursive hierarchical segmentation algorithm was used, in addition to MLAs, to overcome uncertainties. Seventh, MLAs used the knowledge base to classify and separate cropland from noncropland. Eighth, accuracy assessment was conducted by generating error matrices for each of the 74 AEZs using 19,171 independent validation-data samples. Ninth, cropland areas were computed for all countries of the world and compared with United Nation’s (UN’s) Food and Agricultural Organization (FAO) and other national statistics. The outcome was a Landsat-derived global cropland-extent product at 30-m resolution (GCEP30), which has an overall accuracy of 91.7 percent. For the cropland class, producer’s accuracy was 83.4 percent, and user’s accuracy was 78.3 percent. GCEP30 calculated (using direct pixel count) the global net-cropland area (GNCA) for the year 2015 as 1.873 billion hectares (~12.6 percent of the Earth’s terrestrial area). The continental cropland distribution as a percentage of GNCA was Asia, 33 percent; Europe, 25.5 percent; Africa, 16.7 percent; North America, 14.4 percent; South America, 8.1 percent; and Australia and Oceania, 2.4 percent. The worldwide cropland areas in GCEP30 for 2015 were higher by 236 to 299 million hectares (Mha) compared to national statistics reported elsewhere for the same year (for example, in Food and Agriculture Organization’s corporate statistical database [FAOSTAT] and in the monthly irrigated and rainfed crop areas [MIRCA] database). The global cropland area reported for 2015 increased by 344 Mha (22.5 percent), compared to the year 2000. During the same period (2000–2015), the world’s population increased by 20 percent. Whereas some of these areal increases are real increases in cropland areas, others are due to the types of data, methods, and approaches used. Using the highest known resolution (compared to previous coarse-resolution global products) enabled this study to capture fragmented croplands. Coarse-resolution data compute areas on the basis of subpixels, which, for a large proportion of certain land use–land cover classes, will show only a certain percentage of the total pixel area as actual area. Subpixel areas can lead to substantial uncertainties in area computation, as determining the exact fraction of cropland areas within a coarse-resolution pixel is resource intensive and subject to errors. Other innovations in GCEP30 include reference-data hubs, machine learning, and cloud computing. Cropland areas in 214 countries, territories, departments, and regions were calculated for the year 2015 using GCEP30, on the basis of UN’s global administrative unit layers (GAUL) boundaries. The 10 leading countries in terms of cropland area (as a percentage of the GNCA) were India (9.6 percent), United States (8.95 percent), China (8.82 percent), Russia (8.32 percent), Brazil (3.42 percent), Ukraine (2.32 percent), Canada (2.29 percent), Argentina (2.05 percent), Indonesia (2 percent), and Nigeria (1.91 percent). Together, these 10 countries occupy 50 percent of the global cropland, and they have 52 percent of the global population. Their combined cropland area increased by 2 percent between 2000 and 2015, compared to the substantial increase in population of 517 million (15.5 percent). Together, India, United States, China, and Russia encompass 36 percent of the total area. In the United States and Canada, from 2000 to 2015, cropland decreased by about 2 percent, whereas their populations increased by 14 and 13 percent, respectively. The additional food requirements in these 10 countries, which are caused by increased populations, as well as increasing nutritional demands, are met by production increases in existing cropland or through virtual food trade, or both. More than 18 countries, territories, departments, or regions had 60 percent or more of their geographic area as cropland: Republic of Moldova, San Marino, and Hungary had more than 80 percent of the country’s area as cropland; Denmark, Ukraine, Ireland, and Bangladesh, 70 to 80 percent; and Uruguay, Netherlands, United Kingdom, Spain, Lithuania, Poland, Gaza Strip, Czechia, Italy, India, and Azerbaijan, 60 to 70 percent. Europe and South Asia can be considered agricultural capitals of the world, on the basis of their percentages of geographic area as cropland. United States, China, and Russia, which all have high cropland areas, are ranked second, third, and fourth in the world; India is ranked first. However, the amount of cropland as a percentage of the country’s geographic area is relatively very low for United States (18.3 percent), China (17.7 percent), and Russia (9.5 percent), whereas it is 60.5 percent for India. Most African and South American countries, territories, departments, or regions have less than 15 percent of their geographic area as cropland. China and India together house 36 percent of the world’s population; however, between 2000 and 2015, the amount of China’s cropland area fell by 18.9 percent, owing to urban expansion and the abandonment of farmlands caused by demographic changes (that is, the movement of population from villages to cities). In contrast, China’s population grew by 10 percent. The amount of India’s cropland increased by 8.5 percent, whereas its population grew by 20 percent. This study showed that, out of the 10 leading cropland countries, Ukraine, Nigeria, Russia, and Indonesia showed an 18 to 31 percent increase in cropland areas, on the basis of GCEP30 by the year 2015, compared to 2000. Nigeria’s cropland area increased by 25 percent, and its population increased by 31 percent in the same period. In these countries, food security is maintained by cropland expansion, productivity increases, and virtual food trade. Nevertheless, this trend of increasing net-cropland area and productivity will likely become difficult to maintain, owing to diminishing arable lands and plateauing of 50 years of continual yield increases, requiring policymakers to explore novel and data-supported approaches to solving future food security issues. The GCEP30 product, which can be browsed at full resolution at www.croplands.org , has been released for public download and use through U.S. Geological Survey (USGS)–National Aeronautics and Space Administration (NASA) Land Processes Distributed Active Archive Center (see https://lpdaac.usgs.gov/news/release-of-gfsad-30-meter-cropland-extent-products/ ).

Professional Paper↗
USGS2010

Conifer health classification for Colorado, 2008

Colorado has undergone substantial changes in forests due to urbanization, wildfires, insect-caused tree mortality, and other human and environmental factors. The U.S. Geological Survey Rocky Mountain Geographic Science Center evaluated and developed a methodology for applying remotely-sensed imagery for assessing conifer health in Colorado. Two classes were identified for the purposes of this study: healthy and unhealthy (for example, an area the size of a 30- x 30-m pixel with 20 percent or greater visibly dead trees was defined as ?unhealthy?). Medium-resolution Landsat 5 Thematic Mapper imagery were collected. The normalized, reflectance-converted, cloud-filled Landsat scenes were merged to form a statewide image mosaic, and a Normalized Difference Vegetation Index (NDVI) and Renormalized Difference Infrared Index (RDII) were derived. A supervised maximum likelihood classification was done using the Landsat multispectral bands, the NDVI, the RDII, and 30-m U.S. Geological Survey National Elevation Dataset (NED). The classification was constrained to pixels identified in the updated landcover dataset as coniferous or mixed coniferous/deciduous vegetation. The statewide results were merged with a separate health assessment of Grand County, Colo., produced in late 2008. Sampling and validation was done by collecting field data and high-resolution imagery. The 86 percent overall classification accuracy attained in this study suggests that the data and methods used successfully characterized conifer conditions within Colorado. Although forest conditions for Lodgepole Pine (Pinus contorta) are easily characterized, classification uncertainty exists between healthy/unhealthy Ponderosa Pine (Pinus ponderosa), Pi?on (Pinus edulis), and Juniper (Juniperus sp.) vegetation. Some underestimation of conifer mortality in Summit County is likely, where recent (2008) cloud-free imagery was unavailable. These classification uncertainties are primarily due to the spatial and temporal resolution of Landsat, and of the NLCD derived from this sensor. It is believed that high- to moderate-resolution multispectral imagery, coupled with field data, could significantly reduce the uncertainty rates. The USGS produced a four-county follow-up conifer health assessment using high-resolution RapidEye remotely sensed imagery and field data collected in 2009.

Scientific Investigations Map↗
USGS2013

Automated mapping of mineral groups and green vegetation from Landsat Thematic Mapper imagery with an example from the San Juan Mountains, Colorado

Multispectral satellite data acquired by the ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) and Landsat 7 Enhanced Thematic Mapper Plus (TM) sensors are being used to populate an online Geographic Information System (GIS) of the spatial occurrence of mineral groups and green vegetation across the western conterminous United States and Alaska. These geospatial data are supporting U.S. Geological Survey national-scale mineral deposit database development and other mineral resource and geoenvironmental research as a means of characterizing mineral exposures related to mined and unmined hydrothermally altered rocks and mine waste. This report introduces a new methodology for the automated analysis of Landsat TM data that has been applied to more than 180 scenes covering the western United States. A map of mineral groups and green vegetation produced using this new methodology that covers the western San Juan Mountains, Colorado, and the Four Corners Region is presented. The map is provided as a layered GeoPDF and in GIS-ready digital format. TM data analysis results from other well-studied and mineralogically characterized areas with strong hydrothermal alteration and (or) supergene weathering of near-surface sulfide minerals are also shown and compared with results derived from ASTER data analysis.

Colorado↗
USGS2013

Comparative mineral mapping in the Colorado Mineral Belt using AVIRIS and ASTER remote sensing data

This report presents results of interpretation of spectral remote sensing data covering the eastern Colorado Mineral Belt in central Colorado, USA, acquired by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) sensors. This study was part of a multidisciplinary mapping and data integration project at the U.S. Geological Survey that focused on long-term resource planning by land-managing entities in Colorado. The map products were designed primarily for the regional mapping and characterization of exposed surface mineralogy, including that related to hydrothermal alteration and supergene weathering of pyritic rocks. Alteration type was modeled from identified minerals based on standard definitions of alteration mineral assemblages. Vegetation was identified using the ASTER data and subdivided based on per-pixel chlorophyll content (depth of 0.68 micrometer absorption band) and dryness (fit and depth of leaf biochemical absorptions in the shortwave infrared spectral region). The vegetation results can be used to estimate the abundance of fire fuels at the time of data acquisition (2002 and 2003). The AVIRIS- and ASTER-derived mineral mapping results can be readily compared using the toggleable layers in the GeoPDF file, and by using the provided GIS-ready raster datasets. The results relating to mineral occurrence and distribution were an important source of data for studies documenting the effects of mining and un-mined, altered rocks on aquatic ecosystems at the watershed level. These studies demonstrated a high correlation between metal concentrations in streams and the presence of hydrothermal alteration and (or) pyritic mine waste as determined by analysis of the map products presented herein. The mineral mapping results were also used to delineate permissive areas for various mineral deposit types.

Colorado↗
USGS2021

Improved Automated Identification and Mapping of Iron Sulfate Minerals, Other Mineral Groups, and Vegetation using Landsat 8 Operational Land Imager Data, San Juan Mountains, Colorado, and Four Corners Region

Multispectral remote sensing data acquired by the Landsat 8 Operational Land Imager (OLI) sensor were analyzed using a new, automated technique to generate a map of exposed mineral and vegetation groups in the western San Juan Mountains, Colo., and the Four Corners Region of the United States. Band ratio results were combined into displayed mineral and vegetation groups using Boolean algebra. New analysis logic has been implemented to exploit the coastal aerosol band in Landsat 8 OLI data and identify concentrations of iron sulfate minerals. These may indicate the presence of near-surface pyrite, which can be a potential nonpoint source of acid rock drainage. Zoned occurrences of iron sulfate minerals in areas surrounding and down gradient of known sources of pyrite have been mapped using this technique. They show high correlation with occurrences of jarosite-bearing mineral assemblages, as mapped using airborne imaging spectrometer data and supporting field verification surveys. Mapping the occurrence of iron sulfate minerals produced by the weathering and oxidation of pyrite in exposed hydrothermally altered rocks can also provide an important indicator of the genetic environment of alteration and the associated mineral deposit type. The automated analysis methodology is being employed to rapidly and cost-effectively generate maps of large regions of the United States in support of U.S. Geological Survey mineral resource and mineral-environmental assessments. This map, which includes the ERDAS IMAGINE thematic raster format in the data release, has been attributed by pixel value with mineral and vegetation group classification data, which can be queried in most image processing and GIS software packages.

Colorado, Utah↗
USGS2004

Ground-Water System in the Chimacum Creek Basin and Surface Water/Ground Water Interaction in Chimacum and Tarboo Creeks and the Big and Little Quilcene Rivers, Eastern Jefferson County, Washington

A detailed study of the ground-water system in the unconsolidated glacial deposits in the Chimacum Creek Basin and the interactions between surface water and ground water in four main drainage basins was conducted in eastern Jefferson County, Washington. The study will assist local watershed planners in assessing the status of the water resources and the potential effects of ground-water development on surface-water systems. A new surficial geologic map of the Chimacum Creek Basin and a series of hydrogeologic sections were developed by incorporating LIDAR imagery, existing map sources, and drillers' logs from 110 inventoried wells. The hydrogeologic framework outlined in the study will help characterize the occurrence of ground water in the unconsolidated glacial deposits and how it interacts with the surface-water system. Water levels measured throughout the study show that the altitude of the water table parallels the surface topography and ranges from 0 to 400 feet above the North American Vertical Datum of 1988 across the basin, and seasonal variations in precipitation due to natural cycles generally are on the order of 2 to 3 feet. Synoptic stream-discharge measurements and instream mini-piezometers and piezometers with nested temperature sensors provided additional data to refine the positions of gaining and losing reaches and delineate seasonal variations. Chimacum Creek generally gains water from the shallow ground-water system, except near the community of Chimacum where localized losses occur. In the lower portions of Chimacum Creek, gaining conditions dominate in the summer when creek stages are low and ground-water levels are high, and losing conditions dominate in the winter when creek stages are high relative to ground-water levels. In the Quilcene Bay area, three drainage basins were studied specifically to assess surface water/ground water interactions. The upper reaches of Tarboo Creek generally gain water from the shallow ground-water system throughout most of the year and the lower reaches have little or no gains. The Big Quilcene River generally gains water from the shallow ground-water system after it emerges from a bedrock canyon and loses water from the town of Quilcene to the mouth of the river in Quilcene Bay. The Little Quilcene River generally loses water to the shallow ground-water system, although two localized areas were found to have gaining conditions. The Big Quilcene and Little Quilcene Rivers incur significant losses on the alluvial plain at the head of Quilcene Bay. Each of the creeks examined had a unique pattern of gaining and losing reaches, owing to the hydraulic conductivity of the streambed material and the relative altitude of the surrounding water table. Although the magnitudes of gains and losses varied seasonally, the spatial distribution did not vary greatly, suggesting that patterns of gains and losses in surface-water systems depend greatly on the geology underlying the streambed.

Scientific Investigations Report↗
USGS2005

Using the tracer-dilution discharge method to develop streamflow records for ice-affected streams in Colorado

Accurate ice-affected streamflow records are difficult to obtain for several reasons, which makes the management of instream-flow water rights in the wintertime a challenging endeavor. This report documents a method to improve ice-affected streamflow records for two gaging stations in Colorado. In January and February 2002, the U.S. Geological Survey, in cooperation with the Colorado Water Conservation Board, conducted an experiment using a sodium chloride tracer to measure streamflow under ice cover by the tracer-dilution discharge method. The purpose of this study was to determine the feasibility of obtaining accurate ice-affected streamflow records by using a sodium chloride tracer that was injected into the stream. The tracer was injected at two gaging stations once per day for approximately 20 minutes for 25 days. Multiple-parameter water-quality sensors at the two gaging stations monitored background and peak chloride concentrations. These data were used to determine discharge at each site. A comparison of the current-meter streamflow record to the tracer-dilution streamflow record shows different levels of accuracy and precision of the tracer-dilution streamflow record at the two sites. At the lower elevation and warmer site, Brandon Ditch near Whitewater, the tracer-dilution method overestimated flow by an average of 14 percent, but this average is strongly biased by outliers. At the higher elevation and colder site, Keystone Gulch near Dillon, the tracer-dilution method experienced problems with the tracer solution partially freezing in the injection line. The partial freezing of the tracer contributed to the tracer-dilution method underestimating flow by 52 percent at Keystone Gulch. In addition, a tracer-pump-reliability test was conducted to test how accurately the tracer pumps can discharge the tracer solution in conditions similar to those used at the gaging stations. Although the pumps were reliable and consistent throughout the 25-day study period, the pumps underdischarged the tracer by 5.8-15.9 percent as compared to the initial pumping rate setting, which may explain some of the error in the tracer-dilution streamflow record as compared to current-meter streamflow record.

Scientific Investigations Report↗
USGS2004

Seismic monitoring at Cascade volcanic centers, 2004 — Status and recommendations

The purpose of this report is to assess the current (May, 2004) status of seismic monitoring networks at the 13 major Cascade volcanic centers. Included in this assessment are descriptions of each network, analyses of the ability of each network to detect and to locate seismic activity, identification of specific weaknesses in each network, and a prioritized list of those networks that are most in need of additional seismic stations. At the outset it should be recognized that no Cascade volcanic center currently has an adequate seismic network relative to modern-day networks at Usu Volcano (Japan) or Etna and Stromboli volcanoes (Italy). For a system the size of Three Sisters, for example, a modern-day, cutting-edge seismic network would ideally consist of a minimum of 10 to 12 short-period three-component seismometers (for determining particle motions, reliable S-wave picks, moment tensor inversions, fault-plane solutions, and other important seismic parameters) and 7 to 10 broadband sensors (which, amongst other considerations, enable detection and location of very long period (VLP) and other low-frequency events, moment tensor inversions, and, because of their wide dynamic range, on-scale recording of large-amplitude events). Such a dense, multi component seismic network would give the ability to, for example, detect in near-real-time earthquake migrations over a distance of ~0.5km or less, locate tremor sources, determine the nature of a seismic source (that is, pure shear, implosive, explosive), provide on-scale recordings of very small and very large-amplitude seismic signals, and detect localized changes in seismic stress tensor orientations caused by movement of magma bodies. However, given that programmatic resources are currently limited, installation of such networks at this time is unrealistic. Instead, this report focuses on identifying what additional stations are needed to guarantee that anomalous seismicity associated with volcanic unrest will be detected in a timely manner and, in the case of magnitude = 1 earthquakes, reliably located.

California, Nevada, Oregon, Washington↗