These data represent the centerline and measured increments at hundredths, tenths and whole miles, along the centerline of the Colorado River beginning at Glen Canyon Dam near Page, Arizona and terminating near the inflow s of Lake Mead in the Grand Canyon region of Arizona, USA. The centerline was digitized using Color Infra-Red (CIR) orthophotography collected in March 2000 as source information and a LiDAR-derived river shoreline representing 8,000 cubic feet per second (CFS)as the defined extent of the river. Every effort was made to follow the main flow of the river while keeping the line approximately equidistant from both shorelines. The centerline feature class has been created to more accurately map locations along the Colorado River downstream of the Glen Canyon Dam. River miles and river kilometers were developed from measurements along this line. The incremental point feature classes were derived from the centerline of the Colorado River datasets. Specifically, the points were generated from nodes extracted from the centerline endpoints of the tenth mile line feature class. The Grand Canyon Monitoring and Research Center (GCMRC) river mileage was cross-checked with commercially available river guides and always fell within one mile of the guides, usually corresponding within a half mile. Additionally, these data were subjected to internal review by GCMRC scientists and commercial boatmen with decades of river travel experience on the Colorado River. River Mile 0 was measured from the USGS concrete gage and cableway at Lees Ferry, Arizona -- as per the Colorado River Compact of 1922 -- with negative river mile numbers used in Glen Canyon and positive river mile numbers downstream in Marble and Grand Canyons. These data were updated in March 2015 using newer ortho-rectified imagery collected in May of 2009 and 2013, both at approximately 8,000 CFS. Due to extended drought conditions that have persisted in the U.S. Southwest, lake levels have dropped dramatically, especially at Lake Mead. A stretch of the Colorado River corridor that was part of Lake Mead in year 2000 has returned to a flowing river once again, and with a different channel that has not previously existed. All changes to the original centerline are downstream of River Mile 260 which is just upstream of Quartermaster Canyon in western Grand Canyon. New river miles and river kilometers were developed from this updated centerline.

A digital elevation model (DEM) of a portion of the Mobile-Tensaw Delta region and Three Mile Creek in Alabama was produced from remotely sensed, geographically referenced elevation measurements by the U.S. Geological Survey (USGS). Elevation measurements were collected over the area (bathymetry was irresolvable) using the Experimental Advanced Airborne Research Lidar (EAARL), a pulsed laser ranging system mounted onboard an aircraft to measure ground elevation, vegetation canopy, and coastal topography. The system uses high-frequency laser beams directed at the Earth's surface through an opening in the bottom of the aircraft's fuselage. The laser system records the time difference between emission of the laser beam and the reception of the reflected laser signal in the aircraft. The plane travels over the target area at approximately 50 meters per second at an elevation of approximately 300 meters, resulting in a laser swath of approximately 240 meters with an average point spacing of 2-3 meters. The EAARL, developed originally by the National Aeronautics and Space Administration (NASA) at Wallops Flight Facility in Virginia, measures ground elevation with a vertical resolution of +/-15 centimeters. A sampling rate of 3 kilohertz or higher results in an extremely dense spatial elevation dataset. Over 100 kilometers of coastline can be surveyed easily within a 3- to 4-hour mission. When resultant elevation maps for an area are analyzed, they provide a useful tool to make management decisions regarding land development. For more information on Lidar science and the Experimental Advanced Airborne Research Lidar (EAARL) system and surveys, see http://ngom.usgs.gov/dsp/overview/index.php and http://ngom.usgs.gov/dsp/tech/eaarl/index.php .

The purpose of this project is to assess the variability of near shore surface circulation (upper 1 meter) off the coast of Barrow and Wainwright. The North Slope Borough has jurisdiction over waters within 3 miles from its coast. Direct surface flow measurements are taken by CODE (1 m drogue) drifters which were deployed within 3 to 15 nautical miles from shore in July and/or August 2011-2014 during the open water season in the Arctic. These measurements will help us to better understand the flow, shear and dispersion of near shore surface currents in the Chukchi Sea.

Sillimanite deposits were inspected on November 1st, 1949. The deposits are reported to extend over a length of approximately 3 miles and a width of ½ mile. Mr Sandland of Morialpa Station conducted us to the more important outcrops. Sillimanite deposits were inspected on November 1st, 1949. The deposits are reported to extend over a length of approximately 3 miles and a width of ½ mile. Mr Sandland of Morialpa Station conducted us to the more important outcrops.

This statistic shows the total land and water area of the United States by state and territory. Alabama covers an area of 52,420 square miles.

This dataset contains the polygons that make up the geodatabase for Miramar Landuse. The City of Miramar is a linear city 14 miles in length from east to west and 1.5 to 2.5 miles in width, comprising approximately 31 square miles. The boundaries of the City are delineated by Pembroke Road to the north, U.S. 441 to the east, the Broward County line to the south, and they also extend 1/2 mile west of U.S. 27 into Everglades Water Conservation Area 3A. The City’s development pattern has occurred from east to west with approximately one-third of the land area currently developed. The predominate land use is low density residential. Updated on 7/1/2009 related to Ord no. 09-15, on 1/14/2015 related to Ord no.15-07, on 7/10/2019 related to Ord no.19-01 and Ord no.19-18.

This data set provides a 38-year, 1-km resolution inventory of annual on-road CO2 emissions for the conterminous United States based on roadway-level vehicle traffic data and state-specific emissions factors for multiple vehicle types on urban and rural roads as compiled in the Database of Road Transportation Emissions (DARTE). CO2 emissions from the on-road transportation sector are provided annually for 1980-2017 as a continuous surface at a spatial resolution of 1 km.

This is a point data set representing river miles of the main channel of the Lower Boise River created by the City of Boise Public Works Department. The points are approximately 1/10th of a mile apart from each other for flexibility in landmark identification and model node selection (used in analysis). A river mile is a relative measure of the navigable distances in the deepest part of the channel. It is the distance in miles along a river from its mouth. River mile numbers begin at zero and increase further upstream. The data set was created by digitizing 1/10th of a mile measurements along the river channel using 2015 Idaho NAIP Imagery (1-meter resolution) at a 1:3000 scale or finer. As newer high-quality aerial imagery becomes available, a new version of the dataset will be created to reflect changes in the main channel over time and made available here. We are currently working on a 2017 version.For more information about this dataset, please contact Darcy Sharp, City of Boise Public Works Environmental Data Analyst, dsharp@cityofboise.org.Data Usage:If you download this dataset, it is highly recommended that you keep track of the year of imagery the dataset is correlated to, in this case it is 2015. As newer NAIP imagery becomes available, we will release a newer version of this dataset. It is especially important to cite the year if this dataset will be used in published documents so readers are clear on which vintage of the dataset was used in cartographic products, for analyses, etc.Data and Attribute Creation Information:The National Hydrography Dataset (NHD) is not used for this river mile layer. The NHD layer includes alternative side channels, ephemeral tributaries, and other river features that result in a high river mileage tally. NHD often uses contours to predict where the stream should be but does not connect that to actual flowing water.Features in this data set were created via heads-up digitizing. This data set is subject to errors in source data accuracy and errors introduced in the digitizing process. Source data includes: River Mile locations - 2015 Natural Color and IR 1-meter NAIP Idaho aerial imageryRiver Reach (local landmark) values - USGS (https://waterdata.usgs.gov/id/nwis/ for HUC 17050114) Site Identification numbers, IDWR Site Identification Numbers(https://research.idwr.idaho.gov/apps/Hydrologic/Accounting/ for the Boise River System), Idaho Department of Environmental Quality water quality assessments (https://cloud.insideidaho.org), and Idaho Department of Fish and Game fishing and boating access sites (https://data-idfggis.opendata.arcgis.com/datasets/idfg-fishing-and-boating-access-sites)DEQ Assessment Units - assigned by referencing the DEQ Integrated Report found at https://mapcase.deq.idaho.gov/wq2014/Elevation values - grdn44w117_13 raster downloaded from the US Geological Survey digital elevation model available on The National Map at https://viewer.nationalmap.gov/basic/Latitude and Longitude values - calculated using GIS

Surface ocean velocities estimated from HF-Radar are representative of the upper 0.3 - 2.5 meters of the ocean. The main objective of near-real time processing is to produce the best product from available data at the time of processing. Radial velocity measurements are obtained from individual radar sites through the U.S. HF-Radar Network. Hourly radial data are processed by unweighted least-squares on a 6 km resolution grid of the U.S. West Coast to produce near real-time surface current maps.Surface ocean velocities estimated from HF-Radar are representative of the upper 0.3 - 2.5 meters of the ocean. The main objective of near-real time processing is to produce the best product from available data at the time of processing. Radial velocity measurements are obtained from individual radar sites through the U.S. HF-Radar Network. Hourly radial data are processed by unweighted least-squares on a 6 km resolution grid of the U.S. West Coast to produce near real-time surface current maps.Surface ocean velocities estimated from HF-Radar are representative of the upper 0.3 - 2.5 meters of the ocean. The main objective of near-real time processing is to produce the best product from available data at the time of processing. Radial velocity measurements are obtained from individual radar sites through the U.S. HF-Radar Network. Hourly radial data are processed by unweighted least-squares on a 6 km resolution grid of the U.S. West Coast to produce near real-time surface current maps.Surface ocean velocities estimated from HF-Radar are representative of the upper 0.3 - 2.5 meters of the ocean. The main objective of near-real time processing is to produce the best product from available data at the time of processing. Radial velocity measurements are obtained from individual radar sites through the U.S. HF-Radar Network. Hourly radial data are processed by unweighted least-squares on a 6 km resolution grid of the U.S. West Coast to produce near real-time surface current maps.Surface ocean velocities estimated from HF-Radar are representative of the upper 0.3 - 2.5 meters of the ocean. The main objective of near-real time processing is to produce the best product from available data at the time of processing. Radial velocity measurements are obtained from individual radar sites through the U.S. HF-Radar Network. Hourly radial data are processed by unweighted least-squares on a 6 km resolution grid of the U.S. West Coast to produce near real-time surface current maps.

Annual and growing-season weather data and expanded description of methods for flux measurements, chamber volume estimation, and CO2-balance calculations. The appendix also contains nine supplementary figures (pictures and a map of the field site, soil temperature, thaw depth, monthly fluxes, ANPP, NDVI, water table depth) and five tables (statistical results and summaries of warming effects on environmental variables, monthly fluxes, biomass/ANPP/canopy N, and model parameters).

Surface ocean velocities estimated from HF-Radar (HFR) are representative of the upper 0.3 - 2.5 meters of the ocean. The main objective of near-real time processing is to produce the best product from available data at the time of processing. Radial velocity measurements are obtained from individual radar sites through the U.S. HF-Radar Network. Hourly radial data are processed by unweighted least-squares on a 1 km resolution grid of Hawaii to produce near real-time surface current maps.

The reported soil temperature profile measurements (24 locations - 2 probes with 5 and 6 thermistors, respectively - Fig. 1 and Fig. 2) were initiated as part of a soil micro-warming experiment at the Council Road Mile Marker 71 Site (CN_MM71) in September 2017. From 2017 through August 2019, these were measurements of ambient pre-treatment plot conditions. This tussock tundra site (with underlying permafrost) experiences annual frost heaving that causes a vertical movement of the ground surface, hence causing some of the upper most temperature thermistors to be at surface level or above ground and recorded therefore air temperatures near the surface and not below ground soil temperature (see section on Quality Assurance). After August 2019, these measurements ended in preparation for transitioning to the experimental warming of individual plots. The reported temperature data are nominally 3-hour averages of measurements made at varying frequencies (3-hour maximum) with frequencies that depended upon power (solar) availability to operate the sensors (see section in documentation on Methods). The number of values and the standard deviation for each 3-hour average (where appropriate) are also provided. These measurements are located near the NGEE-Arctic CO2 and CH4 eddy covariance tower at the Council Road Site (US-NGC: NGEE Arctic Council, https://ameriflux.lbl.gov/sites/siteinfo/US-NGC#overview) and auxiliary data at https://doi.org/10.5440/1526749. This dataset contains four *.csv files and one *.pdf file. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

The Hawaii Ocean Time-series (HOT) program makes repeated observations of the physics, biology and chemistry at a site approximately 100 km north of Oahu, Hawaii. Two stations are visited about once a month: Kahe Point (Station 1: 21.34N, 158.27W) and Station ALOHA (Station 2: 22.75N, 158W). Various other stations are made intermittently in support of similar research objectives or mooring deployments.

This NODC Accession contains Carbon Assimilation data consisting of Primary Production and Sediment Trap Particle Flux measurements and calculations during HOT cruises 1-227 occurring in 1988-2010. These data are only taken at Station ALOHA. There are over a dozen cruises without data. Files are organized on a yearly basis of each type.

In separate NODC accessions, there are Water Column Chemical data (JGOFS parameters), CTD, Niskin bottle, and thermosalinograph data sets over HOT cruises 1-227 for Station Aloha and other stations and during transit.

Surface ocean velocities estimated from HF-Radar (HFR) are representative of the upper 0.3 - 2.5 meters of the ocean. The main objective of near-real time processing is to produce the best product from available data at the time of processing. Radial velocity measurements are obtained from individual radar sites through the U.S. HF-Radar Network. Hourly radial data are processed by unweighted least-squares on a 6 km resolution grid of Hawaii to produce near real-time surface current maps.

This part of DS 781 presents data for the faults for the geologic and geomorphic map of the Offshore of Monterey map area, California. The vector data file is included in "Faults_OffshoreMonterey.zip," which is accessible from http://dx.doi.org/10.3133/ofr20161110. The shelf north and east of the Monterey Bay Peninsula in the Offshore of Monterey map area is cut by a diffuse zone of northwest striking, steeply dipping to vertical faults comprising the Monterey Bay Fault Zone (MBFZ). This zone, originally mapped by Greene (1977, 1990), extends about 45 km across Monterey Bay (Map E on sheet 9). Fault strands within the MBFZ are mapped with high-resolution seismic-reflection profiles (sheet 8). Seismic-reflection profiles traversing this diffuse zone in the map area cross as many as 5 faults over a width of about 4 to 5 km (see, for example, figs. 3 and 5 on sheet 8). The zone lacks a continuous "master fault," along which deformation is concentrated. Fault length ranges up to about 20 km (based on mapping outside this map area), but most strands are only about 2- to 7-km long. Faults in this diffuse zone cut through Neogene bedrock and locally appear to minimally disrupt overlying inferred Quaternary sediments. The presence of warped reflections along some fault strands suggests that fault offsets may be both vertical and strike-slip. Specific offshore faults within the zone that are continuous with mapped onshore faults include the Navy Fault, Chupines Fault, and Ord Terrace Fault (Clark and others, 1997; Wagner and others, 2002). Carmel Canyon, a relatively straight northwest-trending arm of the Monterey Canyon system, extends through the southwestern part of the Offshore of Monterey map area. Carmel Canyon has three heads (Greene and others, 2002), two of which extend east and northeast into Carmel Bay within the map area; the third head extends southeast along the main canyon trend for about 3 km beyond the confluence with the heads in Carmel Bay. Carmel Canyon is aligned with and structurally controlled by the San Gregorio fault zone (Greene and others, 1991), an important structure in the distributed transform boundary between the North American and Pacific plates (see, for example, Dickinson and others, 2005). This Fault Zone is part of a regional fault system that is present predominantly in the offshore for about 400 km, from Point Conception in the south (where it is known as the Hosgri Fault; Johnson and Watt, 2012) to Bolinas and Point Reyes in the north (Bruns and others, 2002; Ryan and others, 2008). The San Gregorio Fault Zone in the map area is part of a 90-km-long offshore segment that extends northward from Point Sur (about 24 km south of the map area), across outer Monterey Bay to Point Año Nuevo (51 km north of the map area) (see sheet 9; see also, Weber and Lajoie, 1980; Brabb and others, 1998; Wagner and others, 2002). High-resolution seismic-reflection data collected across the canyon do not clearly image the San Gregorio Fault Zone, due largely to significant depth and steep canyon walls. Accordingly, we have mapped the 1,000- 1,300-m-wide fault zone largely on the presence of prominent, lengthy, geomorphic lineaments (sheets 1 and 2) and both geomorphic and lithologic contrasts across the fault. Faults were primarily mapped by interpretation of seismic reflection profile data (see OFR 2013-1071). The seismic reflection profiles were collected between 2007 and 2010. References Cited Bruns, T.R., Cooper, A.K., Carlson, P.R., and McCulloch, D.S., 2002, Structure of the submerged San Andreas and San Gregorio Fault zones in the Gulf of Farallones as inferred from high-resolution seismic-reflection data, in Parsons, T., ed., Crustal structure of the coastal and marine San Francisco Bay region, California: U.S. Geological Survey Professional Paper 1658, p. 77–117, available at http://pubs.usgs.gov/pp/1658/. Brabb, E.E., 1997, Geologic Map of Santa Cruz County, California: A digital database, US Geological Survey Open-File Report 97–489, 1:62,500. Clark, J.C., Dupre, W.R., and Rosenberg, L.L., 1997, Geologic map of the Monterey and Seaside 7.5–minute quadrangles, Monterey County, California–A digital database: U.S. Geological Survey Open-File Report 97-30, 2 sheets, scale 1:24,000, http://pubs.usgs.gov/of/1997/of97-030/ Dickinson, W.R., Ducea, M., Rosenberg, L.I., Greene, H.G., Graham, S.A., Clark, J.C., Weber, G.E., Kidder, S., Ernst, W.G., and Brabb, E.E., 2005, Net dextral slip, Neogene San Gregorio-Hosgri fault zone, coastal California: Geologic evidence and tectonic implications: Geological Society of America Special Paper 391, 43 p. Greene, H.G., Maher, N.M., and Paull, C.K., 2002, Physiography of the Monterey Bay National Marine Sanctuary and implications about continental margin development: Marine Geology, v. 181, p. 55–82. Greene, H.G., Clarke, S.H. and Kennedy, M.P., 1991. Tectonic Evolution of Submarine Canyons Along the California Continental Margin. From Shoreline to Abyss, in Osborne, R.H., ed., Society for Sedimentary Geology, Special Publication No. 46, p. 231–248. Greene, H.G., 1990, Regional tectonics and structural evolution of the Monterey Bay region, central California, in Garrison, R.E., Greene, H.G., Hicks, K.R., Weber, G.E., and Wright, T.L., eds., Geology and tectonics of the central California coastal region, San Francisco to Monterey: American Association of Petroleum Geologists, Pacific Section, Guidebook GB67, p. 31–56. Greene, H.G., 1977, Geology of the Monterey Bay region: U.S. Geological Survey Open-File Report 77–718, 347 p. Greene, H.G., 1990, Regional tectonics and structural evolution of the Monterey Bay region, central California, in Garrison, R.E., Greene, H.G., Hicks, K.R., Weber, G.E., and Wright, T.L., eds., Geology and tectonics of the central California coastal region, San Francisco to Monterey, Pacific Section American Association of Petroleum Geologists, Guidebook GB-67, p. 31–56. Johnson, S.Y., and Watt, J.T., 2012, Influence of fault trend, bends, and convergence on shallow structure and geomorphology of the Hosgri strike-slip fault, offshore Central California: Geosphere, v. 8, p. 1,632–1,656, doi:10.1130/GES00830.1. Ryan, H.F., Parsons, T., and Sliter, R.W., 2008. Vertical tectonic deformation associated with the San Andreas fault zone offshore of San Francisco, California: Tectonophysics, v. 429, p. 209–224, doi:10.1016/j.tecto.2008.06.011. Wagner, D.L., Greene, H.G., Saucedo, G.J., and Pridmore, C.L., 2002, Geologic Map of the Monterey 30' x 60' quadrangle and adjacent areas, California: California Geological Survey Regional Geologic Map Series, scale 1:100,000. Weber, G.E., and Lajoie, K.R., 1980, Map of Quaternary faulting along the San Gregorio fault zone, San Mateo and Santa Cruz Counties, California: U.S. Geological Survey Open-File Report 80–907, 3 sheets, scale 1:24,000, available at http://pubs.er.usgs.gov/publication/ofr80907.

Meteorological data are currently being collected at one location at the Teller Mile 47 (TL_MM47) Research Basin Site, Seward Peninsula (N64 58' 36.918", W166 12' 32.67", 67 meters above sea level). The site was installed and initial measurements started in September 2018 and it has operated continuously since then. The meteorological station is co-located with a continuous snow depth sensor and two soil pits for subsurface temperature and moisture measurements.These data are being collected to better understand the energy dynamics above the active layer and permafrost. They complement in-situ snow and soil measurements also at this location. The data could also be used as supporting measurements for other research and modeling activities.There are 35 comma separated value format (*.csv) files provided, where each file contains the full data for an individual parameter (e.g. air temperature at 1.5 meters above the ground surface (teller_m47_air_temperature_150cm_ags_Avg.csv) or soil temperature 20 centimeters below ground surface (teller_m47_dry_soil_pit_temperature_20cmbgs_Avg.csv)) plus the time in Universal Coordinated Time (UTC) and Alaska Standard Time (UTC time minus nine hours).The site was installed and initial measurements started in September 2018. It has been operated continuously since. Primary data gaps are due to battery failure or sensor failure. These data are being collected to better understand the surface energy dynamics above the active layer and permafrost.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 10-year research effort (2012-2022) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy?s Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy?s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).