Filters: Tags: GPS (X) > partyWithName: U.S. Geological Survey (X)
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A train derailment occurred in Marana, Arizona, on July 10, 2018. Runoff from a severe thunderstorm was flowing over the tracks at the time and may have contributed to the derailment. At the request of the Pima County Regional Flood Control District, USGS collected high-water marks for the flood event upstream from the derailment area.
These are terrestrial laser scanner datasets collected in forested areas west of Flagstaff, Arizona in 2015 and 2016. For each of the two scanners, six treatment areas were scanned, with four of them overlapping one another (Figure 1). These data are composed of individual scans referenced to one another using reflective targets, and geolocated using differentially corrected GPS and RTK locations of scan locations (Figure 3). There were overall large differences in point density among the two scanners (Figure 2).
The dataset consists of a slope-area computation of peak discharge (published via NWIS), stage data from continuous slope-area (CSA) sensors, CSA computations of discharge, verified Manning's roughness coefficients (n), channel geometry and reach properties associated with Manning's n computations, and GPS survey data associated with the flow event on July 28, 2017, at 09471143 - Walnut Gulch below ARS Flume 6, near Tombstone, AZ.
River bathymetry measurements were collected in 2017 and 2018 along the Willamette River, Oregon, between Eugene and Newberg. These data were collected to complement a bathymetric lidar dataset collected in 2017 for the same section of river. In many deeper segments of the river channel, bathymetric lidar did not produce measurements of river bathymetry. To fill gaps in the bathymetric lidar dataset, USGS combined bathymetry data previously collected in 2015 and 2016 with newly collected survey data from 2017 and 2018. The bathymetric survey data acquired in 2017 and 2018 focused on filling gaps within the 2017 bathymetric lidar dataset. Bathymetry data were collected using a network based real time kinematic global...
Studies utilizing Global Positioning System (GPS) telemetry rarely result in 100% fix success rates (FSR). Many assessments of wildlife resource use do not account for missing data, either assuming data loss is random or because a lack of practical treatment for systematic data loss. Several studies have explored how the environment, technological features, and animal behavior influence rates of missing data in GPS telemetry, but previous spatially explicit models developed to correct for sampling bias have been specified to small study areas, on a small range of data loss, or to be species-specific, limiting their general utility. Here we explore environmental effects on GPS fix acquisition rates across a wide...
The dataset contains GPS survey data collected at Colorado River at Salt Wash near Moab, UT, as part of a surface velocity mapping effort. The survey was conducted on October 6, 2020, and documents ground control points for a small unmanned aircraft system (sUAS) survey. The survey was performed using Leica GS14 RTK GPS equipment, S/N base-2806898, S/N rover-2806883.
Capture, GPS-collar tagging, and release of cougars was conducted in northern Arizona and southern Utah and Nevada, USA, from 2003 to 2013 by the U.S. Geological Survey and the National Park Service (Northern Arizona University IACUC Protocol # 02-082-R4), resulting in GPS-tracking and monitoring of study animal activities. This data set includes six individuals that met three criteria: 1) few missing data (≥ 85% fix success rate), 2) long periods of continuous monitoring, with a minimum of 1000 observations, and 3) established home range with no evidence of dispersal. It includes four females (C04, AS02, P26, and C07) and two males (Z04 and AS07), ranging in age from 1.5 – 4 years in age. Two females (C04 and AS02)...
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