This point shapefile contains information on 476 locations surveyed using a single-base real-time kinematic (RTK) global navigation satellite system (GNSS) in Soldier Meadows, Black Rock Desert - High Rock Canyon Emigrant Trails National Conservation Area, Nevada, August 14-15, 2019. The points were collected at 30-second intervals at control points and hydraulic structures and 5-second intervals at topographic points throughout the study area. The points were used as vertical precision verification for lidar data, editing the triangulated irregular network in locations of dense vegetation and surface water, locating streamflow measurement sites, creating hydraulic structures in the hydraulic model, and determining the elevation of possible high-water marks in the natural channel.

This point shapefile contains information on one static reference location collected using three single-baseline online positioning user service – static (OPUS-S) global navigation satellite system (GNSS) surveys in Soldier Meadows, Black Rock Desert - High Rock Canyon Emigrant Trails National Conservation Area, Nevada, August 13-15, 2019. Surveys were completed at one temporary benchmark, TBM1. Data were collected by a Leica Viva GS14 GNSS. Processing of static observations was done using the National Geodetic Survey (NGS) online positioning user system (OPUS).

A digital elevation model represented by a triangulated irregular network (TIN) was developed for proposed channel restoration at Soldier Meadows, Black Rock Desert - High Rock Canyon Emigrant Trails National Conservation Area, Nevada. The TIN was derived from lidar (light imaging, detection, and ranging) of quality level 1 collected in April 2018 by Quantum Spatial (Quantum Spatial Inc, 2018) for the Bureau of Land Management. The DEM also includes points surveyed in August 13-16, 2019, using a real-time kinematic (RTK) global navigation satellite system (GNSS). The lidar data are not included in this USGS publication due to BLM data-release restrictions for this dataset. Contact Bureau of Land Management, Nevada, Winnemucca District office for more information.

This point shapefile contains positional data for 2,205 locations at the Muddy River, near Moapa, Nevada, April 1 to August 9, 2019. Positional data were collected using either a single-base real-time kinematic (RTK) global navigation satellite system (GNSS) or a total station. The survey data primarily were used to define 105 cross-sections, with a secondary use as vertical precision verification for lidar data.

This point shapefile contains positional data for 2,205 locations at the Muddy River, near Moapa, Nevada, April 1 to August 9, 2019. Positional data were collected using either a single-base real-time kinematic (RTK) global navigation satellite system (GNSS) or a total station. The survey data primarily were used to define 105 cross-sections, with a secondary use as vertical precision verification for lidar data.

The USGS, in cooperation with the U.S. Bureau of Land Management (BLM), created a series of geospatial mapping products of the Scotts Creek Watershed in Lake County, California, using National Agriculture Imagery Program (NAIP) imagery from 2018, 2020 and 2022 and Open Street Map (OSM) from 2019. The imagery was downloaded from United States Department of Agriculture (USDA) - Natural Resources Conservation Service (NRCS) Geospatial Data Gateway (https://datagateway.nrcs.usda.gov/) and Geofabrik GmbH - Open Street Map (https://www.geofabrik.de/geofabrik/openstreetmap.html), respectively. The imagery was classified using Random Forest (RF) Modeling to produce land cover maps with three main classifications - bare, vegetation, and shadows. An updated roads and trails map for the Upper Scotts Creek Watershed, including the BLM Recreational Area, was created to estimate road and trail densities in the watershed. Separate metadata records for each product (Land_Cover_Maps_Scotts_Creek_Watershed_CA_2018_2020_2022_metadata.xml, and Roads_and_Trails_Map_Upper_Scotts_Creek_Watershed_CA _2022_metadata.xml) are provided on the ScienceBase page for each child item. Users should be aware of the inherent errors in remote sensing products.