Light Detection and Ranging (LiDAR) datasets for Sunset Crater Volcano National Monument. LiDAR data over Sunset Crater Volcano National Monument include Bare Earth Model, DEM, Highest Hit Model, Intensity Images, and LAS datasets. These data were collected as a project for the NPS in the Sunset Crater Volcano National Monument site in the fall of 2012. The Sunset Crater Volcano National Monument LiDAR project consisted of acquisition, post-processing, classification of LiDAR data and creation of final deliverable products. The goal of the project was to provide high accuracy bare-earth processed data suitable for the project area. All areas were collected with a Leica ALS50 Phase II mounted in a Cessna Caravan. There was an average pulse density of greater than or equal to 8 pulses/m squared over the Sunset Crater LiDAR terrain. All areas were surveyed with an opposing flight line side-lap of greater than or equal to 50 percent, a 100 percent overlap, to reduce laser shadowing and increase surface laser painting. The Leica laser systems record up to four range measurements, returns, per pulse. All discernible laser returns were processed for the output dataset. To accurately solve for laser point position, the geographic coordinates w, y, z, the positional coordinates of the airborne sensor and the attitude of the aircraft were recorded continuously throughout the LiDAR data collection mission. Position of the aircraft was recorded continuously throughout the LiDAR data collection mission. Position of the aircraft was measured twice per second (2Hz) by an onboard differential GPS unit. Aircraft attitude was measured 200 times per second (200Hz) as pitch, roll, and yaw (heading) from an onboard inertial measurement unit (IMU). To allow for post-processing correction and calibration, aircraft/sensor position and attitude data are indexed by GPS time. The data was processed in the office using a suite of automated and manual techniques to process the data into the requested deliverables. Processing tasks included GPS control computations, kinematic corrections, calculation of laser point position, calibration for optimal relative and absolute accuracy, and classification of ground and non-ground points. The full details can be found in the report attached as a digital holding.

This Lidar was collected for the National Park Service because they require a high-resolution digital elevation model to serve as a base layer for further inventory and monitoring of Sunset Crater Volcano's unique resources. The objective of this procurement was to acquire a high-resolution bare-earth digital elevation models (DEM) of SUCR and adjacent areas around the park. The accuracy of the final DEM is an interval ranging from 0.15 meter to 0.50 meter. The lidar survey was accomplished with a Leica ALS50 Phase II mounted in a Cessna Caravan with an average yield pulse density of 8 pulses/m2 over the Sunset Crater Lidar terrain. Project Site: Sunset Crater National Monument which is located in Coconino County Arizona; Acres of Lidar collected 10,233; Date of Acquisition 09/16/2012; Lidar Format LAS v 1.2.

These data were converted from the originally delivered Microsoft Access PLOTs database from the Vegetation Mapping Inventory Project of Sunset Crater Volcano National Monument. These comma-delimited data tables contain(s) vegetation mapping plot classification and accuracy assessment data, as well as summary information about the data itself. If a table is empty, then it was empty in the original database.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. Four basic elements were used to create the SUCR vegetation map: 1) map class development, 2) aerial photography interpretation, 3) digital transfer, and 4) map validation. Following these steps, a formal accuracy assessment determined errors of omission and commission with the goal of achieving a minimum of 80% map accuracy. An ArcInfo GIS database was built for SUCR using in-house protocols for creating vegetation GIS databases. The protocols consist of a shell of Arc Macro Language (AML) scripts and menus that automate the transfer process and insure that all spatial and attribute data are consistent and stored properly. We modified the map classes as a result of field verification and used the modified classes in the final photointerpretation. The final map revision was completed in September 2002.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. Four basic elements were used to create the SUCR vegetation map: 1) map class development, 2) aerial photography interpretation, 3) digital transfer, and 4) map validation. Following these steps, a formal accuracy assessment determined errors of omission and commission with the goal of achieving a minimum of 80% map accuracy. An ArcInfo GIS database was built for SUCR using in-house protocols for creating vegetation GIS databases. The protocols consist of a shell of Arc Macro Language (AML) scripts and menus that automate the transfer process and insure that all spatial and attribute data are consistent and stored properly. We modified the map classes as a result of field verification and used the modified classes in the final photointerpretation. The final map revision was completed in September 2002.

These ESRI shape files are of National Park Service tract and boundary data that was created by the Land Resources Division. Tracts are numbered and created by the regional cartographic staff at the Land Resources Program Centers and are associated to the Land Status Maps. This data should be used to display properties that NPS owns and properties that NPS may have some type of interest such as scenic easements or right of ways.

This data set contains small-scale base GIS data layers compiled by the National Park Service Servicewide Inventory and Monitoring Program and Water Resources Division for use in a Baseline Water Quality Data Inventory and Analysis Report that was prepared for the park. The report presents the results of surface water quality data retrievals for the park from six of the United States Environmental Protection Agency's (EPA) national databases: (1) Storage and Retrieval (STORET) water quality database management system; (2) River Reach File (RF3) Hydrography; (3) Industrial Facilities Discharges; (4) Drinking Water Supplies; (5) Water Gages; and (6) Water Impoundments. The small-scale GIS data layers were used to prepare the maps included in the report that depict the locations of water quality monitoring stations, industrial discharges, drinking intakes, water gages, and water impoundments. The data layers included in the maps (and this dataset) vary depending on availability, but generally include roads, hydrography, political boundaries, USGS 7.5' minute quadrangle outlines, hydrologic units, trails, and others as appropriate. The scales of each layer vary depending on data source but are generally 1:100,000.

This lidar dataset was collected as part of an NCALM Seed grant for Thomas Herbst at the University of Missouri. This project explored Lava Domes, and mapped a portion of the Lassen Volcanic Center in Lassen Volcanic National Park, California. The dataset was collected in 2019 and covers roughly 55 km 2

This reference contains the imagery data used in the completion of the baseline vegetation inventory project for the NPS park unit. Orthophotos, raw imagery, and scanned aerial photos are common files held here. Aerial photography covering the entire project area was received by RSGIG from USGS/BRD. The color infrared (CIR) photographs were acquired on October 8, 1996 by Merrick, & Company, Aurora, Colorado, and were taken at 1:12,000 (1inch=1,000 feet) scale. Hardcopies of the photographs were provided as 9 inch x 9 inch diapositives. Overlap for these photos averaged approximately 50-60% and sidelap between flight lines is approximately 30-40%. The base maps, standard USGS digital orthophoto quarter quads (DOQQs) for geo-referencing or registration of delineated map classes were created from aerial photographs flown in October 1997. These maps are grayscale, with 1 meter per pixel resolution, UTM coordinate system, and NAD83 datum.

These data were compiled for Cabeza Prieta National Wildlife Refuge (CPNWR) in southern Arizona, to support managment efforts of water resources and wildlife conservation. Objective(s) of our study were to 1) measure water storage capacity at select stage heights in three tanks (also termed tinajas), 2) build a stage storage model to help CPNWR staff accurately estimate water volumes throughout the year, and 3) collect topographic data adjacent to the tanks as a means to help connect these survey data to past or future work. These data represent high-resolution (sub-meter) ground based lidar measurements used to meet these objectives and are provided as: processed lidar files (point clouds), rasters (digital elevation models), and vectors (shapefiles). These data were collected in Southern Arizona at Buckhorn, Eagle, and Senita tanks in the CPNWR from February 13-18, 2022. These data were collected by U.S. Geological Survey - Southwest Biological Science Center - Grand Canyon Monitoring and Research Center (GCMRC) staff for the CPNWR using a Riegl VZ 1000 ground-based lidar to produces ground elevation models georeferenced using control target coordinates collected by a Trimble real-time kinematic (RTK) rover and base station. These data which represent maximum water storage capacity at Buckhorn, Eagle and Senita tanks following sediment removal by CPNWR staff less than one month prior can be used to support management efforts for water resources at these tanks, and wildlife conservation in the CPNWR. Additionally, these data can be used as baseline conditions for evaluating changes in water storage and water storage capacity.