This dataset is about books. It has 1 row and is filtered where the book publisher is Utah State University Press, An imprint of University Press of Colorado. It features 7 columns including author, publication date, language, and book publisher.

The bryophyte collection of the Intermountain Herbarium consists largely of duplicates from Seville Flowers, William A. Weber, and Leila M. Shultz. It has started to grow, albeit slowly, mostly with additions from northern Utah.

Financial overview and grant giving statistics of Utah State University

Mainly focused on development of loss of life models.

Explore the progression of average salaries for graduates in Utah State University from 2020 to 2023 through this detailed chart. It compares these figures against the national average for all graduates, offering a comprehensive look at the earning potential of Utah State University relative to other fields. This data is essential for students assessing the return on investment of their education in Utah State University, providing a clear picture of financial prospects post-graduation.

Every four years, the Wasatch Front’s two metropolitan planning organizations (MPOs), Wasatch Front Regional Council (WFRC) and Mountainland Association of Governments (MAG), collaborate to update a set of annual small area -- traffic analysis zone and ‘city area’, see descriptions below) -- population and employment projections for the Salt Lake City-West Valley City (WFRC), Ogden-Layton (WFRC), and Provo-Orem (MAG) urbanized areas.

These projections are primarily developed for the purpose of informing long-range transportation infrastructure and services planning done as part of the 4 year Regional Transportation Plan update cycle, as well as Utah’s Unified Transportation Plan, 2023-2050. Accordingly, the foundation for these projections is largely data describing existing conditions for a 2019 base year, the first year of the latest RTP process. The projections are included in the official travel models, which are publicly released at the conclusion of the RTP process.

Projections within the Wasatch Front urban area ( SUBAREAID = 1) were produced with using the Real Estate Market Model as described below. Socioeconomic forecasts produced for Cache MPO (Cache County, SUBAREAID = 2), Dixie MPO (Washington County, SUBAREAID = 3), Summit County (SUBAREAID = 4), and UDOT (other areas of the state, SUBAREAID = 0) all adhere to the University of Utah Gardner Policy Institute's county-level projection controls, but other modeling methods are used to arrive at the TAZ-level forecasts for these areas.

As these projections may be a valuable input to other analyses, this dataset is made available here as a public service for informational purposes only. It is solely the responsibility of the end user to determine the appropriate use of this dataset for other purposes.

Wasatch Front Real Estate Market Model (REMM) Projections

WFRC and MAG have developed a spatial statistical model using the UrbanSim modeling platform to assist in producing these annual projections. This model is called the Real Estate Market Model, or REMM for short. REMM is used for the urban portion of Weber, Davis, Salt Lake, and Utah counties. REMM relies on extensive inputs to simulate future development activity across the greater urbanized region. Key inputs to REMM include:

Demographic data from the decennial census
County-level population and employment projections -- used as REMM control totals -- are produced by the University of Utah’s Kem C. Gardner Policy Institute (GPI) funded by the Utah State Legislature
Current employment locational patterns derived from the Utah Department of Workforce Services
Land use visioning exercises and feedback, especially in regard to planned urban and local center development, with city and county elected officials and staff
Current land use and valuation GIS-based parcel data stewarded by County Assessors
Traffic patterns and transit service from the regional Travel Demand Model that together form the landscape of regional accessibility to workplaces and other destinations
Calibration of model variables to balance the fit of current conditions and dynamics at the county and regional level

‘Traffic Analysis Zone’ Projections

The annual projections are forecasted for each of the Wasatch Front’s 3,546 Traffic Analysis Zone (TAZ) geographic units. TAZ boundaries are set along roads, streams, and other physical features and average about 600 acres (0.94 square miles). TAZ sizes vary, with some TAZs in the densest areas representing only a single city block (25 acres).

‘City Area’ Projections

The TAZ-level output from the model is also available for ‘city areas’ that sum the projections for the TAZ geographies that roughly align with each city’s current boundary. As TAZs do not align perfectly with current city boundaries, the ‘city area’ summaries are not projections specific to a current or future city boundary, but the ‘city area’ summaries may be suitable surrogates or starting points upon which to base city-specific projections.

Summary Variables in the Datasets

Annual projection counts are available for the following variables (please read Key Exclusions note below):

Demographics

Household Population Count (excludes persons living in group quarters) 
Household Count (excludes group quarters) 

Employment

Typical Job Count (includes job types that exhibit typical commuting and other travel/vehicle use patterns)
Retail Job Count (retail, food service, hotels, etc)
Office Job Count (office, health care, government, education, etc)
Industrial Job Count (manufacturing, wholesale, transport, etc)
Non-Typical Job Count* (includes agriculture, construction, mining, and home-based jobs) This can be calculated by subtracting Typical Job Count from All Employment Count 
All Employment Count* (all jobs, this sums jobs from typical and non-typical sectors).

• These variables includes REMM’s attempt to estimate construction jobs in areas that experience new and re-development activity. Areas may see short-term fluctuations in Non-Typical and All Employment counts due to the temporary location of construction jobs.

Key Exclusions from TAZ and ‘City Area’ Projections

As the primary purpose for the development of these population and employment projections is to model future travel in the region, REMM-based projections do not include population or households that reside in group quarters (prisons, senior centers, dormitories, etc), as residents of these facilities typically have a very low impact on regional travel. USTM-based projections also excludes group quarter populations. Group quarters population estimates are available at the county-level from GPI and at various sub-county geographies from the Census Bureau.

Statewide Projections

Population and employment projections for the Wasatch Front area can be combined with those developed by Dixie MPO (St. George area), Cache MPO (Logan area), and the Utah Department of Transportation (for the remainder of the state) into one database for use in the Utah Statewide Travel Model (USTM). While projections for the areas outside of the Wasatch Front use different forecasting methods, they contain the same summary-level population and employment projections making similar TAZ and ‘City Area’ data available statewide. WFRC plans, in the near future, to add additional areas to these projections datasets by including the projections from the USTM model.

This dataset tracks annual white student percentage from 2014 to 2023 for Weber State University Charter Academy vs. Utah and Weber State University Charter Academy School District

Uncover historical ownership history and changes over time by performing a reverse Whois lookup for the company Utah-State-University.

This dataset tracks annual hispanic student percentage from 2014 to 2022 for Weber State University Charter Academy vs. Utah and Weber State University Charter Academy School District

Researchers at Utah State University created a short survey instrument to gather information about the views and concerns of Utah residents related to water issues. This survey was designed to give the public a chance to share their perceptions and concerns about water supply, water quality, and other related issues. While finding out what the ‘average citizen’ feels about key water issues was one goal of the project, the most interesting and important results are found in exploring ways in which perspectives about water vary across the population based on where people live and their demographic background (gender, age, education, etc.). This survey helps bring a voice to groups of citizens typically not represented in water policy debates. The findings have been and continue to be shared with water managers and decision makers who are planning for local and state water system sustainability.

This survey effort is also a key outreach and education component of the iUTAH project. High school groups, college and university classes, and others are invited to collaborate with iUTAH faculty to conduct public intercept surveys. Co-collection and analysis of survey data provides a hands-on learning opportunity about the principles of social science research. This effort helps increase awareness about the complexity of water issues in Utah, and the methods through which scientists learn about the public’s thoughts and concerns. Between July 2014 and April 2016, the survey has been implemented with collaborating students and faculty from the University of Utah, Utah Valley University, Weber State University, Salt Lake Community College, Southern Utah University, Dixie State University, and Snow College.

The survey involved using a structured protocol to randomly approach adults entering grocery stores in communities across the state, and inviting them to complete a 3-minute questionnaire about thier perceptions and concerns about water issues in Utah. The survey was self-administered on an iPad tablet and uploaded to a web server using the Qualtrics Offline App.

The project generated responses from over 7,000 adults, with a response rate of just over 42% . Comparisons of the respondents with census data suggest that they are largely representative of the communities where data were collected and of the state's adult population.

The data are anonymous and are available as a public dataset here. The data also served as the basis for the development of an open-source web-based survey data viewer that can be found at: http://data.iutahepscor.org/surveys/ and were also reported in Jones et al. (2016). We encourage users to use the viewer to explore the survey results.

The files below include a document describing in detail the method/protocol used in the study, and copies of field materials we used to implement the project. We also include copies of the full dataset and a codebook in various formats.

Utah FORGE phase 2C Native State Simulation zip contains the data used for the boundary conditions and subsequent native state simulation results obtained using the simulation code FALCON. Data are from the nodes of the simulation domain, with used a uniform 50m spacing over a 2500 X 2500 X 2750m domain approximately centered on the FORGE footprint. There is also a read me text file, that is included, containing metadata. The Reservoir Porosity and Upscale DFN Permeability zip contains the data used for the spatial distribution of the anisotropic permeability and porosity used in the native state simulation of the Utah FORGE site. Please contact Robert Podgorney at the Idaho National Laboratory with questions, robert.podgorney@inl.gov. There is also a read me text file included containing metadata.

Financial overview and grant giving statistics of Utah State University Space Dynamics Laboratory

The Measurement Infrastructure Gap Analysis in Utah’s Great Salt Lake Basin was a comprehensive inventory and analysis of existing diversion and stream measurement infrastructure along 19 primary river systems, as well as a preliminary investigation of measurement infrastructure gaps around Great Salt Lake proper. The purpose of this “Gap Analysis” was to develop methods to identify and prioritize areas throughout the Great Salt Lake basin where new or updated measurement infrastructure is needed to serve diverse objectives. The following gaps were identified: (1) existing measurement infrastructure quality and completeness gaps, (2) stakeholder identified gaps, and (3) potential spatial gaps in hydrologic understanding. By adapting the prioritization schema originally presented in the Colorado River Metering and Gaging and Gap Analysis to equally weight these three gap types at the HUC12 scale, a flexible framework for prioritizing new or updated measurement infrastructure in areas with large cumulative measurement gaps was developed, and high, medium, and low priority HUC12s were identified.

Results showed that 250 diversion and 28 stream measurement devices along primary systems had at least one quality and/or completeness gap. The most common quality and completeness gaps were insufficient device types, lack of telemetry, and data record interval. Stakeholders suggested 50 instances of new or updated diversion measurement infrastructure, 95 instances of new or updated stream measurement infrastructure, and 39 recommendations for continued funding of existing measurement infrastructure—totaling 185 stakeholder-identified gaps. To provide a spatially consistent approach to identifying potential gaps in hydrologic understanding, geospatial datasets describing features or attributes that can impact local hydrology were used to identify measurement gaps at the HUC12 scale. Among HUC12s that overlapped with the river systems included in this analysis, HUC12s with the greatest number of potential spatial gaps were in the Bear River sub-basin and near reservoirs in the Weber River sub-basin.

Based on the prioritization schema applied to synthesize these three gap types, there were 52 HUC12s along primary systems classified as high priority for measurement improvement. Of the 250 existing diversion and 28 stream measurement devices with at least one quality and/or completeness gap, 217 and 10 devices, respectively, were located within high priority HUC12s. Most stakeholder-identified gaps identified in the Weber and Jordan River sub-basins also fell within high-priority HUCs. Eighteen unique agencies suggested new or updated measurement infrastructure or continued funding of existing measurement infrastructure in high-priority HUC12s, demonstrating some consensus regarding measurement gaps in critical areas. There were 6 high priority HUC12s with no existing measurement infrastructure quality and completeness gaps, and 11 high priority HUC12s with no stakeholder-identified gaps. High priority HUC12s highlighted only due to potential spatial gaps may warrant additional investigation to further understand potential measurement gaps in these HUC12s.

Because the prioritization schema applied equally weighted all three gap types, it likely does not fully represent the diverse missions and priorities of different stakeholder groups. To facilitate an adaptable approach to prioritize measurement gaps within the Great Salt Lake basin, raw data for each of the three gap types are provided to allow varied prioritization schemes to be developed by weighting gap types differently or considering subsets of data. These data provide the basis for stakeholders within the Great Salt Lake basin to collectively prioritize future investments in gaging infrastructure and better manage water throughout the Great Salt Lake basin.

The geographic focus of the Intermountain Herbarium is the area between the Sierra Nevada and the Rocky Mountains. The fungal collection includes both macrofungi and plant pathogens. Most of the macrofungi are from northern Utah. Dr. Bradley R. Kropp is Curator of Fungi. The herbarium's Assistant Curator, Michael B. Piep, is also a mycologist.

The geographic focus of the Intermountain Herbarium is the area between the Sierra Nevada and the Rocky Mountains but the lichen collection is currently growing most rapidly through research led by Dr. Bradley R. Kropp on the lichens of Wyoming growing on BLM land.

This dataset contains qualitative social science data collected at Weber State University, as part of the social science research focus area of iUTAH. Data were collected through nine focus groups and seven face-to-face interviews, all conducted with diverse WSU stakeholders. The dataset is comprised of summary reports from the focus groups and interviews.

This data represents remote habitat surveys that were performed throughout Nevada in order to assist in the status assessment of Lahontan cutthroat trout (Oncorhynchus clarkii henshawi) habitat.These surveys provide a larger scale assessment of riverscape health by utilizing high-resolution drone products. Surveys were conducted within occupied Lahontan cutthroat trout habitat, as designated by the U.S. Fish and Wildlife Service. Data were collected and managed by the U.S. Geological Survey and U.S. Fish and Wildlife Service, and/or affiliated field crews with support from the U.S. Geological Survey, U.S. Fish and Wildlife Service. U.S. Forest Service, and Nevada Department of Wildlife. Data are stored in a centralized database (LCT Conservation Efforts Database: https://conservationefforts.org/cutr/home/). Survey reaches were determined using a probabalistic sampling design (i.e., Generalized Random Tessellation Stratified).

This collection contains all resources generated as part of the Climate Adaptation Science (CAS) project (https://climateadaptation.usu.edu/). Resources include student course projects, research projects, internship work, assessments of educational outcomes, and other project materials. When creating resources, CAS participants will make all input data, models, code, results, instructions, and other digital artifacts developed for the project available for others to use, with the exception of sensitive human subjects data (expected level of reproducibility of at least Artifacts available). The steps at http://climateadaptation.usu.edu/project-data-models-code/ provide instructions for CAS participants to create a Hydroshare resource and request to add the resource to this collection. These steps were approved by the CAS Leadership Team on Nov. 15, 2018 and will be updated as needed. This collection is maintained by the CAS project coordinator.

This dataset tracks annual diversity score from 2014 to 2023 for Weber State University Charter Academy vs. Utah and Weber State University Charter Academy School District

This dataset was collected as an NCALM Seed grant for PI Keelin Schaffrath of Utah State University. The requested survey area consists of corridor polygons centered on 3 streams draining the Tushar Mountains of southwest Utah located 35 km northeast of Beaver, UT. The dataset was collected to quantify post-wildfire fish habitat quality. This survey was performed with an Optech Titan multispectral airborne LiDAR sensor mounted in a twin-engine Piper PA-31-350 Navajo Chieftain (Tail Number N640WA). Publications associated with this dataset can be found at NCALM's Data Tracking Center