ENERGY STAR Certified Commercial Dishwashers

Certified models meet all ENERGY STAR requirements as listed in the Version 3.0 ENERGY STAR Program Requirements for Commercial Dishwashers that are effective as of July 27, 2021. A detailed listing of key efficiency criteria are available at https://www.energystar.gov/products/commercial_food_service_equipment/commercial_dishwashers/key_product_criteria.

King County Ambient Streams Monitoring - Site Water Quality Criteria

Maricopa County Regional Work Zone Data Exchange (WZDx) v1.1 Feed Sample

The WZDx Specification enables infrastructure owners and operators (IOOs) to make harmonized work zone data available for third party use. The intent is to make travel on public roads safer and more efficient through ubiquitous access to data on work zone activity. Specifically, the project aims to get data on work zones into vehicles to help automated driving systems (ADS) and human drivers navigate more safely. MCDOT leads the effort to aggregate and collect work zone data from the AZTech Regional Partners. A continuously updating archive of the WZDx feed data can be found at <a href="http://usdot-its-workzone-publicdata.s3.amazonaws.com/index.html" target="_blank" rel="noopener">ITS WorkZone Data Sandbox</a>. The live feed is currently compliant with <a href="https://github.com/usdot-jpo-ode/jpo-wzdx/tree/v1.1" target="_blank" rel="noopener">WZDx specification version 1.1</a>.

Restaurant Inspections in Tri-County Colorado 2018

Restaurant Inspection data for food service facilities within Adams, Arapahoe, and Douglas counties in Colorado provided by Tri-County Health Department (TCHD) in 2018.

Mosquito Larval Counts

Records of pools (bodies of water) sampled by city staff for presence of mosquito larvae.

Maricopa County Regional Work Zone Data Exchange (WZDx) v3.0 Feed Sample

The WZDx Specification enables infrastructure owners and operators (IOOs) to make harmonized work zone data available for third party use. The intent is to make travel on public roads safer and more efficient through ubiquitous access to data on work zone activity. Specifically, the project aims to get data on work zones into vehicles to help automated driving systems (ADS) and human drivers navigate more safely. MCDOT leads the effort to aggregate and collect work zone data from the AZTech Regional Partners. A continuously updating archive of the WZDx feed data can be found at <a href="http://usdot-its-workzone-publicdata.s3.amazonaws.com/index.html" target="_blank" rel="noopener">ITS WorkZone Data Sandbox</a>. The live feed is currently compliant with <a href="https://github.com/usdot-jpo-ode/jpo-wzdx/tree/v3.0" target="_blank" rel="noopener">WZDx specification version 3.0</a>.

Horseshoe Crab Spawning Survey

Delaware Bay shore survey data starting with 1999 which denotes peak spawning occurrences by day and lunar period, proportion of spawning in May (coinciding with shorebird stopovers), average water temperature, index values for female and male crabs per square meter by beach and bay-wide, the annual sex ratio, and index of abundance per beach.

NYSERDA 2023 Soils Data for use in the Large-Scale Renewables and NY-Sun Programs

THE NYSERDA 2023 SOILS DATA IS TO BE USED FOR NYSERDA’S RENEWABLE ENERGY STANDARD (RES) REQUEST FOR PROPOSAL (RFP) ISSUED AFTER THE PUBLICATION OF THIS DATA OR THE NY-SUN PROGRAM AND IS NOT INTENDED TO REPRESENT ACTUAL IN SITU SOIL CONDITIONS. In order to facilitate the protection of agricultural lands, developers participating in RESRFPs or the NY-Sun program may be responsible for making an agricultural mitigation payment to a designated fund based on the extent to which the solar project’s facility area overlaps with an Agricultural District and New York’s highly productive agricultural soils, identified as Mineral Soil Groups (MSG) classifications 1 through 4 (MSG 1-4). This mitigation approach is designed to discourage solar projects from siting on MSG 1-4. Furthermore, this mitigation approach is designed to encourage retaining agricultural productivity on the project site. Instances where Proposers cannot avoid or minimize impacts on MSG 1-4 will result in a payment to a fund administered by NYSERDA. Disbursement of collected agricultural mitigation payment funds will be informed by consultation with the New York State Department of Agriculture and Markets (AGM) to support ongoing regional agricultural practices and/or soil conservation initiatives. This dataset contains a combination of soils data from multiple sources to serve participants of NYSERDA’s Large-Scale Renewable and NY-Sun programs. The NYSERDA 2023 Soils Data was created by converting the 2023 New York State Agricultural Land Classification (https://agriculture.ny.gov/system/files/documents/2023/01/masterlistofagriculturalsoils.pdf) master list of soils maintained by AGM to a tabular form and providing a corresponding unique identifier for each listed soil that enables the user to link the soils to the Natural Resources Conservation Service (NRCS) SSURGO soils database, allowing for a geographical representation. When the NYSERDA 2023 Soils Data is joined with spatial data from the Natural Resources Conservation Service (NRCS) SSURGO soils database (https://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/survey/?cid=nrcs142p2_053627), the corresponding soil unit can be mapped in a geographic information system software. The latest version of the SSURGO database (https://nrcs.app.box.com/v/soils) should be used to get the most accurate join. Data is updated yearly from both NRCS and from AGM, however, NYSERDA will not update this dataset and it will remain intact for future reference. NYSERDA intends on creating new soils datasets for future procurements on an annual basis. The New York State Energy Research and Development Authority (NYSERDA) offers objective information and analysis, innovative programs, technical expertise, and support to help New Yorkers increase energy efficiency, save money, use renewable energy, and reduce reliance on fossil fuels. To learn more about NYSERDA’s programs, visit nyserda.ny.gov or follow us on Twitter, Facebook, YouTube, or Instagram.

Land Use_data

This dataset combines the work of several different projects to create a seamless data set for the contiguous United States. Data from four regional Gap Analysis Projects and the LANDFIRE project were combined to make this dataset. In the Northwestern United States (Idaho, Oregon, Montana, Washington and Wyoming) data in this map came from the Northwest Gap Analysis Project. In the Southwestern United States (Colorado, Arizona, Nevada, New Mexico, and Utah) data used in this map came from the Southwest Gap Analysis Project. The data for Alabama, Florida, Georgia, Kentucky, North Carolina, South Carolina, Mississippi, Tennessee, and Virginia came from the Southeast Gap Analysis Project and the California data was generated by the updated California Gap land cover project. The Hawaii Gap Analysis project provided the data for Hawaii. In areas of the county (central U.S., Northeast, Alaska) that have not yet been covered by a regional Gap Analysis Project, data from the Landfire project was used. Similarities in the methods used by these projects made possible the combining of the data they derived into one seamless coverage. They all used multi-season satellite imagery (Landsat ETM+) from 1999-2001 in conjunction with digital elevation model (DEM) derived datasets (e.g. elevation, landform) to model natural and semi-natural vegetation. Vegetation classes were drawn from NatureServe’s Ecological System Classification (Comer et al. 2003) or classes developed by the Hawaii Gap project. Additionally, all of the projects included land use classes that were employed to describe areas where natural vegetation has been altered. In many areas of the country these classes were derived from the National Land Cover Dataset (NLCD). For the majority of classes and, in most areas of the country, a decision tree classifier was used to discriminate ecological system types. In some areas of the country, more manual techniques were used to discriminate small patch systems and systems not distinguishable through topography. The data contains multiple levels of thematic detail. At the most detailed level natural vegetation is represented by NatureServe’s Ecological System classification (or in Hawaii the Hawaii GAP classification). These most detailed classifications have been crosswalked to the five highest levels of the National Vegetation Classification (NVC), Class, Subclass, Formation, Division and Macrogroup. This crosswalk allows users to display and analyze the data at different levels of thematic resolution. Developed areas, or areas dominated by introduced species, timber harvest, or water are represented by other classes, collectively refered to as land use classes; these land use classes occur at each of the thematic levels. Six layer files are included in the download packages to assist the user in displaying the data at each of the Thematic levels in ArcGIS.