The land area of New Plymouth, ID was 1 in 2018. The land area of Parma, ID was 1 in 2018.
Land Area
Water Area
Land area is a measurement providing the size, in square miles, of the land portions of geographic entities for which the Census Bureau tabulates and disseminates data. Area is calculated from the specific boundary recorded for each entity in the Census Bureau's geographic database. Land area is based on current information in the TIGER® data base, calculated for use with Census 2010.
Water Area figures include inland, coastal, Great Lakes, and territorial sea water. Inland water consists of any lake, reservoir, pond, or similar body of water that is recorded in the Census Bureau's geographic database. It also includes any river, creek, canal, stream, or similar feature that is recorded in that database as a two- dimensional feature (rather than as a single line). The portions of the oceans and related large embayments (such as Chesapeake Bay and Puget Sound), the Gulf of Mexico, and the Caribbean Sea that belong to the United States and its territories are classified as coastal and territorial waters; the Great Lakes are treated as a separate water entity. Rivers and bays that empty into these bodies of water are treated as inland water from the point beyond which they are narrower than 1 nautical mile across. Identification of land and inland, coastal, territorial, and Great Lakes waters is for data presentation purposes only and does not necessarily reflect their legal definitions.
Above charts are based on data from the U.S. Census American Community Survey | ODN Dataset | API -
Geographic and Area Datasets Involving New Plymouth, ID or Parma, ID
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Beach Lab Data
data.cityofchicago.org | Last Updated 2024-09-04T19:00:17.000ZThe Chicago Park District collects and analyzes water samples from beaches along Chicago’s Lake Michigan lakefront. The Chicago Park District partners with the University of Illinois at Chicago Department of Public Health Laboratory to analyze water samples using a new DNA testing method called Rapid Testing Method (qPCR analysis) which tests for Enterococci in order to monitor swimming safety. The rapid testing method (qPCR analysis) is a new method that measures levels of pathogenic DNA in beach water. Unlike the culture based test that requires up to 24 hours of processing, the new rapid testing method requires a 4-5 hours for results. The Chicago Park District can use results of the rapid test to notify the public when levels exceed UPEPA recommended levels, which is 1000* CCE. When DNA bacteria levels exceed 1000 CCE, a yellow swim advisory flag is implemented. For more information please refer to the USEPA Recreational Water Quality Criteria (http://water.epa.gov/scitech/swguidance/standards/criteria/health/recreation). Historically, the Chicago Park District used the culture based analysis method and statistical prediction models to monitor beach water quality. The culture based method tests for Escherichia coli (E. coli) bacteria which is an indicator species for the presence of disease-causing bacteria, viruses, and protozoans that may pose health risks to the public. This method requires 18-24 hours of processing to receive results. The Chicago Park District would use results of the culture based method to notify the public when levels exceed UPEPA recommended levels, which is 235* CFU. When bacteria levels exceed 235 CFU, a yellow swim advisory flag was implemented. This standard is still used at most beaches throughout the Great Lakes region. For more information please refer to the USEPA Recreational Water Quality Criteria. The statistical prediction model forecasted real-time Escherichia coli (E. coli) bacteria levels present in the water. The Chicago Park District (CPD) in partnership with the US Geological Survey, developed statistical prediction models by using weather data pulled from CPD buoys (https://data.cityofchicago.org/d/qmqz-2xku) and weather stations (https://data.cityofchicago.org/d/k7hf-8y75). The Chicago Park District would use results of the predictive model to notify the public when bacteria levels would exceed 235 CFU. When bacteria levels exceed 235 CFU, a yellow swim advisory flag was implemented. * The unit of measurement for Escherichia coli is Colony Forming Units (CFU) per 100 milliliters of water. (Culture Based Method / Statistical Prediction Model) *The unit of measuring DNA is Enterococci Calibrator Cell Equivalents (CCE) per 100 milliliters of water. (Rapid Testing Analysis)
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ENERGY STAR Certified Commercial Dishwashers
data.energystar.gov | Last Updated 2024-10-23T13:33:25.000ZCertified 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.
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Cambridge Building Energy Use Disclosure Ordinance (BEUDO) Data 2015-2022
data.cambridgema.gov | Last Updated 2024-01-17T14:49:52.000ZThis dataset contains compliance status and energy and water use data gathered under the Building Energy Use Disclosure Ordinance (BEUDO) program. Property details, energy use and water use data are submitted by property owners or managers whose properties are subject to BEUDO through an online tool called ENERGY STAR Portfolio Manager. Parcel level property information is obtained from the City of Cambridge Property Database. Energy and water use information submitted by property owners and managers is shown for properties that first began reporting data on energy used in 2015. Energy use for the listed Data Year is required to be reported by May of the next year. Properties subject to BEUDO reporting include: - nonresidential properties 25,000 square feet or more, - residential properties with 50 or more units and - municipal properties 10,000 square feet or more. Reports may include data on one or more buildings. The specific building IDs included (from the Cambridge GIS Building Footprints layer) are listed in the Buildings Included column. The report level is the most detailed level of energy use available - if multiple buildings are included in a report, we do not have energy use on the individual buildings, only the group. Building IDs and what they refer to have changed over time, even for buildings that did not change. To ensure you are using only comparable data when comparing reports over time, you should only make direct comparisons for reports with the same Reporting ID. Properties with no energy data included are those that were identified as being subject to BEUDO for the given Data Year, but which did not submit a report. Note that the City of Cambridge makes all efforts to acquire accurate data from BEUDO properties. The data may still contain errors or omissions. Under the 2023 amendments to the BEUDO ordinance, reporters will be required to get third-party verification of their reporting data.
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Neighborly ERA Applications
sharefulton.fultoncountyga.gov | Last Updated 2024-02-20T02:51:22.000ZThis dataset contains all applicants for emergency rental and/or utility assistance in the Neighborly system.
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Water Point Data Exchange - Plus (WPdx+)
data.waterpointdata.org | Last Updated 2024-10-23T06:08:33.000ZWPdx+ is an enhanced version of the WPdx-Basic dataset. For a full comparison between the two datasets, please visit our blog at https://www.waterpointdata.org/2021/10/07/introducing-wpdx-plus/. The Water Point Data Exchange (WPdx) is the global platform for sharing water point data. The WPdx Data Standard was designed by a wide range of stakeholders from across sectors and around the world. The core attributes included in the standard are already being collected by governments, researchers, and organizations around the world. To read more about the standard or to contribute water point data visit www.waterpointdata.org.
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Land Use_data
opendata.utah.gov | Last Updated 2024-04-10T19:40:16.000ZThis 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.
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2020 Census Tracts to 2020 NTAs and CDTAs Equivalency
data.cityofnewyork.us | Last Updated 2024-07-05T13:45:38.000ZThis file shows the relationship between New York City’s 2020 census tracts, 2020 Neighborhood Tabulation Areas (NTAs), and Community District Tabulation Areas (CDTAs). 2020 census tracts nest within 2020 NTAs, and 2020 NTAs nest within CDTAs, so each census tract is listed only once. Note that CDTAs sometimes cross borough boundaries, and therefore will not add up to borough totals for the Bronx, Queens, and Manhattan. As they are nested within CDTAs, NTAs will likewise not add up to borough totals. Also note that census tracts in New York City’s water areas are excluded from this file.
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Water Consumption And Cost (2013 - Feb 2023)
data.cityofnewyork.us | Last Updated 2023-04-11T20:47:16.000ZMonthly consumption and cost data by borough and development. Data set includes utility vendor and meter information.
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Waste Tire Abatement Sites
data.ny.gov | Last Updated 2024-09-27T18:10:25.000ZInformation on designated waste tire abatement sites in New York State, including approximate size, location, and abatement status.
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RSBS MOM: Part 1 of 2, New York State Residential Statewide Baseline Study: Survey of Multifamily Owners and Managers
data.ny.gov | Last Updated 2019-11-15T22:04:57.000ZHow does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov. This is part 1 (containing: Property Characteristics; Heating and Cooling; Water Heating; Tenant Appliances; Lighting; and Common Area) of 2; part 2 (https://data.ny.gov/d/hc4z-b2p5) contains: Purchasing Decisions; Washer and Dryer; and Miscellaneous. The New York State Energy Research and Development Authority (NYSERDA), in collaboration with the New York State Department of Public Service (DPS), conducted a statewide residential baseline study (study) from 2011 to 2014 of the single-family and multifamily residential housing segments, including new construction, and a broad range of energy uses and efficiency measures. This dataset includes data from 219 completed Multifamily owner and manager surveys. The types of data collected during the survey cover property characteristics, heating and cooling equipment, water heating equipment, tenant appliances, lighting, purchasing decision, common areas, clothes washing and drying, and miscellaneous equipment. The data is segmented to cover both common space equipment and, to the degree possible, tenant-unit equipment, such as refrigerators or clothes washers that are included in the rental by the building ownership.