The water area of York, AL was 0 in 2012. The water area of Many, LA was 0 in 2012.

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 - Notes:

1. ODN datasets and APIs are subject to change and may differ in format from the original source data in order to provide a user-friendly experience on this site.

2. To build your own apps using this data, see the ODN Dataset and API links.

3. If you use this derived data in an app, we ask that you provide a link somewhere in your applications to the Open Data Network with a citation that states: "Data for this application was provided by the Open Data Network" where "Open Data Network" links to http://opendatanetwork.com. Where an application has a region specific module, we ask that you add an additional line that states: "Data about REGIONX was provided by the Open Data Network." where REGIONX is an HREF with a name for a geographical region like "Seattle, WA" and the link points to this page URL, e.g. http://opendatanetwork.com/region/1600000US5363000/Seattle_WA

Geographic and Area Datasets Involving Many, LA or York, AL

  • API

    Citizen Statewide Lake Monitoring Assessment Program (CSLAP) Lakes

    data.ny.gov | Last Updated 2024-03-01T18:08:08.000Z

    The dataset represents the lakes participating in the Citizen Statewide Lake Monitoring Assessment Program (CSLAP). CSLAP is a volunteer lake monitoring and education program that is managed by DEC and New York State Federation of Lake Associations (NYSFOLA). The data collected through the program is used to identify water quality issues, detect seasonal and long term patterns, and inform volunteers and lake residents about water quality conditions in their lake. The program has delivered high quality data to many DEC programs for over 25 years.The dataset catalogs CSLAP lake information; including: lake name, lake depth, public accessibility, trophic status, watershed area, elevation, lake area, water quality classification, county, town, CSLAP status, years sampled, and last year sampled.

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    OLAS/SCL WASH Household Survey Interpolated Dataset

    mydata.iadb.org | Last Updated 2024-09-26T15:04:31.000Z

    This dataset is an interpolated version of the OLAS/SCL Household Survey Data Set, and includes data from Latin America and Caribbean countries from 2003-2023. The interpolation can be used for understanding trends in water and sanitation access in the region.

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    Final Disadvantaged Communities (DAC) 2023

    data.ny.gov | Last Updated 2024-07-01T16:29:21.000Z

    The Climate Leadership and Community Protection Act (CLCPA) directs the Climate Justice Working Group (CJWG) to establish criteria for defining disadvantaged communities. This dataset identifies areas throughout the State that meet the final disadvantaged community definition as voted on by the Climate Justice Working Group. 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, accelerate economic growth, and reduce reliance on fossil fuels. To learn more about NYSERDA’s programs, visit nyserda.ny.gov or follow us on X, Facebook, YouTube, or Instagram.

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    NNDSS - Table 1B. Arboviral diseases, Jamestown Canyon virus disease to Powassan virus disease

    data.cdc.gov | Last Updated 2022-01-12T18:33:43.000Z

    NNDSS - TABLE 1B. Arboviral diseases, Jamestown Canyon virus disease to Powassan virus disease – 2021. In this Table, provisional cases* of notifiable diseases are displayed for United States, U.S. territories, and Non U.S. residents. Notice: Due to data processing issues at CDC, data for the following jurisdictions may be incomplete for week 7: Alaska, Arizona, California, Connecticut, Delaware, Florida, Hawaii, Louisiana, Maryland, Michigan, Missouri, North Dakota, New Hampshire, New York City, Oregon, Pennsylvania, and Rhode Island. Note: This table contains provisional cases of national notifiable diseases from the National Notifiable Diseases Surveillance System (NNDSS). NNDSS data from the 50 states, New York City, the District of Columbia and the U.S. territories are collated and published weekly on the NNDSS Data and Statistics web page (https://wwwn.cdc.gov/nndss/data-and-statistics.html). Cases reported by state health departments to CDC for weekly publication are provisional because of the time needed to complete case follow-up. Therefore, numbers presented in later weeks may reflect changes made to these counts as additional information becomes available. The national surveillance case definitions used to define a case are available on the NNDSS web site at https://wwwn.cdc.gov/nndss/. Information about the weekly provisional data and guides to interpreting data are available at: https://wwwn.cdc.gov/nndss/infectious-tables.html. Footnotes: U: Unavailable — The reporting jurisdiction was unable to send the data to CDC or CDC was unable to process the data. -: No reported cases — The reporting jurisdiction did not submit any cases to CDC. N: Not reportable — The disease or condition was not reportable by law, statute, or regulation in the reporting jurisdiction. NN: Not nationally notifiable — This condition was not designated as being nationally notifiable. NP: Nationally notifiable but not published. NC: Not calculated — There is insufficient data available to support the calculation of this statistic. Cum: Cumulative year-to-date counts. Max: Maximum — Maximum case count during the previous 52 weeks. * Case counts for reporting years 2020 and 2021 are provisional and subject to change. Cases are assigned to the reporting jurisdiction submitting the case to NNDSS, if the case's country of usual residence is the U.S., a U.S. territory, unknown, or null (i.e. country not reported); otherwise, the case is assigned to the 'Non-U.S. Residents' category. Country of usual residence is currently not reported by all jurisdictions or for all conditions. For further information on interpretation of these data, see https://wwwn.cdc.gov/nndss/document/Users_guide_WONDER_tables_cleared_final.pdf. †Previous 52 week maximum and cumulative YTD are determined from periods of time when the condition was reportable in the jurisdiction (i.e., may be less than 52 weeks of data or incomplete YTD data).

  • API

    Land Use_data

    opendata.utah.gov | Last Updated 2024-04-10T19:40:16.000Z

    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.

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    NYC Building Energy and Water Data Disclosure for Local Law 84 (2022-Present)

    data.cityofnewyork.us | Last Updated 2024-10-01T19:56:35.000Z

    Local Law 84 of 2009 (LL84) requires annual energy and water benchmarking data to be submitted by owners of buildings with more than 50,000 square feet. This data is collected via the Environmental Protection Agency's (EPA) <a href="https://www.energystar.gov/buildings/tools-and-resources/portfolio-manager-0">Portfolio Manager website</a> Each property is identified by it's EPA assigned property ID, and can contain one or more tax lots identified by one or more BBLs (Borough, Block, Lot) or one or more buildings identified by one or more building identification numbers (BIN) Please visit <a href="https://www1.nyc.gov/site/buildings/codes/benchmarking.page">DOB's Benchmarking and Energy Efficiency Rating page</a> for additional information.

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    Primary Land Use Tax Lot Output (PLUTO)

    data.cityofnewyork.us | Last Updated 2024-09-30T20:56:40.000Z

    Extensive land use and geographic data at the tax lot level in comma-separated values (CSV) file format. The PLUTO files contain more than seventy fields derived from data maintained by city agencies. All previously released versions of this data are available at <a href="https://www.nyc.gov/site/planning/data-maps/open-data/bytes-archive.page?sorts%5Byear%5D=0">BYTES of the BIG APPLE- Archive</a>

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    Database of Political Institutions 2015

    mydata.iadb.org | Last Updated 2024-02-15T17:19:32.000Z

    The Database of Political Institutions presents institutional and electoral results data such as measures of checks and balances, tenure and stability of the government, identification of party affiliation and ideology, and fragmentation of opposition and government parties in the legislature, among others. The current version of the database, which is now hosted at the IDB, expands its coverage to about 180 countries for 40 years, 1975–2015. Researchers at the World Bank Development Research Group first compiled the database in 2000 (see citation information below). It has become one of the most cited databases in comparative political economy and comparative political institutions. Almost 3000 studies have used this database so far as a source of institutional and political data in their empirical analysis. <br><br><b>Click here to access the data: https://mydata.iadb.org/idb/dataset/ngy5-9h9d/</b></br></br>

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    Client Semi-Annual Report: Beginning 2019

    data.ny.gov | Last Updated 2024-07-31T02:46:12.000Z

    Any Contractual Client retaining, employing or designating a Lobbyist or Lobbyists (whether or not any such Lobbyist was required to file a Statement of Registration or Bi-monthly Report) who incurs or reasonably anticipates incurring more than $5,000 in combined Reportable Compensation and Expenses for Lobbying Activities on a State and/or Municipal level, is required to submit a Client Semi-Annual (“CSA”) Report. The CSA Report requires disclosure of the actual Lobbying Activities that occurred during the specific reporting period. The CSA reporting period covers January/June; or July/December.

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    Lobbyist Bi-Monthly Reports: Beginning 2019

    data.ny.gov | Last Updated 2024-08-02T15:58:41.000Z

    Any Principal Lobbyist required to file a Statement of Registration for a Client in a biennial period must also file Bi-monthly Reports, regardless of Compensation, Expenses, or Lobbying Activity, up to the Lobbying Agreement Termination (End) Date. The Bi-monthly Report requires the Filer to disclose the Lobbying Activities that occurred, and monies spent during the applicable reporting period. Proper disclosure of these Lobbying Activities necessitates a level of specificity that makes clear to the public exactly what and who was being lobbied during the specific Bi-monthly reporting period.