The land area of Farmington Hills, MI was 33 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 Farmington Hills, MI
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Beach E. coli Predictions
data.cityofchicago.org | Last Updated 2024-09-03T04:55:05.000ZThe Chicago Park District issues swim advisories at beaches along Chicago's Lake Michigan lakefront based on E. coli levels. This dataset shows predicted E. coli levels based on an experimental analytical modeling approach.
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Utah Census Data Cities 2009-2013
opendata.utah.gov | Last Updated 2019-02-11T22:36:06.000ZData derived from Population Estimates, American Community Survey, Census of Population and Housing, State and County Housing Unit Estimates, County Business Patterns, Nonemployer Statistics, Economic Census, Survey of Business Owners, Building Permits
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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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Integration of Slurry Separation Technology & Refrigeration Units: Public Sanitation - National Water
datahub.usaid.gov | Last Updated 2024-06-25T02:47:00.000ZData from Uganda National Wastewater and Sewerage Corporation, Naalya Substation, April 2014 to April 2016. Provided by UNWSC.
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MDOT Plant Manual for Slope Planting
data.michigan.gov | Last Updated 2024-05-28T13:03:58.000ZThis plant manual identifies plants and planting practices ideal for slope stabilization along urban highways. Appropriate plant selections are adapted to environmental stresses and harsh site conditions along depressed highway slopes found in urban areas. The plant selections also meet additional design criteria (e.g., low growing to allow clear vision, aesthetic appeal). This research was conducted by Michigan State University Department of Horticulture and Dr. Cregg. This research was funded and managed by the Michigan Department of Transportation, Nanette Alton and Yige Qu - Project Managers. This dataset is intended to be updated annually, as needed by roadside development staff. By using this dataset, you are accepting the terms of use attached. Dataset Owner Contact: MDOT-PlantManual@michigan.gov
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Parks - Locations (deprecated November 2016)
data.cityofchicago.org | Last Updated 2019-05-17T16:07:40.000ZOUTDATED. See the current data at https://data.cityofchicago.org/d/ej32-qgdr --Parks managed by the Chicago Park District. Dataset includes park facilities and features information. For Shapefiles, go to https://data.cityofchicago.org/Parks-Recreation/Parks-Shapefiles/5msb-wbxn. For KML files, go to https://data.cityofchicago.org/Parks-Recreation/Parks-KML/hmfy-xsta.
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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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On-Station Trial on Seed Rate for Rainfed Wheat Planting in Balkh, Afghanistan, 2018-19 (Dataset)
datahub.usaid.gov | Last Updated 2024-08-23T16:10:21.000ZOne of 20+ trials conducted annually during 2018-19, 2019-20, and 2020-21 under the USAID-funded Grain Research and Innovation (GRAIN) project implemented by Michigan State University, in partnership with Afghanistan’s Ministry of Agriculture, Irrigation, and Livestock (MAIL), the Agricultural Research Institute of Afghanistan (ARIA), the International Center for Agricultural Research in the Dry Areas (ICARDA), and the International Maize and Wheat Improvement Center (CIMMYT).
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On-Station Trial on Nitrogen and Phosphate Fertilization of Wheat in Balkh, Afghanistan, 2018-19 (Dataset)
datahub.usaid.gov | Last Updated 2024-08-23T15:18:56.000ZOne of 20+ trials implemented during 2018/19, 2019/20, and 2020/21 under the USAID-funded Grain Research and Innovation (GRAIN) project implemented by Michigan State University, in partnership with partnership with Afghanistan’s Ministry of Agriculture, Irrigation, and Livestock (MAIL), the Agricultural Research Institute of Afghanistan (ARIA), the International Center for Agricultural Research in the Dry Areas (ICARDA), and the International Maize and Wheat Improvement Center (CIMMYT).
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On-Station Trial on Nitrogen and Phosphate Fertilization of Wheat in Kabul, Afghanistan 2018-19 (Dataset)
datahub.usaid.gov | Last Updated 2024-08-23T15:23:20.000ZOne of 20+ trials implemented during 2018/19, 2019/20, and 2020/21 under the USAID-funded Grain Research and Innovation (GRAIN) project implemented by Michigan State University, in partnership with partnership with Afghanistan’s Ministry of Agriculture, Irrigation, and Livestock (MAIL), the Agricultural Research Institute of Afghanistan (ARIA), the International Center for Agricultural Research in the Dry Areas (ICARDA), and the International Maize and Wheat Improvement Center (CIMMYT).