The land area of Fair Haven, VT was 3 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 -
Geographic and Area Datasets Involving Fair Haven, VT
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NOAA - Sanctuary and Monument reporting areas providing resource services at an acceptable level
performance.commerce.gov | Last Updated 2024-03-28T20:23:00.000ZAn important purpose of national marine sanctuaries is to ensure that the significant resources they protect provide benefits to the public. This performance measure is intended to track the extent to which marine sanctuaries benefit the public through the provision of “resource services”. Resource services include commonly defined “ecosystem services” as well as the services provided by archaeological resources. The measure uses status ratings from sanctuary condition reports to quantify the proportion of services rated as either “Good” or “Good/Fair,” both of which are considered acceptable levels of service potential.
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RSBS MOM: Multifamily On-Site Inspections, Site Level, New York State Residential Statewide Baseline Study
data.ny.gov | Last Updated 2019-11-15T22:10:45.000ZHow 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. 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 collected from a total of 67 on-site inspections of multifamily buildings. Data collected during the inspections covers property characteristics, heating and cooling equipment, water heating equipment, appliances, lighting, clothes washing and drying, miscellaneous energy using equipment, and observable operating behavior. The objective of the on-site inspections was to enhance the residential baseline study with detailed on-site information and, to the degree possible, verify self-reported data from the phone and web surveys. The on-site inspection data is segmented to cover both common space equipment and tenant-unit equipment.
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Community Survey
datahub.austintexas.gov | Last Updated 2023-09-13T22:02:29.000ZEach year the city of Austin administers a community survey to assess satisfaction with the delivery of the major City Services and to help determine priorities for the community as part of the City's ongoing planning process. To find out more information about the Community Survey and to view the Survey Instruments, please refer to the attachments. The data set for the Community Survey captures data from 2015 through 2019.
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CTCAC/HCD Resource Opportunity Areas 2022
data.bayareametro.gov | Last Updated 2023-06-08T23:15:47.000ZIn 2017, the California Tax Credit Allocation Committee (CTCAC) and the Department of Housing and Community Development (HCD) created the California Fair Housing Task Force (Task Force). The Task Force was asked to assist CTCAC and HCD in creating evidence-based approaches to increasing access to opportunity for families with children living in housing subsidized by the Low-Income Housing Tax Credit (LIHTC) program. This feature set contains Resource Opportunity Areas (ROAs) that are the results of the Task Force's analysis for the two regions used for the San Francisco Bay Region; one is for the cities and towns (urban) and the other is for the rural areas. The reason for treating urban and rural areas as separate reasons is that using absolute thresholds for place-based opportunity could introduce comparisons between very different areas of the total region that make little sense from a policy perspective — in effect, holding a farming community to the same standard as a dense, urbanized neighborhood. ROA analysis for urban areas is based on census tract data. Since tracts in rural areas of are approximately 37 times larger in land area than tracts in non-rural areas, tract-level data in rural areas may mask over variation in opportunity and resources within these tracts. Assessing opportunity at the census block group level in rural areas reduces this difference by 90 percent (each rural tract contains three block groups), and thus allows for finer-grained analysis. In addition, more consistent standards can be useful for identifying areas of concern from a fair housing perspective — such as high-poverty and racially segregated areas. Assessing these factors based on intraregional comparison could mischaracterize areas in more affluent areas with relatively even and equitable development opportunity patterns as high-poverty, and could generate misleading results in areas with higher shares of objectively poor neighborhoods by holding them to a lower, intraregional standard. To avoid either outcome, the Task Force used a hybrid approach for the CTCAC/HCD ROA analysis — accounting for regional differences in assessing opportunity for most places, while applying more rigid standards for high-poverty, racially segregated areas in all regions. In particular: Filtering for High-Poverty, Racially Segregated Areas The CTCAC/HCD ROA filters areas that meet consistent standards for both poverty (30% of the population below the federal poverty line) and racial segregation (over-representation of people of color relative to the county) into a “High Segregation & Poverty” category. The share of each region that falls into the High Segregation & Poverty category varies from region to region. Calculating Index Scores for Non-Filtered Areas The CTCAC/HCD ROAs process calculates regionally derived opportunity index scores for non-filtered tracts and rural block groups using twenty-one indicators (see Data Quality section of metadata for more information). These index scores make it possible to sort each non-filtered tract or rural block group into opportunity categories according to their rank within the urban or rural areas. To allow CTCAC and HCD to incentivize equitable development patterns in each region to the same degree, the CTCAC/HCD analysis 20 percent of tracts or rural block groups in each urban or rural area, respectively, with the highest relative index scores to the "Highest Resource” designation and the next 20 percent to the “High Resource” designation. The region's urban area thus ends up with 40 percent of its total tracts with reliable data as Highest or High Resource (or 40 percent of block groups in the rural area). The remaining non-filtered tracts or rural block groups are then evenly divided into “Low Resource” and “Moderate Resource” categories. Excluding Tracts or Block Groups The analysis also excludes certain census areas from being categorized. To improve the accuracy of the mapping, tracts and rural bl
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Community Survey: 2023 Survey Data
data.bloomington.in.gov | Last Updated 2023-08-03T19:34:23.000ZThe City of Bloomington contracted with National Research Center, Inc. to conduct the 2023 Bloomington Community Survey. This is the fourth time a scientific citywide survey has been completed covering resident opinions on service delivery satisfaction by the City of Bloomington and quality of life issues. <br> The 2023 survey received responses from 367 households (from a scientific sample of 3,000) and an additional 557 residents completed the opt-in survey. Read more at: <a href="https://bton.in/LWVOR">bton.in/LWVOR</a>.
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Current Descriptive Data of Municipal Wastewater Treatment Plants
data.ny.gov | Last Updated 2019-06-10T18:04:47.000ZData containing municipal wastewater treatment plant design other features, with data current through the most recent survey.
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RSBS SMO: Part 2 of 2, New York State Residential Statewide Baseline Study: Single and Multifamily Occupant Telephone or Web Survey
data.ny.gov | Last Updated 2019-11-15T21:50:04.000ZHow 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 2 (contains: Clothes Washing and Drying; Water Heating; Home Lighting; Pool and Spa; Small Household Appliances; and Miscellaneous Equipment) of 2; part 1 (https://data.ny.gov/d/3m6x-h3qa) contains: Behavior and Demographics; Building Shell; Kitchen Appliances; and Heating and Cooling. 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 2,982 single-family and 379 multifamily occupant survey completes for a total of 3,361 responses. The survey involved 2,285 Web, 1,041 telephone, and 35 mini-inspection surveys. The survey collected information on the following building characteristics: building shell, kitchen appliances, heating and cooling equipment, water heating equipment, clothes washing and drying equipment, lighting, pool and spa equipment, small household appliances, miscellaneous energy consuming equipment, as well as behaviors and characteristics of respondents.
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RSBS MOM: Multifamily On-Site Survey, Measure Level, New York State Residential Statewide Baseline Study
data.ny.gov | Last Updated 2019-11-15T22:18:02.000ZHow 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. 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 collected from a total of 67 on-site inspections of multifamily buildings. Data collected during the inspections covers property characteristics, heating and cooling equipment, water heating equipment, appliances, lighting, clothes washing and drying, miscellaneous energy using equipment, and observable operating behavior. The objective of the on-site inspections was to enhance the residential baseline study with detailed on-site information and, to the degree possible, verify self-reported data from the phone and web surveys. The on-site inspection data is segmented to cover both common space equipment and tenant-unit equipment.
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County
data.vermont.gov | Last Updated 2024-07-09T22:51:59.000Z<span style='font-family:"Avenir Next W01", "Avenir Next W00", "Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'>This layer contains a </span><span style='font-family:"Avenir Next W01", "Avenir Next W00", "Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'><span style='font-family:"Avenir Next W01", "Avenir Next W00", "Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'><span style='font-weight:bold;'>Vermont-only subset</span> </span>of county level 2020 Decennial Census redistricting data as reported by the U.S. Census Bureau </span><span style='font-family:"Avenir Next W01", "Avenir Next W00", "Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'>for all states plus DC and Puerto Rico. The attributes come from the 2020 Public Law 94-171 (P.L. 94-171) tables.</span><div style='font-family:"Avenir Next W01", "Avenir Next W00", "Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'><br /></div><div style='font-family:"Avenir Next W01", "Avenir Next W00", "Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'><b>Data download date:</b> August 12, 2021</div><div style='font-family:"Avenir Next W01", "Avenir Next W00", "Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'><b>Census tables:</b> P1, P2, P3, P4, H1, P5, Header</div><div style='font-family:"Avenir Next W01", "Avenir Next W00", "Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'><b>Downloaded from:</b> <a href='https://www2.census.gov/programs-surveys/decennial/2020/data/01-Redistricting_File--PL_94-171/?' style='font-family:"Avenir Next", Avenir, "Helvetica Neue", Helvetica, Arial, sans-serif; font-size:15px;' target='_blank' rel='nofollow ugc noopener noreferrer'>Census FTP site</a></div><div><div style='font-family:inherit; font-size:16px;'><br /></div><div style='font-family:inherit; font-size:16px;'><b>Processing Notes:</b></div><div><ul><li>Data was downloaded from the U.S. Census Bureau FTP site, imported into SAS format and joined to the 2020 TIGER boundaries. Boundaries are sourced from the <a href='https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-geodatabase-file.html' style='font-family:inherit; color:rgb(0, 121, 193); text-decoration-line:none;' target='_blank' rel='nofollow ugc noopener noreferrer'>2020 TIGER/Line Geodatabases</a><span style='font-family:inherit;'>. Boundaries have been projected into Web Mercator and each attribute has been given a clear descriptive alias name. No alterations have been made to the vertices of the data.</span></li><li>Each attribute maintains it's specified name from Census, but also has a descriptive alias name and long description derived from the technical documentation provided by the Census. </li><li>For a detailed list of the attributes contained in this layer, view the Data tab and select "Fields". </li><li>The following alterations have been made to the tabular data:</li><ul><li>Joined all tables to create one wide attribute table:</li><ul><li>P1 - Race</li><li>P2 - Hispanic or Latino, and not Hispanic or Latino by Race</li><li>P3 - Race for the Population 18 Years and Over</li><li>P4 - Hispanic or Latino, and not Hispanic or Latino by Race for the Population 18 Years and Over</li><li>H1 - Occupancy Status (Housing)</li><li>P5 - Group Quarters Population by Group Quarters Type (correctional institutions, juvenile facilities, nursing facilities/skilled nursing, college/university student housing, military quarters, etc.)</li><li>Header</li></ul><li>After joining, dropped fields: FILEID, STUSAB, CHARITER, CIFSN, LOGREC
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DART (Department Application Review and Tracking) on the Web: Beginning 1988
data.ny.gov | Last Updated 2024-10-01T14:01:44.000ZTabular Data for Permits administered by the Agency in which the general public can use a web interface to look up specific facilities and applications.