The land area of Upper Fruitland, NM was 7 in 2015.

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 Upper Fruitland, NM

  • API

    Horseshoe Crab Spawning Survey

    data.delaware.gov | Last Updated 2022-10-06T19:41:25.000Z

    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.

  • API

    Aquatic Biological Monitoring Sampling Locations: Beginning 1980

    data.ny.gov | Last Updated 2024-05-02T15:02:49.000Z

    The Division of Water Stream Biomonitoring Unit (SBU) dataset contains the point sampling locations at which benthic macroinvertebrates, field chemistry, and at some locations, sediment, fish or diatoms have been collected as part of the Rotating Integrated Basin Studies (RIBS) program, Rapid Biological Assessments (RAS), or special studies. The data collected are used for water quality assessment (input to the Waterbody Inventory, completion of the 305(b) report and 303(d) list of impaired Waters) and for track-down of water quality problems. The data set is maintained by the Division of Water, Bureau of Water Assessment and Management, Stream Biomonitoring Unit.

  • API

    Municipal Wastewater COVID19 Sampling Data 10/1/2020-6/30/2022

    data.cambridgema.gov | Last Updated 2024-04-18T20:25:13.000Z

    This dataset is no longer being updated as of 6/30/2022. It is being retained on the Open Data Portal for its potential historical interest. In November 2020, the City of Cambridge began collecting and analyzing COVID-19 data from municipal wastewater, which can serve as an early indicator of increased COVID-19 infections in the city. The Cambridge Public Health Department and Cambridge Department of Public Works are using technology developed by Biobot, a Cambridge based company, and partnering with the Massachusetts Water Resources Authority (MWRA). This Cambridge wastewater surveillance initiative is funded through a $175,000 appropriation from the Cambridge City Council. This dataset indicates the presence of the COVID-19 virus (measured as viral RNA particles from the novel coronavirus per ml) in municipal wastewater. The Cambridge site data here were collected as a 24-hour composite sample, which is taken weekly. The MWRA site data ere were collected as a 24-hour composite sample, which is taken daily. MWRA and Cambridge data are listed here in a single table. An interactive graph of this data is available here: https://cityofcambridge.shinyapps.io/COVID19/?tab=wastewater All areas within the City of Cambridge are captured across four separate catchment areas (or sewersheds) as indicated on the map viewable here: https://cityofcambridge.shinyapps.io/COVID19/_w_484790f7/BioBot_Sites.png. The North and West Cambridge sample also includes nearly all of Belmont and very small areas of Arlington and Somerville (light yellow). The remaining collection sites are entirely -- or almost entirely -- drawn from Cambridge households and workplaces. Data are corrected for wastewater flow rate, which adjusts for population in general. Data listed are expected to reflect the burden of COVID-19 infections within each of the four sewersheds. A lag of approximately 4-7 days will occur before new transmissions captured in wastewater data would result in a positive PCR test for COVID-19, the most common testing method used. While this wastewater surveillance tool can provide an early indication of major changes in transmission within the community, it remains an emerging technology. In assessing community transmission, wastewater surveillance data should only be considered in conjunction with other clinical measures, such as current infection rates and test positivity. Each location is selected because it reflects input from a distinct catchment area (or sewershed) as identified on the color-coded map. Viral data collected from small catchment areas like these four Cambridge sites are more variable than data collected from central collection points (e.g., the MWRA facility on Deer Island) where wastewater from dozens of communities are joined and mixed. Data from each catchment area will be impacted by daily activity among individuals living in that area (e.g., working from home vs. traveling to work) and by daytime activities that are not from residences (businesses, schools, etc.) As such, the Regional MWRA data provides a more stable measure of regional viral counts. COVID wastewater data for Boston North and Boston South regions is available at https://www.mwra.com/biobot/biobotdata.htm

  • API

    RSBS MOM: Part 2 of 2, New York State Residential Statewide Baseline Study: Survey of Multifamily Owners and Managers

    data.ny.gov | Last Updated 2019-11-15T21:58:08.000Z

    How 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 of 2 (containing: Purchasing Decisions; Washer and Dryer; and Miscellaneous); part 1 (https://data.ny.gov/d/e58s-chjh) contains: Property Characteristics; Heating and Cooling; Water Heating; Tenant Appliances; Lighting; and Common Area. 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.

  • API

    2021 Kansas City Energy and Water Consumption Benchmarking for Community-Wide Buildings

    data.kcmo.org | Last Updated 2022-08-09T17:14:11.000Z

    The 2021 Energy and Water consumption sent to the City by owners of buildings 50,000 SQFT or greater using the Energy Star Portfolio Manager tool. Data is required by the Energy Empowerment Ordinance in Kansas City, Missouri. The data was collected in 2022 and might be appended as new submissions come in.

  • API

    ENERGY STAR Certified Water Heaters

    data.energystar.gov | Last Updated 2024-10-25T13:30:40.000Z

    Certified models meet all ENERGY STAR requirements as listed in the Version 5.0 ENERGY STAR Program Requirements for Water Heaters that are effective April 18, 2023. A detailed listing of key efficiency criteria are available at https://www.energystar.gov/products/water_heaters/residential_water_heaters_key_product_criteria

  • API

    Current Descriptive Data of Municipal Wastewater Treatment Plants

    data.ny.gov | Last Updated 2019-06-10T18:04:47.000Z

    Data containing municipal wastewater treatment plant design other features, with data current through the most recent survey.

  • 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.

  • API

    Liquefaction zones (HESS)

    data.bayareametro.gov | Last Updated 2023-06-09T23:59:16.000Z

    Liquefaction zones for development of the Parcel Inventory dataset for the Housing Element Site Selection (HESS) Pre-Screening Tool. This feature set is a subset of the complete feature set for the San Francisco Bay Region. It only provides features for areas at either High or Very High susceptibility to liquefaction. The features delineate different types and ages of Quaternary deposits for the region and their susceptibility to liquefaction. The data provides a framework for the architecture and history of the Quaternary sedimentary basins, which is used in estimating earthquake shaking. **This data set represents the entire San Francisco Bay Region by combining both Open-File Report 00-444 and Open-File Report 2006-1037 data. The area covered by Open-File Report 2006-1037 was erased from Open-File Report 00-444 and the two data sets were merged. A column has been added to the attribute table to label which report each polygon was originally from. Other than this supplemental information paragraph, all the metadata is from Open-File Report 2006-1037.** This report presents a map and database of Quaternary deposits and liquefaction susceptibility for the urban core of the San Francisco Bay region. It supercedes the equivalent area of U.S. Geological Survey Open-File Report 00-444 (Knudsen and others, 2000), which covers the larger nine-county San Francisco Bay region. The report consists of (1) a spatial database, (2) two small-scale colored maps (Quaternary deposits and liquefaction susceptibility), (3) a text describing the Quaternary map and liquefaction interpretation (part 3), and (4) a text introducing the report and describing the database (part 1). All parts of the report are digital; part 1 describes the database and digital files and how to obtain them by downloading across the internet. The nine counties surrounding San Francisco Bay straddle the San Andreas fault system, which exposes the region to serious earthquake hazard (Working Group on California Earthquake Probabilities, 1999). Much of the land adjacent to the Bay and the major rivers and streams is underlain by unconsolidated deposits that are particularly vulnerable to earthquake shaking and liquefaction of water-saturated granular sediment. This new map provides a consistent detailed treatment of the central part of the 9-county region in which much of the mapping of Open-File Report 00-444 was either at smaller (less detailed) scale or represented only preliminary revision of earlier work. Like Open-File Report 00-444, the current mapping uses geomorphic expression, pedogenic soils, inferred depositional environments, and geologic age to define and distinguish the map units. Further scrutiny of the factors controlling liquefaction susceptibility has led to some changes relative to Open-File Report 00-444: particularly the reclassification of San Francisco Bay mud (Qhbm) to have only MODERATE susceptibility and the rating of artificial fills according to the Quaternary map units inferred to underlie them (other than dams ? adf). The two colored maps provide a regional summary of the new mapping at a scale of 1:200,000, a scale that is sufficient to show the general distribution and relationships of the map units but not to distinguish the more detailed elements that are present in the database. The report is the product of cooperative work by the National Earthquake Hazards Reduction Program (NEHRP) and National Cooperative Geologic Mapping Program of the U.S. Geological Survey, William Lettis & Associates, Inc. (WLA), and the California Geological Survey. An earlier version was submitted to the U.S. Geological Survey by WLA as a final report for a NEHRP grant (Witter and others, 2005). The mapping has been carried out by WLA geologists under contract to the NEHRP Earthquake Program (Grant 99-HQ-GR-0095) and by the California Geological Survey. The original reports and data are available at Open-File Report 2006-1037 (https://pubs.usgs.gov/of/2006/

  • API

    Blocks

    data.everettwa.gov | Last Updated 2024-07-06T06:23:01.000Z