- What is the Land Area?
- What is the Population Count?
- What is the Population Density?
- What is the Percent who did not finish the 9th grade?
- What is the Median Earnings?
- What is the Number of Employees?
- What is the Crime incident count?
- What is the Population Rate of Change?
- What is the High School Graduation Rate?
- What is the Median Female Earnings?
The water area of Albuquerque, NM was 2 in 2018.
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.
Geographic and Area Datasets Involving Albuquerque, NM
- API data.ny.gov | Last Updated 2022-01-25T19:49:54.000Z
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.
- API data.ny.gov | Last Updated 2019-06-10T18:02:35.000Z
The New York State Department of Environmental Conservation (DEC) maintains a network of Public Fishing Right parking areas along trout streams in New York. This dataset represents the locations and information about those parking areas. Links to PDF maps of the actual Public Fishing Rights along the streams are available as part of the data set.
- API data.cityofchicago.org | Last Updated 2013-02-28T15:29:13.000Z
RSBS MOM: Part 2 of 2, New York State Residential Statewide Baseline Study: Survey of Multifamily Owners and Managersdata.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 data.energystar.gov | Last Updated 2022-05-18T13:34:22.000Z
Certified 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.
Growing Resources for Growing Cities: Density and the Cost of Municipal Public Services in Brazil, Chile, and Mexicomydata.iadb.org | Last Updated 2017-10-02T20:04:39.000Z
This dataset collects information on municipal expenditures, water-sewerage-and trash collection service coverage, and basic socioeconomic characteristics at municipal level, for two census waves (2000; 2010) for all municipalities of Brazil, Chile, and Mexico.<br><br><b>Click here to access the data: https://mydata.iadb.org/d/hkh9-ch92</b></br></br>
- API data.lacity.org | Last Updated 2020-11-30T17:22:16.000Z
Green infrastructure is designed to capture and infiltrate or filter stormwater runoff through natural systems. This dataset is used in combination with precipitation numbers to update the stormwater dashboard (in progress) and Sustainable City pLAn. It is refreshed as new projects are created.
- API data.cityofchicago.org | Last Updated 2021-09-09T20:00:25.000Z
The 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)
RSBS MOM: Part 1 of 2, New York State Residential Statewide Baseline Study: Survey of Multifamily Owners and Managersdata.ny.gov | Last Updated 2019-11-15T22:04:57.000Z
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 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.
- API data.calgary.ca | Last Updated 2021-11-04T15:59:57.000Z
(Note: Updated inundation maps for 1:2 to 1:1000 floods are available from Alberta Environment and Parks (2020). The new draft maps can be viewed here: https://floods.alberta.ca/?app_code=FI&mapType=Draft) These inundation maps show whether a property is at risk for various sized river floods. The size of flood shown on this map has a 1/100 or a 1% chance of occurring in any year. The three distinct types of inundation shown on the maps are: o Inundation - Area flooded overland due to riverbank overtopping. o Isolated - Low lying areas that will not be wet from riverbank overtopping, but may experience groundwater seepage or stormwater backup. o Potential failure of flood protection barrier - Low lying areas that could be flooded if an existing permanent flood protection barrier were to fail. The flood areas shown were mapped in 2015 jointly by Alberta Environment and Parks and the City of Calgary, using the best available hydrologic and hydraulic data and models. As such, the flooding shown reflects 2015 conditions, hydrology and topography. The effects of mitigation measures (changes to reservoirs/dams or barriers) built since 2015 are not included. There is uncertainty inherent in predicting the effects of flood events, and this uncertainty increases for floods with less than a 1% chance of occurrence in any year. Any use of this data must recognizing the uncertainty with regards to the exact location and extent of flooding. More information on flood mapping for Calgary is available at https://calgary.ca/flood For Calgary's River Flood story, see: https://maps.calgary.ca/RiverFlooding/