The total surface area of the apartments and commercial buildings that were certified by Energy Star increased slightly in 2024. During the past decade, the surface area of buildings that received a certificate from Energy Star has fluctuated significantly, reaching a peak in 2018, when the buildings with a certificate that year amounted to over *********** square feet.

Graph and download economic data for New Privately-Owned Housing Units Under Construction: Units in Buildings with 5 Units or More (UNDCON5MUSA) from Jan 1970 to May 2025 about 5-unit structures +, construction, new, private, housing, and USA.

Graph and download economic data for New Privately-Owned Housing Units Started: Units in Buildings with 5 Units or More (HOUST5F) from Jan 1959 to May 2025 about 5-unit structures +, housing starts, privately owned, housing, and USA.

This dataset denotes HUD subsidized Multifamily Housing properties excluding insured hospitals with active loans. HUD’s Multifamily Housing property portfolio consist primarily of rental housing properties with five or more dwelling units such as apartments or town houses, but can also include nursing homes, hospitals, elderly housing, mobile home parks, retirement service centers, and occasionally vacant land. HUD provides subsidies and grants to property owners and developers in an effort to promote the development and preservation of affordable rental units for low-income populations, and those with special needs such as the elderly, and disabled. The portfolio can be broken down into two basic categories: insured, and assisted. The three largest assistance programs for Multifamily Housing are Section 8 Project Based Assistance, Section 202 Supportive Housing for the Elderly, and Section 811 Supportive Housing for Persons with Disabilities. The Multifamily property locations represent the approximate location of the property. The locations of individual buildings associated with each property are not depicted here.

This dataset contains multifamily housing sites in the City of Detroit meeting the following criteria:

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. 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.

HUD’s Multifamily Housing property portfolio consist primarily of rental housing properties with five or more dwelling units such as apartments or town houses, but can also include nursing homes, hospitals, elderly housing, mobile home parks, retirement service centers, and occasionally vacant land. HUD provides subsidies and grants to property owners and developers in an effort to promote the development and preservation of affordable rental units for low-income populations, and those with special needs such as the elderly, and disabled. The portfolio can be broken down into two basic categories: insured, and assisted. The three largest assistance programs for Multifamily Housing are Section 8 Project Based Assistance, Section 202 Supportive Housing for the Elderly, and Section 811 Supportive Housing for Persons with Disabilities. The Multifamily property locations represent the approximate location of the property. The locations of individual buildings associated with each property are not depicted here. Location data for HUD-related properties and facilities are derived from HUD's enterprise geocoding service. While not all addresses are able to be geocoded and mapped to 100% accuracy, we are continuously working to improve address data quality and enhance coverage. Please consider this issue when using any datasets provided by HUD. When using this data, take note of the field titled “LVL2KX” which indicates the overall accuracy of the geocoded address using the following return codes: ‘R’ - Interpolated rooftop (high degree of accuracy, symbolized as green) ‘4’ - ZIP+4 centroid (high degree of accuracy, symbolized as green) ‘B’ - Block group centroid (medium degree of accuracy, symbolized as yellow) ‘T’ - Census tract centroid (low degree of accuracy, symbolized as red) ‘2’ - ZIP+2 centroid (low degree of accuracy, symbolized as red) ‘Z’ - ZIP5 centroid (low degree of accuracy, symbolized as red) ‘5’ - ZIP5 centroid (same as above, low degree of accuracy, symbolized as red) Null - Could not be geocoded (does not appear on the map) For the purposes of displaying the location of an address on a map only use addresses and their associated lat/long coordinates where the LVL2KX field is coded ‘R’ or ‘4’. These codes ensure that the address is displayed on the correct street segment and in the correct census block. The remaining LVL2KX codes provide a cascading indication of the most granular level geography for which an address can be confirmed. For example, if an address cannot be accurately interpolated to a rooftop (‘R’), or ZIP+4 centroid (‘4’), then the address will be mapped to the centroid of the next nearest confirmed geography: block group, tract, and so on. When performing any point-in polygon analysis it is important to note that points mapped to the centroids of larger geographies will be less likely to map accurately to the smaller geographies of the same area. For instance, a point coded as ‘5’ in the correct ZIP Code will be less likely to map to the correct block group or census tract for that address. In an effort to protect Personally Identifiable Information (PII), the characteristics for each building are suppressed with a -4 value when the “Number_Reported” is equal to, or less than 10. To learn more about Multifamily Housing visit: https://www.hud.gov/program_offices/housing/mfh, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov.Data Dictionary: DD_HUD Assisted Multifamily Properties Date of Coverage: 12/2023

The construction of multifamily homes in the U.S. is expected to fall sharply in 2024 and 2025. This would come after a period of significant growth between 2019 and 2023, when it peaked at ****** billion U.S. dollars. New residential construction in the United States decreased in 2023.

Out of a total of 7.8 million housing units in New York City, approximately 3.6 million units were single family detached homes and 350 unites were single family attached homes in 2021. Unlike single family homes which were mostly owner occupied, housing in multifamily buildings was predominantly renter occupied. In buildings with 50 or more housing units, one million out of 1.3 million units were rented.

This dataset contains multifamily housing sites in the City of Detroit meeting the following criteria:Each site has been completed since 2019 or is currently under construction.At least half of the housing units in each site are affordable.The total amount invested in developing these properties as of April 11, 2024 exceeds $1,000,000,000. For further details on this data, and a full list of multifamily housing construction sites in the City of Detroit since 2016, please refer to Multifamily Housing Construction Sites on the Open Data Portal.

The total number of residential properties located within an area as identified by Maryland Property View. It is important to note that that this indicator is a count of properties (single family homes, condominiums, and duplexes) and that a property can be comprised of multiple housing units. Source: MdProperty View Years Available: 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020

The value of new private non-residential buildings put in place in the United States has doubled between 2014 and 2024. That last year, U.S. expenditure on new private non-residential buildings peaked at over *** billion U.S. dollars. Due to the start of the COVID-19 pandemic, the value of construction of commercial buildings dropped in 2020. However, the total private construction put in place in the U.S. increased during that period.

HUD’s Multifamily Housing property portfolio consist primarily of rental housing properties with five or more dwelling units such as apartments or town houses, but can also include nursing homes, hospitals, elderly housing, mobile home parks, retirement service centers, and occasionally vacant land. HUD provides subsidies and grants to property owners and developers in an effort to promote the development and preservation of affordable rental units for low-income populations, and those with special needs such as the elderly, and disabled. The portfolio can be broken down into two basic categories: insured, and assisted. The three largest assistance programs for Multifamily Housing are Section 8 Project Based Assistance, Section 202 Supportive Housing for the Elderly, and Section 811 Supportive Housing for Persons with Disabilities. The Multifamily property locations represent the approximate location of the property. The locations of individual buildings associated with each property are not depicted here. Location data for HUD-related properties and facilities are derived from HUD's enterprise geocoding service. While not all addresses are able to be geocoded and mapped to 100% accuracy, we are continuously working to improve address data quality and enhance coverage. Please consider this issue when using any datasets provided by HUD. When using this data, take note of the field titled “LVL2KX” which indicates the overall accuracy of the geocoded address using the following return codes: ‘R’ - Interpolated rooftop (high degree of accuracy, symbolized as green) ‘4’ - ZIP+4 centroid (high degree of accuracy, symbolized as green) ‘B’ - Block group centroid (medium degree of accuracy, symbolized as yellow) ‘T’ - Census tract centroid (low degree of accuracy, symbolized as red) ‘2’ - ZIP+2 centroid (low degree of accuracy, symbolized as red) ‘Z’ - ZIP5 centroid (low degree of accuracy, symbolized as red) ‘5’ - ZIP5 centroid (same as above, low degree of accuracy, symbolized as red) Null - Could not be geocoded (does not appear on the map) For the purposes of displaying the location of an address on a map only use addresses and their associated lat/long coordinates where the LVL2KX field is coded ‘R’ or ‘4’. These codes ensure that the address is displayed on the correct street segment and in the correct census block. The remaining LVL2KX codes provide a cascading indication of the most granular level geography for which an address can be confirmed. For example, if an address cannot be accurately interpolated to a rooftop (‘R’), or ZIP+4 centroid (‘4’), then the address will be mapped to the centroid of the next nearest confirmed geography: block group, tract, and so on. When performing any point-in polygon analysis it is important to note that points mapped to the centroids of larger geographies will be less likely to map accurately to the smaller geographies of the same area. For instance, a point coded as ‘5’ in the correct ZIP Code will be less likely to map to the correct block group or census tract for that address. In an effort to protect Personally Identifiable Information (PII), the characteristics for each building are suppressed with a -4 value when the “Number_Reported” is equal to, or less than 10. To learn more about Multifamily Housing visit: https://www.hud.gov/program_offices/housing/mfh, for questions about the spatial attribution of this dataset, please reach out to us at GISHelpdesk@hud.gov.Data Dictionary: DD_HUD Assisted Multifamily Properties Date of Coverage: 12/2023

The majority of the housing stock in the United States is single-family detached houses. Of the total ***** million housing units in 2023, about **** million were detached homes and *** million were attached single-family homes. In comparison, roughly **** million units were in multifamily buildings.

The value of new residential construction put in place in the United States increased to ****** in 2024, and it is expected to increase again in 2025. These figures refer to the construction of single-family and multi-family housing, as well as to the value of the home improvements segment, which includes additions, alterations and major replacements. Non-residential construction spending is rose significantly in 2024.

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. The Multifamily Performance Program (MPP) serves residential buildings with five or more units. Funds are targeted at energy efficiency measures that help to reduce on-site electricity, oil, natural gas, steam, and propane energy demand and energy consumption in multi-unit residential buildings. All buildings receive program support for energy assessments to identify and determine cost-effective measures, expected energy savings, and installation costs. Our dataset is then compiled from the information. The dataset includes information collected throughout the project application process and energy assessments from several NYSERDA-funded programs, including Multifamily Performance Program-Existing Buildings, Multifamily Performance Program-New Construction, and Multifamily Performance Program-Energy Star Pilot. The Multifamily Residential Existing and New Construction Energy Efficiency Projects Reported by NYSERDA: Beginning 2005 dataset includes the following data points for completed projects: Project Name, Program Type, Building Address1, Building City, Building ZIP, Property County, Electric Utility, Gas Utility, Market Type, Number of Buildings, Number of Units, Application NYSERDA Approved Date, Project Completed Date, Funding Amount, Proposed Install Unit Cost, Total Estimated Electric Savings, Total Estimated Annual Energy Savings, and Total Estimated Electric Demand Reduction (MW). Information about the Projects’ measures, measure category, and estimated energy savings by fuel type can be found in the Multifamily Residential Existing and New Construction Energy Efficiency Measures Reported by NYSERDA: Beginning 2005 dataset. Reported savings account for interactive effects between measures.

Analysis of ‘RSBS MOM: Multifamily On-Site Survey, Measure Level, New York State Residential Statewide Baseline Study’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/d63f4215-97e1-41ac-bc56-a1a3f89cce76 on 12 February 2022.

--- Dataset description provided by original source is as follows ---

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.

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.

--- Original source retains full ownership of the source dataset ---

The dataset contains data on the buildings in the residential quarters of Düsseldorf from the small-scale housing market observation since 2014. On the basis of newly defined residential quarters, the small-scale housing market observation enables a detailed spatial analysis of the status quo on the housing market. It includes data since 2014 and is updated annually. Each residential district is assigned to a residential district type. These types are derived from the construction typology and the construction age as well as the different land use. The residential quarters thus characterise the different, small-scale sub-markets in Düsseldorf. In your own datasets you will find geo-information on the residential district boundaries and key tables for the residential quarters. The interactive offer of the data can be found on the website of the Office for Statistics and Elections at: https://www.duesseldorf.de/statistik-und-wahlen/statistik-und-stadtforschung/analysen/wohnungsmarktbeobachtung.html Here you can also find descriptions and the data collection for housing market observation in the file formats PDF and XLS. The data on the buildings in the residential quarters of Düsseldorf are divided into the total number of buildings and four periods for the year of construction: before 1949, 1949-1969, 1970-1989 and after 1990. A distinction is also made between single and two-family houses (EZFH) and multi-family houses (MFH). Here too, the total number and then the numbers of the different periods are listed. The files contain the following column information: Residential area: Number of the quarter Total stock of residential buildings: Total number of residential buildings Existing residential building built before 1949: Number of residential buildings built before 1949 Existing residential building Bj. 1949 to 1969: Number of residential buildings built 1949-1969 Existing residential building Bj. 1970-1989: Number of residential buildings 1970-1989 Existing residential building built after 1990: Number of residential buildings built after 1990 Total stocks of EZFH: Total number of single and two-family houses Stock of EZFH before 1949: Number of single and two-family houses built before 1949 Stock of EZFH year. 1949 to 1969: Number of single and two-family houses built 1949-1969 Stock of EZFH year. 1970-1989: Number of single and two-family houses 1970-1989 Existing EZFH year after 1990: Number of single and two-family houses built after 1990 Total stock MFH: Total number of multi-family houses Stock MFH before 1949: Number of multi-family houses built in 1949 Stock MFH Bj. 1949 to 1969: Number of multi-family houses built 1949-1969 Stock MFH Bj. 1970-1989: Number of multi-family houses 1970-1989 Stock MFH year after 1990: Number of multi-family houses built in 1990 Note: The allocation of the districts to the residential quarters results from the district numbering. The first two places give the district and the district. The subsequent digits indicate the consecutive numbering of the residential quarters.

The value of public residential construction spending in the United States has risen significantly from 2019 to 2024. In 2019, the public sector spent nearly **** billion U.S. dollars on residential construction projects, while that figure reached **** billion U.S. dollars in 2024. The overall value of new residential construction put in place in the U.S. is expected to increase over the coming years.

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.