The NTI is an aggregation of structure inventory and appraisal data of tunnels located on public roads submitted by States, Federal agencies and Tribal governments in accordance with the National Tunnel Inspection Standards (NTIS) which requires each State prepare and maintain an inventory of all tunnels. The NTI data is used as a data source to assist in the oversight of the National Tunnel Inspection Program and to respond to inquiries from different entities on the Nation’s tunnels.

The National Bridge Inventory dataset is as of June 27, 2024 from the Federal Highway Administration (FHWA) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). The data describes more than 615,000 of the Nation's bridges located on public roads, including Interstate Highways, U.S. highways, State and county roads, as well as publicly-accessible bridges on Federal and Tribal lands. The inventory data present a complete picture of the location, description, classification, and general condition data for each bridge. The element data present a breakdown of the condition of each structural and bridge management element for each bridge on the National Highway System (NHS). The Recording and Coding Guide for the Structure Inventory and Appraisal of the Nation's Bridges contains a detailed description of each data element including coding instructions and attribute definitions. The Coding Guide is available at: https://doi.org/10.21949/1519105.

Data in the NBI is used to meet legislative reporting requirements and provide bridge owners, the Federal Highway Administration (FHWA) and the general public with information on the number and condition of the Nation’s bridges.The National Bridge Inventory dataset is as of June 27, 2024 from the Federal Highway Administration (FHWA) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). The data describes more than 615,000 of the Nation's bridges located on public roads, including Interstate Highways, U.S. highways, State and county roads, as well as publicly-accessible bridges on Federal and Tribal lands. The inventory data present a complete picture of the location, description, classification, and general condition data for each bridge. The element data present a breakdown of the condition of each structural and bridge management element for each bridge on the National Highway System (NHS). The Recording and Coding Guide for the Structure Inventory and Appraisal of the Nation's Bridges contains a detailed description of each data element including coding instructions and attribute definitions. The Coding Guide is available at: https://doi.org/10.21949/1519105.

Leading flood loss estimation models include Federal Emergency Management Agency’s (FEMA’s) Hazus, FEMA’s Flood Assessment Structure Tool (FAST), and (U.S.) Hydrologic Engineering Center’s Flood Impact Analysis (HEC-FIA), with each requiring different data input. No research to date has compared the resulting outcomes from such models at a neighborhood scale. This research examines the building and content loss estimates by Hazus Level 2, FAST, and HEC-FIA, over a levee-protected census block in Metairie, in Jefferson Parish, Louisiana. Building attribute data in National Structure Inventory (NSI) 2.0 are compared against “best available data” (BAD) collected at the individual building scale from Google Street View, Jefferson Parish building inventory, and 2019 National Building Cost Manual, to assess the sensitivity of input building inventory selection. Results suggest that use of BAD likely enhances flood loss estimation accuracy over existing reliance on default data in the software or from a national data set that generalizes over a broad scale. Although the three models give similar mean (median) building and content loss, Hazus Level 2 results diverge from those produced by FAST and HEC-FIA at the individual building level. A statistically significant difference in mean (median) building loss exists, but no significant difference is found in mean (median) content loss, between building inventory input (i.e., NSI 2.0 vs BAD), but both the building and content loss vary at the individual building scale due to difference in building-inventory-reported foundation height, foundation type, number of stories, replacement cost, and content cost. Moreover, building loss estimation also differs significantly by depth-damage function (DDF), for flood depths corresponding with the longest return periods, with content loss differing significantly by DDF at all return periods tested, from 10 to 500 years. Knowledge of the extent of estimated differences aids in understanding the degree of uncertainty in flood loss estimation. Much like the real estate industry uses comparable home values to appraise a home, flood loss planners should use multiple models to estimate flood-related losses. Moreover, results from this study can be used as a baseline for assessing losses from other hazards, thereby enhancing protection of human life and property.

The NBI System is the collection of bridge inspection information and costs associated with bridge replacements of structurally deficient bridges on and off the NHS. This data is collected under the auspices of the National Bridge Inspection Standards (NBIS) as prescribed by law. The NBI System collects the information that is used to determine eligibility for NHS projects, performance measure reporting, NHS penalty determination, and reporting to Congress. It supports oversight of the NBIS through various report tools, and provides data reporting that supports agency strategic goals.

The NBI is an aggregation of State, Federal agency and Tribal government bridge and associated highway data submitted to and maintained by the Federal Highway Administration (FHWA). It contains inspection and appraisal data of more than 600,000 of the Nation’s highway bridges located on public roads in accordance with the National Bridge Inspection Standards. The NBI data is used to determine the condition of the Nation’s bridges that is included in reports to Congress, as a data source for executing various sections of the Federal-aid program which involve highway bridges, for assessing the bridge penalty provisions of Title 23 United States Code (U.S.C.) section 119, as the data source for the evaluation of bridge performance measures established in Title 23 U.S.C. section 150, to assist in the oversight of the National Bridge Inspection Program, as a data source to assess and inform the condition and funding needs of highway bridges, and for strategic national defense needs.

The GIS layers and data in this resource are derived from the study on flood risk and potential solutions within a flood-prone community in South Louisiana, USA. The analysis leverages the Version 1 (V1) National Structure Inventory dataset in conjunction with the 500-year flood inundation map for Lafayette Parish. The objective was to quantify and analyze the damage and loss to buildings at both an individual and census block level due to potential flood scenarios. To calculate the potential damage, we utilized HAZUS, a nationally standardized methodology developed by the Federal Emergency Management Agency (FEMA) for estimating potential losses from disasters. HAZUS applies scientific and engineering principles to assess physical damage, economic losses, and social impacts of disasters. The resulting GIS layers represent a critical component of the spatial analysis, offering detailed insights into the spatial distribution of flood risk and the potential economic impact on the community's infrastructure. This documentation aims to provide future users with a comprehensive understanding of each GIS layer. Further details on the methodology behind each layer's production are provided in the sections below.

The National Inventory of Architectural Heritage (NIAH) is a state initiative under the administration of the Department of Housing, Local Government and Heritage and established on a statutory basis under the provisions of the Architectural Heritage (National Inventory) and Historic Monuments (Miscellaneous Provisions) Act 1999.The purpose of the NIAH is to identify, record, and evaluate the post-1700 architectural heritage of Ireland, uniformly and consistently as an aid in the protection and conservation of the built heritage. NIAH surveys provide the basis for the recommendations of the Minister for Housing, Local Government and Heritage to the planning authorities for the inclusion of particular structures in their Record of Protected Structures (RPS). This dataset is provided for re-use in a number of ways and the technical options are outlined below. For a live and current view of the data, please use the web services or the data extract tool in the Historic Environment Viewer. The NIAH also provide an Open Data snapshot of its national dataset in CSV as a bulk data download. It contains all the Ministerial Recommendations published to date and is updated as surveys are published. Open Data Bulk Data Downloads (version date: 11/10/2023) The NIAH Survey data is provided as a national download in Comma Separated Value (CSV) format. This format can be easily integrated into a number of software clients for re-use and analysis. The Longitude and Latitude coordinates are also provided to aid its re-use in web mapping systems, however, the ITM easting/northings coordinates should be quoted for official purposes. GIS Web Service APIs (live views): For users with access to GIS software please note that the NIAH data is also available as spatial data web services. By accessing and consuming the web service users are deemed to have accepted the Terms and Conditions. The web services are available at the URL endpoints advertised below: NIAH Feature Service: https://services-eu1.arcgis.com/HyjXgkV6KGMSF3jt/arcgis/rest/services/NIAHBuildingsOpenData/FeatureServer Historic Environment Viewer - Query Tool The "Query" tool can alternatively be used to selectively filter and download the data represented in the Historic Environment Viewer. The instructions for using this tool in the Historic Environment Viewer are detailed in the associated Help file: https://www.archaeology.ie/sites/default/files/media/pdf/HEV_UserGuide_v01.pdf

Graph and download economic data for Existing Single-Family Home Sales: Housing Inventory (HSFINVUSM495N) from May 2024 to May 2025 about 1-unit structures, inventories, family, sales, housing, and USA.

Bridges-Rail in the United States According to The National Bridge Inspection Standards published in the Code of Federal Regulations (23 CFR 650.3), a bridge is: A structure including supports erected over a depression or an obstruction, such as water, highway, or railway, and having a track or passageway for carrying traffic or other moving loads. Each bridge was captured as a point which was placed in the center of the "main span" (highest and longest span). For bridges that cross navigable waterways, this was typically the part of the bridge over the navigation channel. If no "main span" was discernable using the imagery sources available, or if multiple non contiguous main spans were discernable, the point was placed in the center of the overall structure. Bridges that are sourced from the National Bridge Inventory (NBI) that cross state boundaries are an exception. Bridges that cross state boundaries are represented in the NBI by two records. The points for the two records have been located so as to be within the state indicated by the NBI's [STATE_CODE] attribute. In some cases, following these rules did not place the point at the location at which the bridge crosses what the user may judge as the most important feature intersected. For example, a given bridge may be many miles long, crossing nothing more than low lying ground for most of its length but crossing a major interstate at its far end. Due to the fact that bridges are often high narrow structures crossing depressions that may or may not be too narrow to be represented in the DEM used to orthorectify a given source of imagery, alignment with ortho imagery is highly variable. In particular, apparent bridge location in ortho imagery is highly dependent on collection angle. During verification, TechniGraphics used imagery from the following sources: NGA HSIP 133 City, State or Local; NAIP; DOQQ imagery. In cases where "bridge sway" or "tall structure lean" was evident, TGS attempted to compensate for these factors when capturing the bridge location. For instances in which the bridge was not visible in imagery, it was captured using topographic maps at the intersection of the water and rail line. TGS processed 784 entities previously with the HSIP Bridges-Roads (STRAHNET Option - HSIP 133 Cities and Gulf Coast). These entities were added into this dataset after processing. No entities were included in this dataset for American Samoa, Guam, Hawaii, the Commonwealth of the Northern Mariana Islands, or the Virgin Islands because there are no main line railways in these areas. At the request of NGA, text fields in this dataset have been set to all upper case to facilitate consistent database engine search results. At the request of NGA, leading and trailing spaces were trimmed from all text fields. At the request of NGA, all diacritics (e.g., the German umlaut or the Spanish tilde) have been replaced with their closest equivalent English character to facilitate use with database systems that may not support diacritics. The currentness of this dataset is given by the publication date which is 09/02/2009. A more precise measure of currentness cannot be provided since this is dependent on the NBI and the source of imagery used during processing.

Abstract

DHS, FIMA, FEMA’s Response Geospatial Office, Oak Ridge National Laboratory, and the U.S. Geological Survey collaborated to build and maintain the nation’s first comprehensive inventory of all structures larger than 450 square feet for use in Flood Insurance Mitigation, Emergency Preparedness and Response.

FEMA and our federal partners identified a need to create a building outline (the polygon representation of the structure) and an updated address database for the nation that could help ensure that critical infrastructure and residential buildings are accounted for in the disaster response and recovery decision-making processes.

To respond effectively, we need to understand population and the built environment—where people live, work and the critical infrastructure they rely on.

Many residential structures have an address where the occupants receive mail, but the address is not associated with the structure’s physical location. This can happen when people use a Post Office box, or when the mailbox is located in a central location, which is often the case in mobile home parks, apartment buildings, and rural communities.

The lack of structure information can limit our ability to adequately characterize a disaster’s potential impacts since parts of the community are missed by the predictive models. Furthermore, the homes that lack a footprint with an associated address are occupied by the most vulnerable in the community, delaying aid to those who are most in need. How? Since the location and address are not coupled, FEMA and our response partners can struggle to determine which damaged home is associated with the address presented by the survivor seeking assistance.

Methodology

To create the building outline inventory, FEMA, in conjunction with DHS Science and Technology, partnered with the Oak Ridge National Laboratory (ORNL) to extract the outlines via commercially available satellite imagery. We then worked to determine the building’s usage or occupancy type (e.g., residential, commercial, industrial) which is noted as an attribute for each structure.

In the past, geographers have relied on satellite imagery as a high-coverage and low-cost data source to create building-location inventories; however, identifying individual buildings is labor-intensive and had been difficult to automate due to large variations of building appearances. Our processes included some new machine learning techniques and a collection method to obtain data from multiple sources, including from local governments who agreed to share it, and open data from the National Geospatial-Intelligence Agency (NGA).

Structures adjacent to the project area are described and photographed in relation to the project boundaries. Basic data gathered for each structure included location, function, and age of the structure. For structures that are older than 50 years, information that documents the history of ownership, architectural description, modifications, integrity, associated outbuildings and landscape features was also collected. For structures that appear to be potentially eligible for inclusion in the National Register, a DOT Structure Inventory Form, modified from the OPRHP form, was completed and a detailed architectural description is included. There are five structures in the project area that appear to meet the criteria for eligibility to the National Register.

abstract: Non-government users are no longer able to directly download current NID data. NID data was plotted using the Latitude and Longitude fields from an Excel Spreadsheet provided by NID. The dataset was clipped to only include dams in Calfornia near the coast. There are a total of 735 dams included in this dataset.The National Inventory of Dams (NID) is a congressionally authorized database, which documents dams in the U.S. and its territories. The NID was most recently reauthorized in the Dam Safety Act of 2006. The current NID, published in 2010, includes information on 84,000 dams that are more than 25 feet high, hold more than 50 acre-feet of water, or are considered a significant hazard if they fail. The NID is maintained and published by USACE, in cooperation with the Association of State Dam Safety Officials (ASDSO), the states and territories, and federal dam-regulating agencies. The database contains information about the dams location, size, purpose, type, last inspection, regulatory facts, and other technical data. The information contained in the NID is updated approximately every two years.Extracted from the USACE National Inventory of Dams, this is the 2010 version of the NID database that has been approved for public online display.Coastal Dams - NID 2010

The National Bridge Inventory dataset is as of June 27, 2024 from the Federal Highway Administration (FHWA) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). The data describes more than 615,000 of the Nation's bridges located on public roads, including Interstate Highways, U.S. highways, State and county roads, as well as publicly-accessible bridges on Federal and Tribal lands. The inventory data present a complete picture of the location, description, classification, and general condition data for each bridge. The element data present a breakdown of the condition of each structural and bridge management element for each bridge on the National Highway System (NHS). The Recording and Coding Guide for the Structure Inventory and Appraisal of the Nation's Bridges contains a detailed description of each data element including coding instructions and attribute definitions. The Coding Guide is available at: https://doi.org/10.21949/1519105.

The NBI System is the collection of bridge inspection information and costs associated with bridge replacements of structurally deficient bridges on and off the NHS. This data is collected under the auspices of the National Bridge Inspection Standards (NBIS) as prescribed by law. The NBI System collects the information that is used to determine eligibility for NHS projects, performance measure reporting, NHS penalty determination, and reporting to Congress. It supports oversight of the NBIS through various report tools, and provides data reporting that supports agency strategic goals.

description: National Capital Region Network American Chestnut Inventory Data Summary 2014. This dataset represents the first four years of forest vegetation monitoring (2006-2009) by the National Capital Region Network (NCRN) Inventory and Monitoring Program. Data was collected from 400 forest plots randomly scattered throughout the NCRN. Each of the plots was visited a single time and will be revisited between 2010 and 2013. Given the large number of plots and numerous measurements made on each plot, it is not practcal to report all of the data. Instead, summary data related to forest structure and plant community composition is reported for the region as a whole and each individual park. This data is reported in the following categories: Trees, Shrubs, Herbacious Vegetation, Vines and Conditions (including Pests and Diseases). Additionally, a list of the sampling events is included along with a species list by growth habit and size class for each plot.; abstract: National Capital Region Network American Chestnut Inventory Data Summary 2014. This dataset represents the first four years of forest vegetation monitoring (2006-2009) by the National Capital Region Network (NCRN) Inventory and Monitoring Program. Data was collected from 400 forest plots randomly scattered throughout the NCRN. Each of the plots was visited a single time and will be revisited between 2010 and 2013. Given the large number of plots and numerous measurements made on each plot, it is not practcal to report all of the data. Instead, summary data related to forest structure and plant community composition is reported for the region as a whole and each individual park. This data is reported in the following categories: Trees, Shrubs, Herbacious Vegetation, Vines and Conditions (including Pests and Diseases). Additionally, a list of the sampling events is included along with a species list by growth habit and size class for each plot.

This fieldwork was to inventory the concession cabin area in Badlands National Park that is to be disturbed by the replacement and relocation of sewer lines. The survey and inventory took place on July 23rd, 1987 and was conducted on foot, maximizing opportunities to observe the bare ground.

The Wisconsin In-Service Structures GIS Layer provides a spatial representation of all in-service bridges and structures across the state. This layer includes detailed attributes such as inventory data, inspection records, and National Bridge Inventory (NBI) ratings. The dataset will be refreshed monthly. For the most up-to-date and detailed information, users can access the HSIS application via https://trust.dot.state.wi.us/hsi/HSIController.

This dataset is a subset (containing records of the dams present in the state of Arizona) of the National Inventory of Dams (NID). The NID database contains information on 79,777 dams throughout the United States and its territories. The National Inventory of Dams began in 1972 with the National Dam Inspection Act and continues to be updated with the Water Resources Development Act of 1986 and 1996. The Corps of Engineers is authorized to maintain and publish the inventory. Significant changes have been made to the inventory data over the last 20 years, including the addition of new dam records and removal of breached dams, and duplicate dam records. The data is submitted from all 50 states, US territories and 16 federal agencies. The NID includes all high and significant hazard potential classification dams. Low hazard potential dams must exceed 25 feet in height and15 acre-feet in storage or exceed 50 acre-feet in storage and 6 feet in height. This inclusion criteria is applied to all dams submitted to the NID. The Corps calculates two fields, NID height and NID storage, which are the maximum values in their multiple respective fields and these values are used in the inclusion criteria process. Since the last update in 2001, one new field, submit_date, has been added. This field represents the date the agency submitted the data to the Corps of Engineers. All 109th congressional information contained in the NID was populated based on a GIS query of the dam coordinates. If a dam has no coordinates (noted as -999.999, -999.999 in the database), no congressional information is associated with that dam.Tabular data was downloaded from the National Inventory of Dams (https://nid.sec.usace.army.mil) for Arizona. Layer was created by the Map and Geospatial Hub using the coordinate information contained in the tabular data.

The NBI System is the collection of bridge inspection information and costs associated with bridge replacements of structurally deficient bridges on and off the NHS. This data is collected under the auspices of the National Bridge Inspection Standards (NBIS) as prescribed by law. The NBI System collects the information that is used to determine eligibility for NHS projects, performance measure reporting, NHS penalty determination, and reporting to Congress. It supports oversight of the NBIS through various report tools, and provides data reporting that supports agency strategic goals.