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.

This USGS data release is intended to provide a baselayer of information on likely stream crossings throughout the United States. The geopackage provides likely crossings of infrastructure and streams and provides observed information that helps validate modeled crossings and build knowledge about associated conditions through time (e.g. crossing type, crossing condition). Stream crossings were developed by intersecting the 2020 United States Census Bureau Topologically Integrated Geographic Encoding and Referencing (TIGER) U.S. road lines with the National Hydrography Dataset High Resolution flowlines. The current version of this data release specifically focuses on road stream crossings (i.e. TIGER2020 Roads) but is designed to support additions of other crossing types that may be included in future iterations (e.g. rail). In total 6,608,268 crossings are included in the dataset and 496,564 observations from the U.S. Department of Transportation, Federal Highway Administration's 2019 National Bridge Inventory (NBI)are included to help identify crossing types of bridges and culverts. This data release also contains Python code that documents methods of data development.

The Railroad Bridges dataset was compiled on October 14, 2022 from the Federal Railroad Administration (FRA) and is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics (BTS) National Transportation Atlas Database (NTAD). A railroad bridge is defined as â Railroad bridge means any structure with a deck, regardless of length, which supports one or more railroad tracks, or any other undergrade structure with an individual span length of 10 feet or more located at such a depth that it is affected by live loads.â based on the Code of Federal Regulations (49 CFR Part 237). The FRA does not have a mandate to inspect railroad bridges: these inspections are required by the owner of the track. The FRA will use this railroad bridge dataset to determine the number of bridges per railroad, state, etc. and will assist in determining priority field activities.

About this dataset

Context

The dataset tabulates the Twin Bridges population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Twin Bridges. The dataset can be utilized to understand the population distribution of Twin Bridges by age. For example, using this dataset, we can identify the largest age group in Twin Bridges.

Key observations

The largest age group in Twin Bridges, MT was for the group of age 60 to 64 years years with a population of 32 (14.68%), according to the ACS 2019-2023 5-Year Estimates. At the same time, the smallest age group in Twin Bridges, MT was the 10 to 14 years years with a population of 0 (0%). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Twin Bridges is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Twin Bridges total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Twin Bridges Population by Age. You can refer the same here

The National Bridge Inventory Elements 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 Specification for the National Bridge Inventory Bridge Elements contains a detailed description of each data element including coding instructions and attribute definitions. The Coding Guide is available at: https://doi.org/10.21949/1519106.

The United State Federal Highway Administration (FHWA) collects and updates information on the nation's bridges that are located on public roads, including both interstate and US highways, state and county roads, and publicly accessible bridges on federal land. This collection of information is known as the National Bridge Inventory (NBI), and it has been captured electronically since 1972. While parts of the data were first made available to the public in 1997, it wasn't until 2007 that the FWHA decided to make all elements of the NBI database publicly available.

This NBI data set contains 135 variables describing over 600,000 bridges. Variables describe the location, structure, maintenance, usage, status, and other aspects of the bridges. An extremely detailed (124 page) pdf guide to the variables, codes, and other metadata on the NBI can be found here:

https://www.fhwa.dot.gov/bridge/mtguide.pdf

Acknowledgements

The Department of Transportation FHWA collects and provides the NBI data as authorized by statue 23, U.S.C. 151

This data set was downloaded from the Homeland Infrastructure Foundation here:

https://hifld-dhs-gii.opendata.arcgis.com/datasets/94c41e96db0d4b85b9eb622923e0a0e8_0

Inspiration

This data set contains variables describing the cost of bridge (ITEM94) and roadway (ITEM95) improvement in thousands of dollars. How many improvement projects could be completed for $20B?

Use of the NBI data also enables FHWA to satisfy its requirements under 23 U.S.C. 144, which mandate the inventory, classification, cost estimates for replacement or rehabilitation, and assignment of replacement or rehabilitation priorities for all highway bridges on all public roads. Can you come up with better cost estimates and classifications? For example, in the absence of additional information, FHWA recommends using 10% of the bridge cost as a roadway improvement cost estimator.

Using Latitude and Longitude data and operational status (ITEM41), can you find any bridges to nowhere?

These data are high-resolution bathymetry (riverbed elevation) and depth-averaged velocities in ASCII format, generated from hydrographic and velocimetric surveys of the Missouri River near highway bridge structures on U.S. Highway 40 near St. Louis, Missouri, in 2010, 2011, and 2016. Hydrographic data were collected using a high-resolution multibeam echosounder mapping system (MBMS), which consists of a multibeam echosounder (MBES) and an inertial navigation system (INS) mounted on a marine survey vessel. Data were collected as the vessel traversed the river along planned survey lines distributed throughout the reach. Data collection software integrated and stored the depth data from the MBES and the horizontal and vertical position and attitude data of the vessel from the INS in real time. Data processing required computer software to extract bathymetry data from the raw data files and to summarize and map the information. Velocity data were collected using an acoustic Dopp ...

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.

A public view dataset containing point locations of bridges that are under the care and management of the Canal & River Trust.Audience: Public, Internal/ExternalExtent: England and WalesUpdate regime: Attributes weekly, geometry upon request.Source: Canal & River TrustNoticed a data error? Please contact us.

These data are high-resolution bathymetry (riverbed elevation) and depth-averaged velocities in ASCII format, generated from hydrographic and velocimetric surveys of the Missouri River near near highway bridge structures on U.S. Highway 69 in Kansas City, Missouri, in 2010, 2011, and 2017. Hydrographic data were collected using a high-resolution multibeam echosounder mapping system (MBMS), which consists of a multibeam echosounder (MBES) and an inertial navigation system (INS) mounted on a marine survey vessel. Data were collected as the vessel traversed the river along planned survey lines distributed throughout the reach. Data collection software integrated and stored the depth data from the MBES and the horizontal and vertical position and attitude data of the vessel from the INS in real time. Data processing required computer software to extract bathymetry data from the raw data files and to summarize and map the information. Velocity data were collected using an acoustic Doppler current profiler (ADCP) mounted on a survey vessel equipped with a differential global positioning system (DGPS). Data were collected as the vessel traversed the river along planned transect lines distributed throughout the reach. Velocity data were processed using the Velocity Mapping Toolbox (Parsons and other, 2013), and smoothed using neighboring nodes.

Bridges are defined in 335.074, F.S. as the following: Bridges are defined as having an opening measured along the center of the roadway of more than 20 feet between under croppings of the abutments or spring lines of arches or extreme ends of openings for multiple boxes and those bridges consisting of multiple pipes where the clear distance between openings is less than half of the smaller contiguous opening. This dataset is maintained by the Transportation Data & Analytics office (TDA). The source spatial data for this hosted feature layer was created on: 07/05/2025.For more details please review the FDOT RCI Handbook Download Data: Enter Guest as Username to download the source shapefile from here: https://ftp.fdot.gov/file/d/FTP/FDOT/co/planning/transtat/gis/shapefiles/bridges.zip

About this dataset

Context

The dataset tabulates the population of Twin Bridges by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Twin Bridges. The dataset can be utilized to understand the population distribution of Twin Bridges by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Twin Bridges. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Twin Bridges.

Key observations

Largest age group (population): Male # 65-69 years (17) | Female # 60-64 years (25). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Twin Bridges population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Twin Bridges is shown in the following column.
• Population (Female): The female population in the Twin Bridges is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Twin Bridges for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Twin Bridges Population by Gender. You can refer the same here

Polylines representing bridges throughout Pierce County with attribution provided from mobility data maintained by Pierce County. Please read metadata for additional information (https://matterhorn.co.pierce.wa.us/GISmetadata/pdbtrans_bridge_lines.html). Any data download constitutes acceptance of the Terms of Use (https://matterhorn.co.pierce.wa.us/Disclaimer/PierceCountyGISDataTermsofUse.pdf).

New York City bridge structure conditions and ratings.

About this dataset

Context

The dataset tabulates the data for the Twin Bridges, MT population pyramid, which represents the Twin Bridges population distribution across age and gender, using estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. It lists the male and female population for each age group, along with the total population for those age groups. Higher numbers at the bottom of the table suggest population growth, whereas higher numbers at the top indicate declining birth rates. Furthermore, the dataset can be utilized to understand the youth dependency ratio, old-age dependency ratio, total dependency ratio, and potential support ratio.

Key observations

• Youth dependency ratio, which is the number of children aged 0-14 per 100 persons aged 15-64, for Twin Bridges, MT, is 19.3.
• Old-age dependency ratio, which is the number of persons aged 65 or over per 100 persons aged 15-64, for Twin Bridges, MT, is 71.9.
• Total dependency ratio for Twin Bridges, MT is 91.2.
• Potential support ratio, which is the number of youth (working age population) per elderly, for Twin Bridges, MT is 1.4.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group for the Twin Bridges population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Twin Bridges for the selected age group is shown in the following column.
• Population (Female): The female population in the Twin Bridges for the selected age group is shown in the following column.
• Total Population: The total population of the Twin Bridges for the selected age group is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Twin Bridges Population by Age. You can refer the same here

About this dataset

Context

The dataset presents the distribution of median household income among distinct age brackets of householders in Twin Bridges. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varies among householders of different ages in Twin Bridges. It showcases how household incomes typically rise as the head of the household gets older. The dataset can be utilized to gain insights into age-based household income trends and explore the variations in incomes across households.

Key observations: Insights from 2023

In terms of income distribution across age cohorts, in Twin Bridges, the median household income stands at $70,500 for householders within the 45 to 64 years age group, followed by $66,429 for the 25 to 44 years age group. Notably, householders within the 65 years and over age group, had the lowest median household income at $48,750.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2023-inflation-adjusted dollars.

Age groups classifications include:

• Under 25 years
• 25 to 44 years
• 45 to 64 years
• 65 years and over

Variables / Data Columns

• Age Of The Head Of Household: This column presents the age of the head of household
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific age group

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Twin Bridges median household income by age. You can refer the same here

This group of layers was developed by the Balmoral Group and contains the transportation and evacuation route layers as defined in 380.093(2)(a) Florida Statutes. The layers were sourced from various public State of Florida and Federal Sources. Transportation and evacuation routes include airports, bridges, bus terminals, ports, major roadways, marinas, rail facilities, and railroad bridges. Typically, the data are utilized in various vulnerability assessments in evaluating the exposure and sensitivity from combined events of sea level rise, precipitation, major storms, and flooding. The data will also be used in efforts to complete a comprehensive statewide assessment for the State of Florida.

These data are high-resolution bathymetry (riverbed elevation) and depth-averaged velocities in comma-delimited table format, generated from hydrographic and velocimetric surveys near highway bridge structures over the Missouri River between Kansas City and St. Louis, Missouri, May 19–26, 2021. Hydrographic data were collected using a high-resolution multibeam echosounder mapping system (MBMS), which consists of a multibeam echosounder (MBES) and an inertial navigation system (INS) mounted on a marine survey vessel. Data were collected as the vessel traversed the river along planned survey lines distributed throughout the reach. Data collection software integrated and stored the depth data from the MBES and the horizontal and vertical position and attitude data of the vessel from the INS in real time. Data processing required specialized computer software to extract bathymetry data from the raw data files and to summarize and map the information. Velocity data for the surveys were collected using an acoustic Doppler current profiler (ADCP) mounted on a survey vessel equipped with a differential global positioning system (DGPS). Velocity data were collected for all sites except site 14 at Lexington due to a faulty ADCP unit. Data were collected as the vessel traversed the river along seven planned transect lines distributed throughout the reach. Velocity data were processed using the Velocity Mapping Toolbox (Parsons and others, 2013), and smoothed using neighboring nodes. There is a zip file for the 8 surveyed sites available for download containing the bathymetric data and depth-averaged velocities. The files follow the format of "site-##_MissouriRiver_HWY#_2021-05.zip", where "site-##" is the site number from 14 to 21 and "HWY#" is the highway type and route number. The zip files each contain two comma-delimited text files, one with the bathymetry and uncertainty data and one with the depth-averaged velocity data, as well as associated metadata and thumbnail images. Reference cited: Parsons, D.R., Jackson, P.R., Czuba, J.A., Engel, F.L., Rhoads, B.L., Oberg, K.A., Best, J.L., Mueller, D.S., Johnson, K.K., and Riley, J.D., 2013, Velocity Mapping Toolbox (VMT) A process and visualization suite for moving-vessel ADCP measurements: Earth Surface Processes and Landforms, v. 38, no. 11, p. 1244-1260. [Also available at https://doi.org/10.1002/esp.3367.] First posted May 10, 2023, ver. 1.0 Revised July 31, 2023, ver. 2.0

About this dataset

Context

The dataset tabulates the population of Twin Bridges by race. It includes the population of Twin Bridges across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of Twin Bridges across relevant racial categories.

Key observations

The percent distribution of Twin Bridges population by race (across all racial categories recognized by the U.S. Census Bureau): 92.68% are white, 6.34% are American Indian and Alaska Native and 0.98% are some other race.

https://i.neilsberg.com/ch/twin-bridges-mt-population-by-race.jpeg" alt="Twin Bridges population by race">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the Twin Bridges
• Population: The population of the racial category (excluding ethnicity) in the Twin Bridges is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of Twin Bridges total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Twin Bridges Population by Race & Ethnicity. You can refer the same here

These data are high-resolution bathymetry (riverbed elevation) in ASCII format, generated from hydrographic surveys near six highway bridge structures over the Gasconade River in central Missouri. These sites were surveyed in June 2017 to help identify possible effects from extreme flooding on May 1-2, 2017. At the five downstream sites, hydrographic data were collected using a high-resolution multibeam echosounder mapping system (MBMS), which consists of a multibeam echosounder (MBES) and an inertial navigation system (INS) mounted on a marine survey vessel. Data were collected as the vessel traversed the river along planned survey lines distributed throughout the reach. Data collection software integrated and stored the depth data from the MBES and the horizontal and vertical position and attitude data of the vessel from the INS in real time. At the upstream-most site, hydrographic data were collected using a high-resolution multibeam scanning echosounder system (MSES), whi ...