The Bureau of Transportation Statistics (BTS) Border Crossing Data provide summary statistics for inbound crossings at the U.S.-Canada and the U.S.-Mexico border at the port level. Data are available for trucks, trains, containers, buses, personal vehicles, passengers, and pedestrians. Border crossing data are collected at ports of entry by U.S. Customs and Border Protection (CBP). The data reflect the number of vehicles, containers, passengers or pedestrians entering the United States. CBP does not collect comparable data on outbound crossings. Users seeking data on outbound counts may therefore want to review data from individual bridge operators, border state governments, or the Mexican and Canadian governments.

The statistic shows the total population in Canada from 2020 to 2024, with projections up until 2030. In 2024, the total population in Canada amounted to about 41.14 million inhabitants. Population of Canada Canada ranks second among the largest countries in the world in terms of area size, right behind Russia, despite having a relatively low total population. The reason for this is that most of Canada remains uninhabited due to inhospitable conditions. Approximately 90 percent of all Canadians live within about 160 km of the U.S. border because of better living conditions and larger cities. On a year to year basis, Canada’s total population has continued to increase, although not dramatically. Population growth as of 2012 has amounted to its highest values in the past decade, reaching a peak in 2009, but was unstable and constantly fluctuating. Simultaneously, Canada’s fertility rate dropped slightly between 2009 and 2011, after experiencing a decade high birth rate in 2008. Standard of living in Canada has remained stable and has kept the country as one of the top 20 countries with the highest Human Development Index rating. The Human Development Index (HDI) measures quality of life based on several indicators, such as life expectancy at birth, literacy rate, education levels and gross national income per capita. Canada has a relatively high life expectancy compared to many other international countries, earning a spot in the top 20 countries and beating out countries such as the United States and the UK. From an economic standpoint, Canada has been slowly recovering from the 2008 financial crisis. Unemployment has gradually decreased, after reaching a decade high in 2009. Additionally, GDP has dramatically increased since 2009 and is expected to continue to increase for the next several years.

Number of vehicles travelling between Canada and the United States, by trip characteristics, length of stay and type of transportation. Data available monthly.

Number of personal vehicle passengers, train passengers, bus passengers, and pedestrians entering the United States from Canada. The Bureau of Transportation of Statistics releases incoming border crossing statistics using data collected at ports of entry by U.S. Customs and Border Protection.

Monthly Border Wait times in the land mode broken down by port of entry. Note: The CBSA’s Border Wait Times dataset contain data intended for travellers entering Canada. A US-bound historical border wait times dataset is available from the U.S. Department of Transportation’s Bureau of Transportation Statistics. Please visit their Border Crossing/Entry Data web page to access their dataset.

The international land border between the United States and Canada is the longest in the world at almost 8,900 kilometers. It includes the border between Canada and the continental U.S. as well as the border between Alaska and northern Canada.

Analysis of ‘Border Crossing Entry Data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/656e0b2d-60f1-49e8-a3a7-073602d441a2 on 12 February 2022.

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

The Bureau of Transportation Statistics (BTS) Border Crossing Data provide summary statistics for inbound crossings at the U.S.-Canada and the U.S.-Mexico border at the port level. Data are available for trucks, trains, containers, buses, personal vehicles, passengers, and pedestrians. Border crossing data are collected at ports of entry by U.S. Customs and Border Protection (CBP). The data reflect the number of vehicles, containers, passengers or pedestrians entering the United States. CBP does not collect comparable data on outbound crossings. Users seeking data on outbound counts may therefore want to review data from individual bridge operators, border state governments, or the Mexican and Canadian governments.

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

Number of trucks entering the United States from Canada. The Bureau of Transportation of Statistics releases incoming border crossing statistics using data collected at ports of entry by U.S. Customs and Border Protection.

This dataset includes a reference baseline used by the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics for the sheltered north coast of Alaska coastal region between the U.S. Canadian Border to the Hulahula River for the time period 1947 to 2010. This baseline layer serves as the starting point for all transects cast by the DSAS application and can be used to establish measurement points used to calculate shoreline-change rates.

This dataset includes a reference baseline used by the Digital Shoreline Analysis System (DSAS) to calculate rate-of-change statistics for the exposed north coast of Alaska coastal region between the U.S. Canadian Border to the Hulahula River for the time period 1947 to 2010. This baseline layer serves as the starting point for all transects cast by the DSAS application and can be used to establish measurement points used to calculate shoreline-change rates.

description: This dataset consists of long-term (~63 years) shoreline change rates for the north coast of Alaska between the U.S. Canadian Border and the Hulahula River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2010. A reference baseline was used as the originating point for the orthogonal transects cast by the DSAS software. The transects intersect each shoreline establishing measurement points, which are then used to calculate long-term rates.; abstract: This dataset consists of long-term (~63 years) shoreline change rates for the north coast of Alaska between the U.S. Canadian Border and the Hulahula River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2010. A reference baseline was used as the originating point for the orthogonal transects cast by the DSAS software. The transects intersect each shoreline establishing measurement points, which are then used to calculate long-term rates.

The data and programs replicate tables and figures from "The Canadian border and the US dollar: The impact of exchange rate changes on US retailers", by Chen, Devereux and Lapham. Please see the ReadMe file for additional details.

description: This dataset includes shorelines from 63 years ranging from 1947 to 2010 for the north coast of Alaska between the U.S. Canadian Border and the Hulahula River. Shorelines were compiled from topographic survey sheets (T-sheets; National Oceanic and Atmospheric Administration (NOAA)), aerial orthophotographs (U.S. Geological Survey (USGS), National Aeronautics and Space Administration (NASA), satellite imagery (U.S. Fish and Wildlife Service (USFWS), State of Alaska), and lidar elevation data (USGS). Historical shoreline positions serve as easily understood features that can be used to describe the movement of beaches through time. These data are used to calculate rates of shoreline change for the U.S. Geological Survey's National Assessment of Shoreline Change Project. Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3. DSAS uses a measurement baseline method to calculate rate-of-change statistics. Transects are cast from the reference baseline to intersect each shoreline, establishing measurement points used to calculate shoreline change rates.; abstract: This dataset includes shorelines from 63 years ranging from 1947 to 2010 for the north coast of Alaska between the U.S. Canadian Border and the Hulahula River. Shorelines were compiled from topographic survey sheets (T-sheets; National Oceanic and Atmospheric Administration (NOAA)), aerial orthophotographs (U.S. Geological Survey (USGS), National Aeronautics and Space Administration (NASA), satellite imagery (U.S. Fish and Wildlife Service (USFWS), State of Alaska), and lidar elevation data (USGS). Historical shoreline positions serve as easily understood features that can be used to describe the movement of beaches through time. These data are used to calculate rates of shoreline change for the U.S. Geological Survey's National Assessment of Shoreline Change Project. Rates of long-term and short-term shoreline change were generated in a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3. DSAS uses a measurement baseline method to calculate rate-of-change statistics. Transects are cast from the reference baseline to intersect each shoreline, establishing measurement points used to calculate shoreline change rates.

This dataset shows active grain (corn, soybeans, wheat, and sorghum) rail tariff rates to the Mexico border for a number of U.S. locations, border crossings, car types, and shipment sizes for BNSF, Union Pacific, and Kansas City Southern (KCS). These rates are Rule 11 rates, where a through rate from a U.S. origin to a Mexico destination is divided into a rate from a U.S. origin to the border and a rate from the border to a Mexico destination. The U.S. railroads began reporting only Rule 11 rates to the border in January 2022 following the implementation of a VAT tax on the Mexican portion of the rail shipment. This dataset only contains rates on the U.S. to-the-border portion of the shipment.

The rates are collected from the BNSF, UP, and KCS websites. The railroads do not update the tariffs on defined interval, but do typically have at least one update a year before that commodity's harvest season. The tariff rates are joined to fuel surcharges that are updated monthly. A row in the dataset represents the active tariff rate for that shipment type (route, size, etc.) and the fuel surcharge for that railroad in a particular month. In the case where a tariff rate is changed mid-month, the row is an average of any rates that were active during that month.

Fuel surcharges are published by the railroads on a monthly, per-mile basis and are collected separately from the tariff documents (See USDA's fuel surcharge data at https://agtransport.usda.gov/d/f883-g4tq). To compute a per car fuel surcharge, the U.S. origin to the border rail route distance is approximated using the Department of Transportation's National Rail Network Lines (NARL) dataset and a shortest-path computation.

KCS is now CPKC, but KCS rates are still reported separately at https://web.kcsouthern.com/AgricultureTariff/Default.aspx.

The dataset is intended to capture most of the published tariffs for corn, soybean, and wheat shipments to Mexico. However, some routes and tariff updates may not be included.

This dataset consists of long-term (70 years) shoreline change rates for the mainland coast of Alaska sheltered by barrier islands from the U.S. Canadian Border to the Hulahula River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 5.1, an ArcGIS extension developed by the U.S. Geological Survey. Long-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1947 and 2017. A reference baseline was used as the originating point for the orthogonal transects cast by the DSAS software. The transects intersect each shoreline establishing measurement points, which are then used to calculate long-term rates.

This dataset consists of short-term (~32 years) shoreline change rates for the north coast of Alaska between the U.S. Canadian Border and the Hulahula River. Rate calculations were computed within a GIS using the Digital Shoreline Analysis System (DSAS) version 4.3, an ArcGIS extension developed by the U.S. Geological Survey. Short-term rates of shoreline change were calculated using a linear regression rate-of-change method based on available shoreline data between 1978 and 2010. A reference baseline was used as the originating point for the orthogonal transects cast by the DSAS software. The transects intersect each shoreline establishing measurement points, which are then used to calculate short-term rates.

Border Crossing/Entry Data provides summary statistics for incoming crossings at the U.S.-Canadian and the U.S.-Mexican border at the port level. Data are available for trucks, trains, containers, buses, personal vehicles, passengers, and pedestrians.

Total value of merchandise freight for United States exports to and imports from Canada. The Bureau of Transportation Statistics releases freight data using a special tabulation of official international trade statistics that are collected by the U.S. Customs and Border Protection and processed and validated by the U.S. Census Bureau, Foreign Trade Division.

The international boundary data featured in this shapefile consists of the boundary between the United States and Canada and the United States and Mexico. Each country's section is administered independently. The United States and Canada border data was provided by the International Boundary Commission, United States and Canada (IBC). The International Boundary and Water Commission (IBWC) provided the United States and Mexico section of the border data. Geospatial data files provided individually by the IBC and IBWC were used to re-align the Census Bureau's MAF/TIGER System data for the agency's representation of the international boundaries of United States with Canada and Mexico. The Census Bureau's MAF/TIGER System and the IBWC source file data for the portion of the United States and Mexico border featured a gap between Cameron County, Texas and the three-mile limit in the Gulf of Mexico. The National Oceanic and Atmospheric Administration Coast Survey Office's representation of the United States and Mexico boundary used to fill this gap.Download: https://www2.census.gov/geo/tiger/TIGER2023/INTERNATIONALBOUNDARY/tl_2023_us_internationalboundary.zipMetadata: https://meta.geo.census.gov/data/existing/decennial/GEO/GPMB/TIGERline/Current_19115/tl_2023_us_internationalboundary.shp.iso.xml

The International Travel Survey (ITS) is an ongoing survey conducted by Statistics Canada since the 1920s to meet the requirements of the Canadian System of National Accounts (Balance of Payments (BOP). Through the years, the need for detailed characteristics of travellers for market research and industry planning was gradually incorporated in the survey. Today, the ITS provides a full range of statistics on the volume of international travellers and detailed characteristics of their trips such as expenditures, activities, places visited and length of stay. The ITS covers both Canadian residents returning from trips outside Canada and international visitors to Canada. In addition to fulfilling BOP requirements, the ITS is also being used by the Tourism Satellite Account (TSA), Customs Canada, the Canadian tourism Commission (CTC), provincial tourism agencies, the United States Department of Commerce and a number of private sector industries. The ITS is also used for reporting to international organizations such as the World Tourism Organization (WTO), the Organization for Economic Co-operation and Development and the Pacific-Asia Tourism Association.