DescriptionOpenFlights Airports Database contains over 70,000 airports. The data as generated by from DAFIF (October 2006 cycle) and OurAirports, plus timezone information from EarthTools. All DST information added manually. Significant revisions and additions made by the users of OpenFlights. LimitationsBlank.AttributesOBJECTID: Assigned by WWF. Unique identifier id: Unique OpenFlights identifier for this airport ident: ICAO airport code or location indicator type: Type of the airport. Value "airport" for air terminals, "station" for train stations, "port" for ferry terminals and "unknown" if not known. In airports.csv, only type=airport is included name: Name of airport. May or may not contain the city name latitude_d: Latitude in decimal degrees longitude_: Longitude in decimal degrees elevation_: Altitude in feet continent: Continent code where the airport is located. Cross-reference to ISO 3166-1 codes here iso_countr: Country code where airport is located. Cross-reference to ISO 3166-1 codes here iso_region: Region code where airport is located. Cross-reference to ISO 3166-1 municipali: Name of the municipality where the airport is located scheduled_: Availability of airline schedule data service gps_code: GPS airport code iata_code: IATA airport code, also know as an IATA location identifier, IATA station code or simply a location identifier local_code: Local airport code. Can be the same IATA code. home_link: Website of the airport in question wikipedia_: Source of Airport Data keywords x: X location in the original coordinate system of the database (WGS 1984) y: Y location in the original coordinate system of the database (WGS 1984)

This map presents transportation data, including highways, roads, railroads, and airports for the world.

The map was developed by Esri using Esri highway data; Garmin basemap layers; HERE street data for North America, Europe, Australia, New Zealand, South America and Central America, India, most of the Middle East and Asia, and select countries in Africa. Data for Pacific Island nations and the remaining countries of Africa was sourced from OpenStreetMap contributors. Specific country list and documentation of Esri's process for including OSM data is available to view.

The Geographic Names Information System (GNIS) actively seeks data from and partnerships with Government agencies at all levels and other interested organizations. The GNIS is the Federal standard for geographic nomenclature. The U.S. Geological Survey developed the GNIS for the U.S. Board on Geographic Names, a Federal inter-agency body chartered by public law to maintain uniform feature name usage throughout the Government and to promulgate standard names to the public. The GNIS is the official repository of domestic geographic names data; the official vehicle for geographic names use by all departments of the Federal Government; and the source for applying geographic names to Federal electronic and printed products of all types. See http://geonames.usgs.gov for additional information.

This is a custom Story Map design not based on a Story Map app template.

Airport Runway Surveillance Market Outlook

The global airport runway surveillance market size is expected to grow remarkably, from USD 1.2 billion in 2023 to an impressive USD 3.5 billion by 2032, exhibiting a CAGR of 12.5% during the forecast period. The growth of this market is primarily driven by increasing global air traffic, heightened security concerns, and the need for advanced technological integration in airport operations.

One of the key factors fueling the growth of the airport runway surveillance market is the relentless increase in global air traffic. With the rise in passenger numbers and cargo volumes, airports around the world are under pressure to enhance their operational efficiency and ensure the safety and security of both passengers and aircraft. This necessitates the adoption of advanced surveillance technologies capable of providing real-time monitoring and quick incident response. Consequently, there has been a significant uptick in investments toward the modernization of airport infrastructure, which is expected to drive market growth.

Another critical driver of this market is the heightened security concerns at airports. Given the growing threat of terrorism and other security breaches, airports are implementing stringent surveillance measures to ensure the safety of passengers, staff, and infrastructure. Advanced runway surveillance systems, such as radar, LiDAR, and thermal imaging, play a vital role in detecting unauthorized access and potential threats, thereby enhancing overall security. The integration of these technologies helps in preventing incidents and mitigating risks, thus bolstering market demand.

Technological advancements are also playing a significant role in the expansion of the airport runway surveillance market. The advent of sophisticated surveillance solutions that leverage artificial intelligence (AI), machine learning (ML), and the Internet of Things (IoT) has revolutionized the way airport operations are managed. These technologies enable more accurate and efficient monitoring, predictive maintenance, and proactive threat detection, which are essential for modern airport management. As a result, there is a growing trend towards the adoption of smart airport solutions, further propelling market growth.

Regionally, North America currently holds a substantial share of the airport runway surveillance market, driven by significant investments in airport infrastructure and the presence of major technology providers. However, Asia Pacific is expected to witness the highest growth rate during the forecast period, attributed to the rapid expansion of air travel, the construction of new airports, and rising government initiatives to enhance airport security. This regional growth is indicative of broader global trends that favor the adoption of advanced surveillance technologies to ensure safety and efficiency in airport operations.

The integration of the Runway Foreign Object Automatic Detection System is becoming increasingly critical in the airport runway surveillance market. This system utilizes advanced sensors and AI-driven analytics to automatically detect and alert operators to the presence of foreign objects on runways. By providing real-time data and rapid response capabilities, it significantly enhances the safety and efficiency of airport operations. The adoption of such systems is driven by the need to prevent potential hazards that could compromise aircraft safety. As airports continue to prioritize safety, the demand for these automatic detection systems is expected to rise, contributing to the overall growth of the market.

Technology Analysis

The airport runway surveillance market by technology is segmented into radar, LiDAR, video surveillance, and thermal imaging. Radar technology has long been a cornerstone of airport surveillance due to its ability to detect objects and movements with high precision, even in adverse weather conditions. The reliability and robustness of radar systems make them indispensable for runway monitoring and aircraft tracking. With continuous advancements in radar technology, including better resolution and range, its application in airport surveillance is expected to remain significant, driving steady market growth.

LiDAR technology, which uses laser pulses to create high-resolution 3D maps, is gaining traction in airport runway surveillance. Its ability to provide detailed and accurate

8831 Active Global Airport buyers list and Global Airport importers directory compiled from actual Global import shipments of Airport.

The data include the coastal ports and airport distribution in the Belt and Road region. The data are from the Natural Earth global port and airport data. The data are cut according to the standard map of the 65 countries along the Belt and road, and further corrected, then the distribution of the ports and airports in the area along the B&R is obtained. This data is mainly one to analyze the B&R area's important spatial layout and main characteristics of the transportation facilities, and to get other attributes data of port and airport in the following research, including the throughput of different port cargo types, the incoming and outgoing throughput, the number of docks and berths, the number of passengers on the airport, the data of the flights and routes of ports and airports, we can get further understanding of the spatial differentiation of the distribution of ports and airports in the B&R region.

This vector tile layer provides a customized world basemap that is uniquely symbolized. It is optimized to display special areas of interest (AOIs) that have been created and edited by Community Maps contributors. These special areas of interest include landscaping features such as grass, trees, and rock and sports amenities like tennis courts, football and baseball field lines, and more. This vector tile layer is built using the same data sources used for the World Topographic Map and other Esri basemaps.

Link to landing page referenced by identifier. Service Protocol: Link to landing page referenced by identifier. Link Function: information-- dc:identifier.

6247 Global import shipment records of Airport with prices, volume & current Buyer's suppliers relationships based on actual Global export trade database.

This point shapefile represents airports in Pakistan. This layer is part of Global Map version 2. The drainage and Transportation layers version 2 are prepared by using the digital 1:1000k data of nepal. The Global Map Nepal version 1.0 Boundaries layer was developed using The Digital Map 200000. Updating the data of version 1.0 using 1:500,000 District Map series and 1:1,000,000 International Map series developed the Global Map Nepal version 1.1 Boundary layer. Updating the Global Map Nepal version 1.1 using 1:1,000,000 Topographic Maps and other information developed the Global Map Nepal version 2.0 Boundary layer, which is corresponding to the merger of municipalities as of April 1, 2010. The Global Map Nepal version 1.0 Population center layer was developed using The 1:1,000,000 Chart International series. Updating the data of version 1.0 using The 1:500,000 District Map series and 1:1,000,000 International Map series developed the Global Map Nepal version 1.1 Population center layer. Updating the Global Map Nepal version 1.1 developed the Global Map Nepal version 2.0 Population center layer, which is corresponding to the merger of municipalities as of April 1, 2010. (Because the built-up area data of the Global Map Nepal is corresponding to the location of each municipality.)

This point shapefile represents airports in Mozambique. The Global Map Mozambique version 2 was developed to update Global Map Mozambique version 1 based on Global Map Specifications version 2.1. The Global Map Mozambique version 1.0 was developed from the shapefiles Map 1:250.000 and 1:50.000 developed 1996-1999.

Here's a non exhaustive map of what I think are some of the hardest places to land a plane around the world!

Also took info from www.forbes.com/sites/jimdobson/2018/11/08/the-17-most-dangerous-airports-in-the-world-and-why-you-must-experience-them/?sh=3e0adae12a8f

interestingengineering.com/top-10-scariest-airports-in-the-world

www.aerotime.aero/aerotime.extra/23073-23-extremely-dangerous-airports

This point shapefile represents airports in Senegal. The Global Map Senegal drainage version 2.0 was developed by using the Global Map Senegal version 1.0 and the International map serie at the scale 1000000 and the map scale 500 000. The Global Map Senegal version 1.0 Transportation layer was developed using The 1:1,000,000 Chart International series and The Digital Map 200000. Updating the data of version 1.0 using The 1:500,000 District Map series and 1:1,000,000 International Map series developed the Global Map Senegal version 1.1 Transportation layer. Updating the Global Map Senegal version 1.1 using 1:1,000,000 Topographic Maps developed the Global Map Senegal version 2.0 Transportation layer. 1.1: 2006-12-13, Version 2.0: 2012-07-25. The Global Map Senegal version 2.0 Boundaries layer was developed using the Digital Map 200000. The Global Map Senegal version 2.0 Population center layer was developed using The 1:200,000 Topographic Map. The Release of Global map Senegal Elevation layer series are as follows: Version 1.0: 2000-11-28, Version 1.1: 2006-12-13, Version 2.0: 2012-07-25

This point shapefile represents airports in Serbia. Boundaries of administrative units are collected from different sources (cadastral maps, basic state map and topographic maps of various scales). Positional accuracy has value between 1m to 300m based on source for data collecting. Global Map Serbia version 2.1 Drainage, Population center and Transportation layers were created using the Topographic map 1:300 000. Updating the data using The vector national database (scale 1:1 000 000) and orthophoto images. Digital Terrain Model with 30m grid is produced using terrain elevation data obtained under "Production of digital orthophoto maps for the Republic of Serbia". In order to satisfied Global Map Specification data resampling is done to 1km resolution. Global Map Serbia version 2.0 Land Cover was created using the vector data from European Environment Agency (EEA) - The data were collected and processed using remote sensing satellite images.

This vector tile layer provides a customized world basemap that is uniquely symbolized. It is optimized to display special areas of interest (AOIs) that have been created and edited by Community Maps contributors. These special areas of interest include landscaping features such as grass, trees, and rock and sports amenities like tennis courts, football and baseball field lines, and more. This vector tile layer is built using the same data sources used for the World Topographic Map and other Esri basemaps.

213 Active Global Airport suppliers, manufacturers list and Global Airport exporters directory compiled from actual Global export shipments of Airport.

Current METAR weather stations and associated weather conditions based on Meteorological Terminal Aviation Routine Weather Report (METAR) data collected globally from either airports or permanent weather observation stations by NOAA’s NWS Aviation Weather Center (http://www.aviationweather.gov/metar). IGEMS reads this source data and updates the layer every 10 minutes.

This layer is a component of Interior Geospatial Emergency Management System (IGEMS) General Data.

This map presents the geospatial locations and additional information for global tide monitoring stations, and U.S. stream gages, weather stations and DOI managed lands. This map is part of the Interior Geospatial Emergency Management System (IGEMS) and is supported by the DOI Office of Emergency Management. This map contains data from a variety of public data sources, including non-DOI data, and information about each of these data providers, including specific data source and update frequency is available at: http://igems.doi.gov.

© DOI Office of Emergency Management

This point shapefile represents airports in Albania. The Global Map Albania version 2 was developed based on Global Map Specifications version 2.2. The source data of vector layers were a Digital Map 1:25000 and Orthophoto, map image made in 1985 and orthophoto made in 2008. The data source of Elevation layer was developed using orthophoto 2000 year. The data source of Land Use and Vegetation layer were developed using orthophoto 2012 year. IRS, SPOT and RapidEye satellite images, dual coverage, orthophotos (2012), topographic maps for making Land Cover.

This point shapefile represents airports in Lebanon. The Global Map Lebanon version 2 was developed to update Global Map Lebanon version 1 based on Global Map Specifications version 2.1.