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Traffic data, public transit, aviation, shipping, ride-hailing, accident records
8,151 datasets
AI-derived road surface, width, and passability metrics cover approximately 5,100 km of arterial roads in Nicaragua, produced by HeiGIT using PlanetScope satellite imagery from 2020 and 2024. The data maps motorway, trunk, primary, and secondary road classes to fill gaps where OpenStreetMap (OSM) surface tags are missing.
HeiGIT produced this dataset of AI-derived road surface, width, and passability metrics for approximately 3,400 km of arterial roads in Liberia using 2020 and 2024 PlanetScope satellite imagery. It integrates OpenStreetMap (OSM) segments with deep-learning predictions for motorway, trunk, primary, and secondary road classes to fill data gaps in national infrastructure maps.
HeiGIT generated this geospatial dataset for Sint Maarten (Dutch part) using AI analysis of PlanetScope satellite imagery from 2020 and 2024. It maps arterial road segments including motorways, trunks, primary, and secondary roads with attributes for surface type, width, and logistical accessibility. The dataset provides surface predictions for road segments where OpenStreetMap (OSM) tags were previously missing.
A source of AI-derived road surface, width, and passability metrics for approximately 5,900 km of arterial roads in Tajikistan, produced by HeiGIT using 2020 and 2024 PlanetScope satellite imagery. It covers motorway, trunk, primary, and secondary road classes, filling data gaps where OpenStreetMap (OSM) surface tags are missing for 43.6% of the network.
Delivering AI-derived road surface, width, and passability metrics for approximately 300 km of arterial roads in Curaçao, produced by HeiGIT using 2020 and 2024 PlanetScope satellite imagery. It integrates OpenStreetMap (OSM) attributes with deep-learning predictions to fill gaps where surface tags are missing or inaccurate.
Stretching across approximately 6,300 km of arterial roads in Papua New Guinea, providing AI-derived surface and width attributes generated by HeiGIT. It utilizes PlanetScope satellite imagery from 2020 and 2024 to supplement OpenStreetMap data with logistical accessibility metrics for motorway, trunk, primary, and secondary road classes.
HeiGIT produced this geospatial dataset covering approximately 100 km of arterial roads in the Northern Mariana Islands using 2020 and 2024 PlanetScope satellite imagery. It features AI-derived attributes for road surface, width, and passability to supplement missing OpenStreetMap (OSM) data. The analysis focuses specifically on motorway, trunk, primary, and secondary road classifications.
AI-derived road surface, width, and passability metrics for approximately 1,200 km of arterial roads in Belize. Produced by HeiGIT using PlanetScope satellite imagery from 2020 and 2024, it covers motorway, trunk, primary, and secondary road classifications.
A source of AI-derived road surface, width, and passability metrics for arterial roads in Niue, generated by HeiGIT using PlanetScope satellite imagery from 2020 and 2024. It covers road segments classified in OpenStreetMap as motorway, trunk, primary, and secondary, including their link classes. The data includes a Humanitarian Passability Index (HPI) to assist in logistical planning and infrastructure monitoring.
HeiGIT generated this geospatial dataset covering approximately 1,800 km of arterial roads in New Caledonia using AI analysis of PlanetScope satellite imagery from 2020 and 2024. It provides deep-learning predictions for road surface, width, and a Humanitarian Passability Index (HPI) to supplement existing OpenStreetMap (OSM) attributes. The data specifically targets motorway, trunk, primary, and secondary road classes.
HeiGIT produced this geospatial dataset providing AI-derived road surface, width, and passability metrics for Nauru's arterial road network using PlanetScope imagery from 2020 and 2024. It covers motorway, trunk, primary, and secondary road classes, offering 89.2% accuracy for surface predictions compared to 64.7% in OpenStreetMap.
A collection of AI-derived road surface types, width classes, and passability scores for approximately 800 km of arterial roads in Fiji, developed by HeiGIT. It utilizes PlanetScope satellite imagery from 2020 and 2024 to supplement OpenStreetMap data with deep-learning predictions that fill gaps in existing surface tags.
AI-derived road surface, width, and passability metrics for approximately 400 km of arterial roads in the Åland Islands, produced by HeiGIT using 2020 and 2024 PlanetScope satellite imagery. It integrates OpenStreetMap (OSM) road segments with deep-learning predictions to fill gaps in existing surface tags, achieving a validated 89.2% accuracy for surface classification.
Kiribati arterial road network data featuring AI-derived surface types, widths, and passability scores generated by HeiGIT from 2020 and 2024 PlanetScope imagery. The dataset covers approximately 100 km of roads, providing surface predictions for the 65% of segments that lack tags in OpenStreetMap.
Norfolk Island arterial road network data featuring AI-derived surface and width attributes generated by HeiGIT from 2020 and 2024 PlanetScope imagery. It provides logistical metrics for motorway, trunk, primary, and secondary road classes to support humanitarian accessibility analysis.
AI-derived road surface, width, and passability metrics for approximately 2,100 km of arterial roads in Lesotho, produced by HeiGIT using 2020 and 2024 PlanetScope imagery. The data integrates OpenStreetMap (OSM) attributes with deep-learning predictions to fill gaps in existing infrastructure records and assess logistical accessibility.
This dataset maps approximately 11,600 km of arterial roads in Zambia, providing AI-derived surface types, widths, and passability scores generated by HeiGIT from 2020 and 2024 PlanetScope satellite imagery. It covers motorway, trunk, primary, and secondary road classes, filling data gaps for over 1,200 km of the network where OpenStreetMap surface tags were previously missing.
HeiGIT generated this dataset of AI-derived road attributes for approximately 900 km of arterial roads in Guinea-Bissau using PlanetScope satellite imagery from 2020 and 2024. It provides surface type, width classifications, and humanitarian passability scores for segments classified as motorway, trunk, primary, and secondary in OpenStreetMap.
HeiGIT produced this dataset covering approximately 300 km of arterial roads in Vanuatu using AI analysis of PlanetScope satellite imagery from 2020 and 2024. It provides road surface types, width classifications, and a Humanitarian Passability Index (HPI) to supplement OpenStreetMap (OSM) data. The analysis focuses on motorway, trunk, primary, and secondary road classes.
Marshall Islands arterial road network data featuring AI-derived surface and width attributes generated by HeiGIT from 2020 and 2024 PlanetScope satellite imagery. It covers approximately 100 kilometers of roads, providing surface predictions for segments missing OpenStreetMap (OSM) surface tags. The analysis focuses on motorway, trunk, primary, and secondary road classifications.