Loading...
Loading...
Traffic data, public transit, aviation, shipping, ride-hailing, accident records
8,045 datasets
A location selection framework integrates five key criteria—location, planning, transportation, land use, and urban compatibility—for Agricultural Product Wholesale Markets. The dataset contains weights derived from Analytic Hierarchy Process and entropy methods, optimized via a Genetic Algorithm. Researcher Guizhe Xin published the supporting data in April 2026.
A 9.5 KB Excel dataset contains evaluation results for siting large-scale agricultural product wholesale markets. Guizhe Xin created this resource, which was last updated in April 2026. It presents a framework integrating GIS data, AHP, and entropy weight methods for location analysis.
Pairwise importance scores for five key criteria—location, planning, transportation, land use, and urban compatibility—used to evaluate wholesale market sites. The dataset contains weights derived from an Analytic Hierarchy Process and entropy weight method, integrated via a Genetic Algorithm. It was created by Guizhe Xin and published on figshare in April 2026.
A case study evaluates seven candidate location schemes for large-scale Agricultural Product Wholesale Markets (APWMs). The dataset supports a five-phase methodology integrating GIS data, AHP, and entropy weight methods for site selection. Guizhe Xin authored this research, which was last updated in April 2026.
Evaluation results originate from a case study applying a genetic algorithm to optimize site selection for large-scale agricultural wholesale markets. Guizhe Xin authored this dataset, which was last updated in April 2026. The 5.5 KB file contains calculated weights and rankings for candidate locations based on five key criteria.
A case study presents evaluation results for selecting large-scale Agricultural Product Wholesale Markets (APWMs). The dataset contains the outcomes of a five-phase methodology integrating GIS data, AHP, entropy weighting, and a Genetic Algorithm for weight optimization. It was authored by Guizhe Xin and published on figshare in 2026.
A unified GIS database integrates national territorial planning, road traffic planning, industrial development planning, and urban big data for location analysis. The dataset supports a five-phase location selection methodology, including region screening and weight optimization via a Genetic Algorithm. Guizhe Xin authored this research, last updated in April 2026.
A study by Guizhe Xin, published in April 2026, presents a methodology for selecting locations for Agricultural Product Wholesale Markets. The research integrates Geographic Information System (GIS) data, national planning resources, and urban big data into a unified database. It applies a Genetic Algorithm implemented in Python to optimize location selection criteria, validated through a case study with seven candidate schemes.
An Analytic Hierarchy Process (AHP) expert scoring table supporting a location selection framework for Agricultural Product Wholesale Markets (APWMs). The dataset contains integrated subjective (AHP) and objective (entropy weight) criteria weights, optimized using a Genetic Algorithm. It was created by Guizhe Xin and published on figshare in April 2026.
28 maps depict areas of Australia's maritime jurisdiction, including the continental shelf, treaties, and various maritime zones. The collection includes wall maps and regional maps for areas like the Torres Strait, Timor Sea, and Australian Antarctic Territory. Digital files in PDF format are provided by the Australian Ocean Data Network, with a last update recorded in 2026.
A 2006 printed map derived from Geoscience Australia's Australian Maritime Boundaries version 2.0 data, depicting the territorial sea baseline and maritime limits as established under the Sea and Submerged Lands Act 1973. The map, published by the Australian Ocean Data Network, describes maritime zones, boundary arrangements with neighboring countries, and the extended continental shelf as submitted to the UN. It has been superseded by a 2013 edition and is kept for historical record only.
A 112.8 MB dataset from figshare demonstrates programmable drop manipulation using pressure modulation on a superhydrophobic substrate. The method enables reversible switching between pinned and mobile drop states in real time, as reported by author Ioannis E. Markodimitrakis in April 2026. It holds promise for applications in open-surface microfluidics and adaptive liquid handling systems.
Offering AI-derived road surface, width, and passability metrics for approximately 500 km of arterial roads in the Isle of Man, produced by HeiGIT. It utilizes PlanetScope satellite imagery from 2020 and 2024 to supplement OpenStreetMap (OSM) data, focusing on motorway, trunk, primary, and secondary road classes.
HeiGIT produced this dataset of AI-derived road surface, width, and passability metrics for arterial roads in the Maldives using PlanetScope satellite imagery from 2020 and 2024. It covers approximately 100 km of road segments classified in OpenStreetMap as motorway, trunk, primary, and secondary routes. The data provides a high-accuracy alternative to existing crowdsourced tags, specifically targeting logistical accessibility.
Madagascar arterial road network data featuring AI-derived surface and width attributes for approximately 7,300 km of roads. Created by HeiGIT using 2020 and 2024 PlanetScope satellite imagery, it fills gaps for 51% of roads lacking OpenStreetMap surface tags. The dataset focuses on motorway, trunk, primary, and secondary road classes.
Offering AI-derived road attributes for approximately 500 km of arterial roads in the Falkland Islands, generated by HeiGIT using 2020 and 2024 PlanetScope satellite imagery. It includes surface type predictions, width classifications, and a Humanitarian Passability Index (HPI) for segments classified in OpenStreetMap as motorway, trunk, primary, or secondary roads.
This dataset maps approximately 3,200 km of arterial roads in Eritrea using AI-derived analysis of PlanetScope satellite imagery from 2020 and 2024. Produced by HeiGIT, it provides surface classification, width estimates, and passability scores for motorway, trunk, primary, and secondary road classes. The data supplements OpenStreetMap (OSM) by filling gaps where surface tags are missing.
Giving access to AI-derived attributes for approximately 8,700 km of arterial roads in Uruguay, produced by HeiGIT using PlanetScope satellite imagery from 2020 and 2024. It maps road surface types, width classifications, and logistical accessibility for segments classified in OpenStreetMap as motorway, trunk, primary, and secondary roads.
HeiGIT produced this dataset of AI-derived road surface, width, and passability metrics for approximately 200 km of arterial roads in Aruba using 2020 and 2024 PlanetScope satellite imagery. It integrates OpenStreetMap (OSM) segments with deep-learning predictions to fill gaps where surface tags are missing.
HeiGIT generated this geospatial dataset covering approximately 200 km of arterial roads in Sao Tome and Principe using 2020 and 2024 PlanetScope satellite imagery. It integrates OpenStreetMap (OSM) data with AI-derived predictions for road surface type, width, and logistical passability. The analysis focuses on motorway, trunk, primary, and secondary road classifications.