Global Road Inventory Project Global Roads Database¶.
The Global Road Inventory Project (GRIP) dataset was developed to provide more up-to-date and consistent global road datasets for use in global environmental and biodiversity assessment models such as GLOBIO.
GRIP datasets include global and regional vector datasets in ESRI filegeodatabase and shapefile formats, and a global road density raster dataset with a resolution of 5 arc minutes (approximately 8x8 km). Preface – Bed Length Artificial Intelligence Tutorial
The main purpose of the GRIP dataset is to provide an easy-to-use road dataset for global environmental and biodiversity scientific modeling projects. This dataset is not suitable for navigation. GRIP4 is based on a number of different sources (including OpenStreetMap), and to the extent of our ability we have verified their public availability as a standard for our research. The UNSDI-Transportation data model is used to coordinate the various source datasets. GRIP4 is provided under a Creative Commons license (CC-BY 4.0) and is free to use. Read about the methodology ShieldSquare Captcha here
Georeferencing information on road infrastructure is critical for spatial planning, socioeconomic assessment, and environmental impact analysis. However, current global road maps are often outdated or characterized by spatial bias in coverage. In the Global Road Inventory project, we collected, harmonized and integrated nearly 60 geospatial datasets on road infrastructure into the Global Roads dataset. The resulting dataset covers 222 countries and includes more than 21 million kilometers of roads, two to three times the combined length of the best current country-based global road datasets. We then related the total length of roads in each country to country area, population density, GDP, and OECD membership to form a regression model with an adjusted R2 of 0.90, and found that the highest road density was correlated with both dense population and richer countries. Applying our regression model to future population density and GDP estimates under the Shared Socioeconomic Path (SSP) scenario, we obtain a preliminary estimate of an increase in road length of 3-4.7 million km in 2050. In some of the world's last remaining wilderness regions, such as the Amazon, the Congo Basin, and New Guinea, road lengths in developing countries are projected to increase substantially. This highlights the need for accurate spatial road datasets to support strategic spatial planning to reduce road impacts on remaining native ecosystems.
Download the dataset here
Use the following credit when these datasets are cited:
Meijer, Johan R., Mark AJ Huijbregts, Kees CGJ Schotten, and Aafke M. Schipper. "Global patterns of current and future road infrastructure." Environmental Research Letters 13, no. 6 (2018): 064006.
Earth Engine Snippet¶
var grip4_africa = ee.FeatureCollection("projects/sat-io/open-datasets/GRIP4/Africa");
var grip4_central_south_america = ee.FeatureCollection("projects/sat-io/open-datasets/GRIP4/Central-South-America");
var grip4_europe = ee.FeatureCollection("projects/sat-io/open-datasets/GRIP4/Europe");
var grip4_north_america = ee.FeatureCollection("projects/sat-io/open-datasets/GRIP4/North-America");
var grip4_oceania = ee.FeatureCollection("projects/sat-io/open-datasets/GRIP4/Oceania");
var grip4_south_east_asia = ee.FeatureCollection("projects/sat-io/open-datasets/GRIP4/South-East-Asia");
var grip4_middle_east_central_asia = ee.FeatureCollection("projects/sat-io/open-datasets/GRIP4/Middle-East-Central-Asia");
Total features: 25,758,453
Shared License: This work is licensed under a Creative Commons Attribution 4.0. You are free to copy and redistribute the material in any medium or format, and to transform and build upon the material for any purpose, even commercially. You must give appropriate credit, provide a link to the license, and indicate if changes were made.
Curated by: Samapriya Roy
Keywords: global, road map, infrastructure, global roads inventory project (GRIP), SSP scenarios
Last updated: 2021-04-03