Next Article in Journal
Optical Flow-Based Detection of Gas Leaks from Pipelines Using Multibeam Water Column Images
Previous Article in Journal
Coarse-Resolution Satellite Images Overestimate Urbanization Effects on Vegetation Spring Phenology
Open AccessArticle

Assessing OpenStreetMap Completeness for Management of Natural Disaster by Means of Remote Sensing: A Case Study of Three Small Island States (Haiti, Dominica and St. Lucia)

1
New Light Technologies Inc., Washington, DC 20005, USA
2
Global Facility for Disaster Reduction and Recovery/World Bank, Washington, DC 20433, USA
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(1), 118; https://doi.org/10.3390/rs12010118
Received: 26 November 2019 / Revised: 18 December 2019 / Accepted: 25 December 2019 / Published: 1 January 2020
Over the last few decades, many countries, especially islands in the Caribbean, have been challenged by the devastating consequences of natural disasters, which pose a significant threat to human health and safety. Timely information related to the distribution of vulnerable population and critical infrastructure is key for effective disaster relief. OpenStreetMap (OSM) has repeatedly been shown to be highly suitable for disaster mapping and management. However, large portions of the world, including countries exposed to natural disasters, remain incompletely mapped. In this study, we propose a methodology that relies on remotely sensed measurements (e.g., Visible Infrared Imaging Radiometer Suite (VIIRS), Sentinel-2 and Sentinel-1) and derived classification schemes (e.g., forest and built-up land cover) to predict the completeness of OSM building footprints in three small island states (Haiti, Dominica and St. Lucia). We find that the combinatorial effects of these predictors explain up to 94% of the variation of the completeness of OSM building footprints. Our study extends the existing literature by demonstrating how remotely sensed measurements could be leveraged to evaluate the completeness of the OSM database, especially in countries with high risk of natural disasters. Identifying areas that lack coverage of OSM features could help prioritize mapping efforts, especially in areas vulnerable to natural hazards and where current data gaps pose an obstacle to timely and evidence-based disaster risk management. View Full-Text
Keywords: OpenStreetMap; OSM; OpenStreetMap coverage; disaster management; remote sensing OpenStreetMap; OSM; OpenStreetMap coverage; disaster management; remote sensing
Show Figures

Graphical abstract

MDPI and ACS Style

Goldblatt, R.; Jones, N.; Mannix, J. Assessing OpenStreetMap Completeness for Management of Natural Disaster by Means of Remote Sensing: A Case Study of Three Small Island States (Haiti, Dominica and St. Lucia). Remote Sens. 2020, 12, 118.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop