Big earth data analytics on Sentinel-1 and Landsat imagery in support to global human settlements mapping
Year: 2017
Type: article
Abstract: Continuous global-scale mapping of human settlements in the service of international agreements calls for massive volume of multi-source, multi-temporal, and multi-scale earth observation data. In this paper, the latest developments in terms of processing big earth observation data for the purpose of improving the Global Human Settlement Layer (GHSL) data are presented. Two experiments with Sentinel-1 and Landsat data collections were run leveraging on the Joint Research Centre Earth Observation Data and Processing Platform. A comparative analysis of the results of built-up areas extraction from different remote sensing data and processing workflows shows how the information production supported by data-intensive computing infrastructure for optimization and multiple testing can improve the output information reliability and consistency within the GHSL scope. The paper presents the processing workflows and the results of the two main experiments, giving insights into the enhanced mapping capabilities gained by analyzing Sentinel-1 and Landsat data-sets, and the lessons learnt in terms of handling and processing big earth observation data.
Source: Big Earth Data
Authors: Christina Corbane, Martino Pesaresi, Panagiotis Politis, Vasileios Syrris, Aneta J. Florczyk, Pierre Soille, Luca Maffenini, Armin Burger, Veselin Vasilev, Dario Rodriguez, Filip Sabo, Lewis Dijkstra, Thomas Kemper
Language: English
Topic: Remote Sensing and Land Use
Subfield: Geography, Planning and Development
Field: Social Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,024
OpenAlex ID: W2773484054