Paper Info
Title
Multimodal Fusion of Mobility Demand Data and Remote Sensing Imagery for Urban Land-Use and Land-Cover Mapping
Abstract
This paper aims at exploring the potentiality of the multimodal fusion of remote sensing imagery with information coming from mobility demand data in the framework of land-use mapping in urban areas. After a discussion on the function of mobility demand data, a probabilistic fusion framework is developed to take advantage of remote sensing and transport data, and their joint use for urban land-use and land-cover applications in urban and surrounding areas. Two different methods are proposed within this framework, the first based on pixelwise probabilistic decision fusion and the second on the combination with a region-based multiscale Markov random field. The experimental validation is conducted on a case study associated with the city of Genoa, Italy.
Year
DOI
Venue
2022
10.3390/rs14143370
REMOTE SENSING
Keywords
DocType
Volume
urban land-use mapping, data fusion, Markov random fields, transport zones, mobility demand
Journal
14
Issue
ISSN
Citations 
14
2072-4292
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Martina Pastorino100.34
Federico Gallo201.35
Angela Di Febbraro300.34
Gabriele Moser491976.92
Nicola Sacco500.34
Sebastiano B. Serpico674964.86