This work introduces two feature fusion techniques that exploit previously developed algorithms for urban extent extraction from multispectral and SAR spaceborne data, adapting them to the joint use of Sentinel-1 (S1) and Sentinel-2 (S2) data sets. The approaches aim at exploiting the finer spatial and spectral resolution of multispectral S2 data as well as the double bounce backscatter effect that is common to all built-up areas in SAR S1 data. To this aim, we introduce first a simplified and less computational demanding version of the Urban Extractor (UEXT) algorithm, recently introduced for urban extent extraction from S1 data, and improve its results by two different ways of selecting the seed pixels involved in UEXT by means of the urban extent maps extracted from S2 using the normalized difference spectral vector (NDSV), whose application for national and regional extraction of human settlements have already proved as very effective. Experimental results for Rio de Janeiro and Beijing show the improvements obtained by considering one of the two proposed techniques, and explains while the other one fails in achieving similar results.
Jointly exploiting sentinel-1 and sentinel-2 for urban mapping
Iannelli G. C.;Gamba P.
2018-01-01
Abstract
This work introduces two feature fusion techniques that exploit previously developed algorithms for urban extent extraction from multispectral and SAR spaceborne data, adapting them to the joint use of Sentinel-1 (S1) and Sentinel-2 (S2) data sets. The approaches aim at exploiting the finer spatial and spectral resolution of multispectral S2 data as well as the double bounce backscatter effect that is common to all built-up areas in SAR S1 data. To this aim, we introduce first a simplified and less computational demanding version of the Urban Extractor (UEXT) algorithm, recently introduced for urban extent extraction from S1 data, and improve its results by two different ways of selecting the seed pixels involved in UEXT by means of the urban extent maps extracted from S2 using the normalized difference spectral vector (NDSV), whose application for national and regional extraction of human settlements have already proved as very effective. Experimental results for Rio de Janeiro and Beijing show the improvements obtained by considering one of the two proposed techniques, and explains while the other one fails in achieving similar results.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
