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Repeat-pass SAR interferometry for land cover classification: a methodology using Sentinel-1 Short-Time-Series

Sica, Francescopaolo and Pulella, Andrea and Nannini, Matteo and Pinheiro, Muriel and Rizzoli, Paola (2019) Repeat-pass SAR interferometry for land cover classification: a methodology using Sentinel-1 Short-Time-Series. Remote Sensing of Environment, 232 (111277). Elsevier. DOI: 10.1016/j.rse.2019.111277 ISSN 0034-4257

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Official URL: https://www.sciencedirect.com/science/article/pii/S0034425719302962?via%3Dihub

Abstract

In this paper we explore the potential of repeat-pass interferometric SAR (InSAR) for land cover classification purposes. We introduce a novel approach for the generation of large-scale thematic maps, based on the use of multi-temporal data, acquired over short observation intervals (short-time-series). A larger interferometric coherence loss is expected with the increasing time difference between two interferometric acquisitions. This phenomenon is normally indicated as temporal decorrelation whose amount differs depending on the type of imaged target on ground. The basic idea is therefore to accurately model the evolution in time of the temporal decorrelation and use the estimated parameters, together with backscatter, as input features for the Random Forest machine learning classification algorithm. The work has been carried out on the case study of land cover mapping over central Europe, considering Sentinel-1 C-band interferometric stacks, acquired over a time span of about one month. Three different land cover classes have been considered: artificial surfaces as e.g. urban areas, forests, and non-forested areas as the ensemble of low vegetation, bare soil, and agricultural areas. The results show a level of agreement above 91%, when compared to the CORINE land cover map product of 2012, which has been used as external reference for both training and testing of the classification algorithm.

Item URL in elib:https://elib.dlr.de/128491/
Document Type:Article
Title:Repeat-pass SAR interferometry for land cover classification: a methodology using Sentinel-1 Short-Time-Series
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Sica, FrancescopaoloFrancescopaolo.Sica (at) dlr.dehttps://orcid.org/0000-0003-1593-1492
Pulella, AndreaAndrea.Pulella (at) dlr.deUNSPECIFIED
Nannini, MatteoMatteo.Nannini (at) dlr.deUNSPECIFIED
Pinheiro, Murielmuriel.pinheiro (at) dlr.dehttps://orcid.org/0000-0001-5770-1738
Rizzoli, PaolaPaola.Rizzoli (at) dlr.dehttps://orcid.org/0000-0001-9118-2732
Date:16 July 2019
Journal or Publication Title:Remote Sensing of Environment
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:232
DOI :10.1016/j.rse.2019.111277
Editors:
EditorsEmail
Chuvieco, EmilioUNSPECIFIED
Publisher:Elsevier
ISSN:0034-4257
Status:Published
Keywords:Land cover classification SAR Interferometric coherence Sentinel-1 Temporal decorrelation
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - SAR-Methodology
Location: Oberpfaffenhofen
Institutes and Institutions:Microwaves and Radar Institute
Deposited By: Sica, Dr. Francescopaolo
Deposited On:31 Jul 2019 15:25
Last Modified:31 Jul 2019 20:26

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