Towards a 20 m Global Building Map from Sentinel-1 SAR Data

This study introduces a technique for automatically mapping built-up areas using synthetic aperture radar (SAR) backscattering intensity and interferometric multi-temporal coherence generated from Sentinel-1 data in the framework of the Copernicus program. The underlying hypothesis is that, in SAR i...

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Main Authors: Marco Chini, Ramona Pelich, Renaud Hostache, Patrick Matgen, Carlos Lopez-Martinez
Format: Article
Language:English
Published: MDPI AG 2018-11-01
Series:Remote Sensing
Subjects:
Online Access:https://www.mdpi.com/2072-4292/10/11/1833
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spelling doaj-9c82705f25734b2598c31371a73466542020-11-24T23:14:53ZengMDPI AGRemote Sensing2072-42922018-11-011011183310.3390/rs10111833rs10111833Towards a 20 m Global Building Map from Sentinel-1 SAR DataMarco Chini0Ramona Pelich1Renaud Hostache2Patrick Matgen3Carlos Lopez-Martinez4Luxembourg Institute of Science and Technology (LIST), Environmental Research and Innovation Department (ERIN), 4422 Belvaux, LuxembourgLuxembourg Institute of Science and Technology (LIST), Environmental Research and Innovation Department (ERIN), 4422 Belvaux, LuxembourgLuxembourg Institute of Science and Technology (LIST), Environmental Research and Innovation Department (ERIN), 4422 Belvaux, LuxembourgLuxembourg Institute of Science and Technology (LIST), Environmental Research and Innovation Department (ERIN), 4422 Belvaux, LuxembourgLuxembourg Institute of Science and Technology (LIST), Environmental Research and Innovation Department (ERIN), 4422 Belvaux, LuxembourgThis study introduces a technique for automatically mapping built-up areas using synthetic aperture radar (SAR) backscattering intensity and interferometric multi-temporal coherence generated from Sentinel-1 data in the framework of the Copernicus program. The underlying hypothesis is that, in SAR images, built-up areas exhibit very high backscattering values that are coherent in time. Several particular characteristics of the Sentinel-1 satellite mission are put to good use, such as its high revisit time, the availability of dual-polarized data, and its small orbital tube. The newly developed algorithm is based on an adaptive parametric thresholding that first identifies pixels with high backscattering values in both VV and VH polarimetric channels. The interferometric SAR coherence is then used to reduce false alarms. These are caused by land cover classes (other than buildings) that are characterized by high backscattering values that are not coherent in time (e.g., certain types of vegetated areas). The algorithm was tested on Sentinel-1 Interferometric Wide Swath data from five different test sites located in semiarid and arid regions in the Mediterranean region and Northern Africa. The resulting building maps were compared with the Global Urban Footprint (GUF) derived from the TerraSAR-X mission data and, on average, a 92% agreement was obtained.https://www.mdpi.com/2072-4292/10/11/1833built-up areascoherencehierarchical split-based approach (HSBA)intensityparametric thresholdingmulti-temporalSAR urban mapsSentinel-1
collection DOAJ
language English
format Article
sources DOAJ
author Marco Chini
Ramona Pelich
Renaud Hostache
Patrick Matgen
Carlos Lopez-Martinez
spellingShingle Marco Chini
Ramona Pelich
Renaud Hostache
Patrick Matgen
Carlos Lopez-Martinez
Towards a 20 m Global Building Map from Sentinel-1 SAR Data
Remote Sensing
built-up areas
coherence
hierarchical split-based approach (HSBA)
intensity
parametric thresholding
multi-temporal
SAR urban maps
Sentinel-1
author_facet Marco Chini
Ramona Pelich
Renaud Hostache
Patrick Matgen
Carlos Lopez-Martinez
author_sort Marco Chini
title Towards a 20 m Global Building Map from Sentinel-1 SAR Data
title_short Towards a 20 m Global Building Map from Sentinel-1 SAR Data
title_full Towards a 20 m Global Building Map from Sentinel-1 SAR Data
title_fullStr Towards a 20 m Global Building Map from Sentinel-1 SAR Data
title_full_unstemmed Towards a 20 m Global Building Map from Sentinel-1 SAR Data
title_sort towards a 20 m global building map from sentinel-1 sar data
publisher MDPI AG
series Remote Sensing
issn 2072-4292
publishDate 2018-11-01
description This study introduces a technique for automatically mapping built-up areas using synthetic aperture radar (SAR) backscattering intensity and interferometric multi-temporal coherence generated from Sentinel-1 data in the framework of the Copernicus program. The underlying hypothesis is that, in SAR images, built-up areas exhibit very high backscattering values that are coherent in time. Several particular characteristics of the Sentinel-1 satellite mission are put to good use, such as its high revisit time, the availability of dual-polarized data, and its small orbital tube. The newly developed algorithm is based on an adaptive parametric thresholding that first identifies pixels with high backscattering values in both VV and VH polarimetric channels. The interferometric SAR coherence is then used to reduce false alarms. These are caused by land cover classes (other than buildings) that are characterized by high backscattering values that are not coherent in time (e.g., certain types of vegetated areas). The algorithm was tested on Sentinel-1 Interferometric Wide Swath data from five different test sites located in semiarid and arid regions in the Mediterranean region and Northern Africa. The resulting building maps were compared with the Global Urban Footprint (GUF) derived from the TerraSAR-X mission data and, on average, a 92% agreement was obtained.
topic built-up areas
coherence
hierarchical split-based approach (HSBA)
intensity
parametric thresholding
multi-temporal
SAR urban maps
Sentinel-1
url https://www.mdpi.com/2072-4292/10/11/1833
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