Built-Up Area Characterization: Advanced Techniques For Dual-Pol Sentinel-1 SAR Data

An accurate and timely characterization of built-up areas is essential in making cities and human settlements safe, resilient, and sustainable. Dual-polarized (dual-pol) Synthetic Aperture Radar (SAR) data, commonly used for urban analysis, primarily relies on backscatter intensity, which lacks adequate built-up target characteristics in complex urban scenarios. This study utilizes a set of dual-pol descriptors specifically designed to discriminate built-up areas from other land cover targets, facilitating enhanced characterization of diverse built-up targets in complex urban environments. The applicability of these descriptors to Sentinel-1 Ground Range Detected (GRD) SAR data accessible on the Google Earth Engine (GEE) platform enables efficient global built-up area characterization with frequent updates.

Authors

Institutions

Publication Details

Published
2025-05-05
DOI
https://doi.org/10.1109/jurse60372.2025.11076034
Primary Topic
Synthetic Aperture Radar (SAR) Applications and Techniques
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Built-Up Area Characterization: Advanced Techniques For Dual-Pol Sentinel-1 SAR Data

Paolo Gamba, Abhinav Verma, Avik Bhattacharya
Synthetic Aperture Radar (SAR) Applications and Techniques
article

Built-Up Area Characterization: Advanced Techniques For Dual-Pol Sentinel-1 SAR Data

Paolo Gamba, Abhinav Verma, Avik Bhattacharya
article en

Abstract

An accurate and timely characterization of built-up areas is essential in making cities and human settlements safe, resilient, and sustainable. Dual-polarized (dual-pol) Synthetic Aperture Radar (SAR) data, commonly used for urban analysis, primarily relies on backscatter intensity, which lacks adequate built-up target characteristics in complex urban scenarios. This study utilizes a set of dual-pol descriptors specifically designed to discriminate built-up areas from other land cover targets, facilitating enhanced characterization of diverse built-up targets in complex urban environments. The applicability of these descriptors to Sentinel-1 Ground Range Detected (GRD) SAR data accessible on the Google Earth Engine (GEE) platform enables efficient global built-up area characterization with frequent updates.

Indian Institute of Technology Bombay (IN), University of Pavia (IT)
Sustainable cities and communities
Openalex Percentile: Top 76%
Synthetic Aperture Radar (SAR) Applications and Techniques
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Built-Up Area Characterization: Advanced Techniques For Dual-Pol Sentinel-1 SAR Data — Paolo Gamba, Abhinav Verma, et al. · (2025) | TGRS Research Map | TGRS