ABSTRACT The demarcation of linear geomorphological features due to fracture systems, underlying or exposed faults, drainage lines etc. from satellite images has been one of the most widely used applications in geological studies. Synthetic Aperture Radar (SAR) data has been recognized as an effective tool for lineament extraction due to its unique sensitivity to subtle topography, soil moisture and texture. However, the typical SAR sensor parameters such as frequency, polarization and look direction plays a vital role in enhancing the performance for a specific application. Therefore, the study aims to analyse the multi-frequency (C- and L-band), multi-polarization (like and cross) and multi-look direction SAR data for geological lineaments extraction. In this paper, Sentinel-1 and Advanced Land Observation Satellite (ALOS)-2 Phased Array type L-band Synthetic Aperture Radar (PALSAR)-2 datasets acquired over a part of the Indo-Burma ranges of Manipur region (northeastern part of India) are considered for analysis. The lineaments extracted from SAR datasets are compared with reference to lineaments provided by the Geological Survey of India (GSI) through their portal. The study observes that the like-polarization C-band SAR data provide optimal results for this application. It is also observed that the integration of lineaments extracted from multi-look SAR data can significantly improve the performance than that derived from single-look data. Overall, the study also focuses on the spatial distribution of lineaments with respect to the local structural regime for a better understanding of the regional tectonic setup.

中文翻译：

---

用于地质线状提取的多参数合成孔径雷达数据性能评估

摘要 从卫星图像中划分由裂缝系统、下伏或暴露断层、排水线等引起的线性地貌特征已成为地质研究中应用最广泛的应用之一。合成孔径雷达 (SAR) 数据因其对细微地形、土壤湿度和质地的独特敏感性而被公认为是提取轮廓线的有效工具。然而，典型的 SAR 传感器参数（例如频率、极化和视向）在增强特定应用的性能方面起着至关重要的作用。因此，本研究旨在分析用于地质线条提取的多频（C 波段和 L 波段）、多极化（同向和交叉）和多视方向 SAR 数据。在本文中，Sentinel-1 和高级陆地观测卫星 (ALOS)-2 相控阵型 L 波段合成孔径雷达 (PALSAR)-2 数据集考虑在曼尼普尔地区（印度东北部）的部分印缅范围内采集分析。将从 SAR 数据集中提取的线状线与印度地质调查局 (GSI) 通过其门户提供的线状线进行比较。该研究观察到，类似极化的 C 波段 SAR 数据为本应用提供了最佳结果。还观察到，从多视 SAR 数据中提取的线条的集成可以显着提高性能，而不是从单视数据中提取的。全面的，