Data for Publication

Published: 13 August 2023| Version 1 | DOI: 10.17632/g8tcphkwcc.1
prabhakar kallempudi


Lineaments are the linear geological features can extend from few meters to hundreds of kms. Geologically lineaments are either structural or stratigraphical, typically it will comprise fault, fold axis, bedding contacts, dyke intrusions, shear zone or a straight coast line. Mapping lineaments using remote sensing is economical, faster can act as a preliminary study for geological survey. Generally, lineaments have been mapped using the optical remote sensing data such as Landsat, Resourcesat etc. For India, Lineaments were mapped using the LISS III and LISS IV of Resourcesat-1 & 2 at a scale of 1:50k. However in tropical region like India, limited exposure of ground due to vegetation cover, lineaments may go unnoticed in optical remote sensing data. This problem can be overcome by Synthetic Aperture Radar (SAR) data, which can penetrate ground significantly. With the launch of RISAT-1satelite, data availability of SAR data is immense for Indian region. Aim of this study to explore the SAR data and merged SAR and optical data for lineament mapping.


Steps to reproduce

In this study Radar Satellite-1 (RISAT-1) is used for delineation of lineaments. Radar Satellite-1 (RISAT-1) is a state of the art microwave remote sensing satellite carrying a Synthetic Aperture Radar (SAR) Payload operating in C-band (5.35 GHz), which enables imaging of the surface features during both day and night under all weather conditions. RISAT-1 was successfully launched by ISRO using PSLV-C19 on 26 April 2012. The RISAT can provide quad polarisation data (HH, VV, HV, VH) as well as circular polarizations. The RISAT-1 can be operated in different modes ranging from spatial resolution of 3m in fine resolution mode with 30Km swath to 50m resolution with 240m resolution in Coarse resolution model data(Tapan Misra et al., 2005).In the absence of emergency or user request, the default mode of collection will be MRS descending, left looking, with dual polarization with a repeat cycle of 25 days with spatial resolution of 18-25m. The data can be acquired in all weather conditions, in both ascending (Evening) and descending mode (Morning) and in both right look and left look which means user can get data for any part of India at every 14 days interval. In the present study dual polarisation (HH, HV) with the spatial resolution of 18m is used. In addition to SAR data, IRS LISS III data was used which contains four spectral bands ranging from Optical to Near InfraRed (NIR) with the 30m spatial resolution. Resolution merge of SAR and optical data were done using Brovey transform in ERDAS 2015 software. Apart from this GSI map 1:5,000,000 is used in this study to discuss geological background of lineaments (Fig. 9).


Andhra University College of Science and Technology


Remote Sensing, Geographic Information Systems