Geomatics Laboratory, Civil Engineering, IIT Jammu

Notifications

Congratulations to Mr. Hemant Singh for receiving the Prestigious PMRF fellowship for Cycle-9, 2022.
I wish him many accolades ahead.

Looking for a Ph.D. student under the Ministry of Education Fellowship to work on the estimation of snow geophysical parameters using microwave remote sensing. The applications will open for the July 2023 session here

I am looking for a NPDF fellow for working on research problems rooted in the parameterization of snow and glacier melt. Interested candidates can discuss their proposal for submission to SERB here.

We are accepting research contributions for the following special issues of the journal ALL EARTH, Taylor and Francis.
Sustainable Natural Resource Management in the framework of the Water-Energy-Food-Ecosystem (WEFE) Nexus
Remote Sensing for Global Environmental Change

We are accepting full or mini-review contributions for the collection Reviews in Microwave Remote Sensing: 2022 in the journal Frontiers in Remote Sensing.

Featured Research

Analyzing urbanization induced groundwater stress and land deformation using time-series Sentinel-1 datasets applying PSInSAR approach

Highlights

  • PSInSAR processing of Sentinel-1 datasets reveals significant land subsidence in the Lucknow region.

  • Groundwater fluctuations due to alarming pace of sub-surface water pumping causes significant impact on land subsidence in Lucknow.

  • A linkage is observed between the declining ground water, land subsidence and the urban growth in the Lucknow region.

  • A significant correlation is observed between the ground water level variation and the surface displacement.



Development of a novel approach for snow wetness estimation using hybrid polarimetric RISAT-1 SAR datasets in North-Western Himalayan region

https://doi.org/10.1016/j.jhydrol.2022.128252

Highlights

  • This study proposes a novel methodology for the estimation of snow wetness utilizing the C-band hybrid polarimetric RISAT-1 SAR dataset.

  • The Estimation of Surface and Volume Dielectric Constant of Snowpack is done for the retrieval of Snowpack Wetness utilizing surface and volume scattering characteristics.

  • The modeled generalized surface and volume scattering parameter (α), and (γ), based on the X-Bragg’s reflection coefficients and Fresnel transmission coefficients, are used for the inversion of surface and volume snow permittivity respectively.

  • The proposed method using RISAT-1 dataset outperformed the estimates based on fully polarimetric RADARSAT-2 dataset utilizing the conventional Shi and Dozier method.

  • The developed methodology for snow wetness estimation will be applicable for the Hybrid Polarimetric mode datasets from upcoming missions like NISAR, ALOS-3, and Radar Constellation Mission (RCM).