Surendar Manickam

Surendar Manickam
VIT University | VIT · Centre for Disaster Mitigation and Management

PhD

About

35
Publications
7,045
Reads
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373
Citations
Citations since 2016
23 Research Items
363 Citations
2016201720182019202020212022020406080
2016201720182019202020212022020406080
2016201720182019202020212022020406080
2016201720182019202020212022020406080
Additional affiliations
October 2018 - present
Duke University
Position
  • PostDoc Position
September 2016 - August 2018
Friedrich-Alexander-University of Erlangen-Nürnberg
Position
  • PostDoc Position
April 2016 - June 2016
Indian Institute of Technology Bombay
Position
  • Research Associate

Publications

Publications (35)
Chapter
In this chapter, we first discuss the significance of snow studies in the alpine regions. We then give an overview of the snowpack properties in the alpine regions that are essential for snowpack characterization. We then introduce the role of remote sensing in the context of retrieving the snowpack's physical properties, followed by discussions on...
Article
Full-text available
The seasonal snow cover contributes significantly to the water resource in the Indian Himalayas, and snow density is one of the vital parameters in the determination of the hydrological potential of snow. The application of conventional methods for snow density retrieval using fully polarimetric SAR data is constrained by the properties of snow pri...
Article
Full-text available
This study investigates the spatial signatures of seasonal snow in Synthetic Aperture Radar (SAR) observations at different spatial scales and for different physiographic regions. Sentinel-1 C-band (SAR) backscattering coefficients (BSC) were analyzed in the Swiss Alps (SA), in high elevation forest and grasslands in Grand Mesa (GM), Colorado, and...
Article
Full-text available
Recently, with the extensive availability of fully polarimetric SAR data, methods that are simple and efficient, and involve lesser computation and data processing are needed to be explored for snow cover mapping. This paper analyses different polarimetric parameters such as entropy, anisotropy and the mean scattering angle for the identification o...
Article
Full-text available
The studies on snow depth comprise a crucial area of research in the Indian Himalayas, where the seasonal snow cover primarily drives the rivers and significant water resources. In this paper, the initial estimates of the line of sight displacement obtained using differential interferometric phase in VV and VH polarizations using Sentinel-1 bi-temp...
Conference Paper
Full-text available
The snow water equivalent is a significant parameter in the determination of the hydrological potential of snow, which requires timely information on snow density and snow depth. For shallow snow depth, the C-band polarimetric synthetic aperture radar (SAR) data can be effectively utilized for the estimation of snow density. Although methods exist...
Presentation
Full-text available
The snow water equivalent is a significant parameter in the determination of the hydrological potential of snow, which requires timely information on snow density and snow depth. For shallow snow depth, the C-band polarimetric synthetic aperture radar (SAR) data can be effectively utilized for the estimation of snow density. Although methods exist...
Article
Full-text available
We propose a multi-sensor multi-spectral and bi-temporal dual-polarimetric Synthetic Aperture Radar (SAR) data integration scheme for dry/wet snow mapping using Sentinel-2 and Sentinel-1 data which are freely available to the research community. The integration is carried out by incorporating the information retrieved from ratio images of the conve...
Article
Full-text available
Remote sensing is an indispensable tool for Earth observation over large areal extent. Snow cover extent monitoring has been one such application where microwave sensors have been a popular choice due to their sensitivity toward the dielectric property. Snow is a dynamic matter since its dielectric state is dependent on climatic factors prevailing...
Article
Full-text available
Monitoring of snow cover over large areal extent requires the use of remotely sensed satellite data. Conventional snow cover mapping algorithms using SAR data have seldom utilized target scattering information for land cover characterization. In this paper, an approach is proposed for snow cover mapping that utilizes the Touzi eigenvalue-eigenvecto...
Article
Full-text available
In this letter, a methodology is proposed to improve the scattering powers obtained from model-based decomposition using Polarimetric Synthetic Aperture Radar (PolSAR) data. The novelty of this approach lies in utilizing the intrinsic information in the off-diagonal elements of the 3 × 3 coherency matrix T represented in the form of complex correla...
Conference Paper
Full-text available
Surficial uranium concentrations in the form of calcrete-hosted carnotite deposits are highly soughtafter because of low mining and extraction costs. These deposits form by precipitation of uraniumpotassium vanadate (i.e., carnotite) from ground waters in very-near- to near-surface environments in Tertiary to Recent palaeochannels that are etched o...
Article
A novel methodology is proposed in this paper for the estimation of snow surface dielectric constant from polarimetric SAR (PolSAR) data. The dominant scattering type magnitude proposed in Touzi et. al., is used to characterize scattering mechanism over the snowpack. Whereas two methods have been used to obtain the optimized degree polarization of...
Article
Full-text available
In this article, a methodology is proposed for enhanced target characterization and improvement in scattering powers from model-based decomposition using full Polarimetric Synthetic Aperture Radar (PolSAR) data. The novelty of this approach is established by utilizing the degree of polarization (DOP) from full PolSAR data. The optimum degree of pol...
Conference Paper
In this work, we present urban area mapping from full-polarimetric synthetic aperture radar (SAR) data using fuzzy inference system (FIS). In particular, our aim is to utilize the profound knowledge available about scattering mechanism from urban targets to delineate urban environment. In this approach, we have utilized the recently developed polar...
Article
Glaciers have a high impact in the socio-economic sectors including water supply, energy production, flood and avalanches. A high precision digital elevation model (DEM) is required to monitor glaciers and to study various glacier processes. The present study deals with the qualitative and quantitative evaluation of the DEM generated from the bista...
Article
Abstract In this paper, a new snow wetness estimation model is proposed for full-polarimetric Synthetic Aperture Radar (SAR) data. Surface and volume are the dominant scattering components in wet-snow conditions. The generalized four component polarimetric decomposition with unitary transformation (G4U) based generalized surface and volume paramete...
Article
Full-text available
An adaptive general four-component scattering power decomposition method (AG4U) is proposed in this letter. The degree of polarization mis used as a criterion for the adaptive nature of the proposed decomposition. In this method, one among the two complex special unitary transformation matrices is chosen to transform a real unitary rotated coherenc...
Article
Full-text available
In this paper, we have proposed a new decomposition technique for compact polarimetric (CP) synthetic aperture radar (SAR) data. In the proposed decomposition, the odd and the even bounce scattering powers and are, respectively, obtained by combining the powers received in the opposite-sense circular (OC) polarization and the same-sense circular (S...
Article
6 In this paper, a new snow density estimation methodology is proposed for full-polarimetric Synthetic Aperture Radar (SAR) data. The generalized four component polarimetric decomposition with unitary transformation (G4U) based generalized volume parameter is utilized to invert snowpack dielectric constant using the Fresnel transmission coefficient...
Article
Full-text available
Model-based decompositions have gained considerable attention after the initial work of Freeman and Durden. This decomposition which assumes the target to be reflection symmetric was later relaxed in the Yamaguchi et al. decomposition with the addition of the helix parameter. Since then many decomposition have been proposed where either the scatter...
Article
In this paper, a new snow wetness estimation methodology is proposed for dual-coherent polarimetric Synthetic Aperture Radar (SAR) data. Surface and volume are the dominant scattering components in the wet-snow conditions. These components, with a limit of penetration depth of high frequency SAR, have been taken into account to estimate the snow-pa...
Conference Paper
Full-text available
Snow wetness is a very important parameter for forecasting snow avalanche and for snow melt run off modeling in cragged areas specifically for Himalayan regions of India. In this paper, a new snow wetness estimation approach is used for fully polarimetric Synthetic Aperture Radar (SAR) data. In this new methodology, Freeman surface scattering and C...
Conference Paper
Recently launched TanDEM-X SAR mission (June, 2010) aims to generate a consistent global DEM equaling HRTI-3 specification. In view of global DEM generation using TanDEM-X InSAR data, it is very important to evaluate their accuracy over various test areas. This paper presents the evaluation of DEM generated using interferometric technique from TanD...
Conference Paper
Full-text available
Snow wetness is an important parameter for forecasting of snow avalanche and snow melt run off modeling in cragged areas specifically Himalayan region of India. In this paper a new snow wetness estimation approach is used for fully polarimetric Synthetic Aperture Radar (SAR) data. In this new methodology Freeman surface scattering and Cloude volume...

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Projects

Projects (2)
Project
Estimation of snow geophysical parameters (wetness, density, and depth) Estimation of snow water equivalent. Fusion of optical and SAR data
Project
Snow cover mapping & glacier velocity estimation