Debanshu RathaUiT The Arctic University of Norway · Department of Physics and Technology
Debanshu Ratha
Doctor of Philosophy
About
35
Publications
10,012
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
792
Citations
Publications
Publications (35)
We propose a generic Scattering Power Factorization Framework (SPFF) for Polarimetric Synthetic Aperture Radar (PolSAR) data to directly obtain $N$ scattering power components along with a residue power component for each pixel. Each scattering power component is factorized into similarity (or dissimilarity) using elementary targets and a generaliz...
European Space Agency’s (ESA) Sentinel-1 mission provides a comprehensive coverage of earth in dual polarization mode (VV+VH) with a frequent revisit time of six days from a constellation of two satellites. The transmission occurs in vertical polarisation (V) only, hence the received backscatter can be analyzed as a Stokes vector on the Poincare sp...
In this letter, we propose a novel vegetation index from polarimetric synthetic-aperture radar (PolSAR) data using the generalized volume scattering model. The geodesic distance between two Kennaugh matrices projected on a unit sphere proposed by Ratha et al. is used in this letter. This distance is utilized to compute a similarity measure between...
Built-up (BU) area extraction from remote sensing images is important to monitor and manage urbanization and industrialization. In this letter, we propose two BU area extraction techniques based on the analysis of fully polarimetric synthetic aperture radar (PolSAR) data. Both methods exploit the geodesic distance on the unit sphere in the space of...
Uncertainty is unavoidable in classification tasks and might originate from data (e.g., due to noise or wrong labeling), or the model (e.g., due to erroneous assumptions, etc). Providing an assessment of uncertainty associated with each outcome is of paramount importance in assessing the reliability of classification algorithms, especially on unsee...
Present and future sensors are diversifying from traditional quad polarimetric mode of Synthetic Aperture Radar acquisition. Thus, an approach that is interpretative in nature and applicable across polarimetric modes is required. In this context, the Geodesic Distance (GD) based approach within the Polarimetric SAR (PolSAR) literature is seen as an...
div>Information on rice phenological stages from Synthetic Aperture Radar (SAR) images is of prime interest for in-season monitoring. Often, prior in-situ measurements of phenology are not available. In such situations, unsupervised clustering of SAR images might help in discriminating phenological stages of a crop throughout its growing period. Am...
Information on rice phenological stages from Synthetic Aperture Radar (SAR) images is of prime interest for in-season monitoring. Often, prior in-situ measurements of phenology are not available. In such situations, unsupervised clustering of SAR images might help in discriminating phenological stages of a crop throughout its growing period. Among...
In this paper, we present two radar vegetation indices for full-pol and compact-pol SAR data, respectively. Both are derived using the notion of a geodesic distance between observation and well-known scattering models available in the literature. While the full-pol version depends on a generalized volume scattering model, the compact-pol version us...
In this study, we propose a new vegetation index (DpRVI) for dual polarimetric synthetic aperture radar (SAR) data. The evaluation of this new index is performed with a particular attention towards the preparation of the NASA-ISRO SAR (NISAR) L-band system science objective. The proposed vegetation index is derived for two dual-pol (HH-HV and VV-VH...
The scattering information from targets is either estimated by fitting suitable scattering models or by optimizing the received wave intensity through the diagonalization of the coherency (or covariance) matrix. In this study, a new roll-invariant scattering-type parameter is introduced, which jointly uses the 3D Barakat degree of polarisation and...
div>Information on rice phenological stages from Synthetic Aperture Radar (SAR) images is of prime interest for in-season monitoring. Often, prior in-situ measurements of phenology are not available. In such situations, unsupervised clustering of SAR images might help in discriminating phenological stages of a crop throughout its growing period. Am...
Information on rice phenological stages from Synthetic Aperture Radar (SAR)images is of prime interest for in-season monitoring. Often, prior in-situ measurements of phenology are not available. In such situations, unsupervised clustering of SAR images might help in discriminating phenological stages of a crop throughout its growing period. Among t...
Sentinel-1 Synthetic Aperture Radar (SAR) data have provided an unprecedented opportunity for crop monitoring due to its high revisit frequency and wide spatial coverage. The dual-pol (VV-VH) Sentinel-1 SAR data are being utilized for the European Common Agricultural Policy (CAP) as well as for other national projects, which are providing Sentinel...
In this paper, we present two radar vegetation indices for full-pol and compact-pol SAR data, respectively. Both are derived using the notion of a geodesic distance between observation and well-known scattering models available in the literature. While the full-pol version depends on a generalized volume scattering model, the compact-pol version us...
Crop growth monitoring using compact-pol Synthetic Aperture Radar (CP-SAR) data is gaining attention with the rapid advancements toward operational applications. In this study, we propose a vegetation index for compact polarimetric (CP) SAR data (CpRVI). The CpRVI is derived using the concept of a geodesic distance between Kennaugh matrices project...
This manuscript was submitted on 31 December 2019 to IEEE Transactions on Geoscience and Remote Sensing.
Abstract: Incoherent target decomposition techniques provide unique scattering information from polarimetric SAR data either by fitting appropriate scattering models or by optimizing the ``received" wave intensity through the diagonalization of...
This manuscript was submitted on 31 December 2019 to IEEE Transactions on Geoscience and Remote Sensing.
Abstract: Incoherent target decomposition techniques provide unique scattering information from polarimetric SAR data either by fitting appropriate scattering models or by optimizing the ``received" wave intensity through the diagonalization of...
In radar polarimetry, incoherent target decomposition techniques help extract scattering information from polarimetric SAR data. This is achieved either by fitting appropriate
scattering models or by optimizing the received wave intensity
through the diagonalization of the coherency (or covariance)
matrix. As such, the received wave information dep...
In this paper, a generic scattering power factorization framework
for Polarimetric SAR (PolSAR) data is proposed to
directly obtain N scattering power components along with
a residue power component for each pixel. Each scattering
power component can be factorized into similarity (or
dissimilarity) with the utilized scattering models. The similarit...
In this study, we propose a vegetation index for compact polarimetric (CP) SAR data (CpRVI) using a geodesic distance between two Kennaugh matrices projected on a unit sphere, as given in Ratha et. al. This distance is utilized to compute a similarity measure between the observed Kennaugh matrix and the Kennaugh matrix of an isotropic depolarizer....
This paper presents a novel scattering power factor-ization framework in radar polarimetry using a geodesic distance between the 4 × 4 real Kennaugh matrices of the observed and the elementary targets (viz. dihedral, trihedral, dipole etc.). The framework provides both qualitative and quantitative estimates of the dominance of elementary scattering...
In this letter, we propose a novel technique for obtaining scattering components from Polarimetric Synthetic Aperture Radar (PolSAR) data using the geodesic distance on the unit sphere. This geodesic distance is obtained between an elementary target and the observed Kennaugh matrix, and it is further utilized to compute a similarity measure between...
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...