Ys Rao

Indian Institute of Technology Bombay | IIT Bombay · Centre of Studies in Resources Engineering (CSRE)

Biophysical parameters are descriptors of crop growth and production estimates. Retrieval of these biophysical parameters from synthetic aperture radar sensors at operational scales is highly interesting given the increase in access to data from radar missions. Vegetation backscattering can be simulated using the water cloud model (WCM). Crop bioph...

Polarimetric Synthetic Aperture Radar (SAR) data has been extensively used to estimate soil permittivity because of its high sensitivity to the dielectric properties of the target. However, the presence of vegetation cover induces bias in the permittivity estimates. % Previous researchers tackle this problem in various ways, including using polari...

Vegetation cover significantly influences the hydrometeorological processes of land surfaces. The heterogeneity of vegetation cover makes these processes more complex and impacts the interaction between water held in the soil matrix and vegetation cover. The backscatter measured by Synthetic Aperture Radar (SAR) is sensitive to target dielectric an...

Soil moisture is a critical land variable that controls the energy and mass balance in land-atmosphere interactions. Spaceborne Synthetic Aperture Radar (SAR) sensors offer an efficient way to map and monitor soil moisture because of their sensitivity towards the dielectric and geometric properties of the target. In addition, SAR acquisitions are w...

This study investigates the performances of three radar vegetation indices derived from full (HH-VH-VV), compact (RH-RV), and dual (VV-VH or HH-HV) polarimetric Synthetic Aperture Radar (SAR) data for Leaf Area Index (LAI) and biomass estimation. We use the notion of a geodesic distance between the incoherent representation of radar measurements an...

Soil permittivity estimation using polarimetric synthetic aperture radar (PolSAR) data has been an extensively researched area. Nonetheless, it provides ample scope for further improvements. The vegetation cover over the soil surface leads to a complex interaction of the incident polarized wave with the canopy and subsequently with the underlying s...

Using the cross-validation approach, strategies for estimating biophysical parameters are still pre-operational with synthetic aperture radar (SAR) data. In this regard, the Joint Experiment for Crop Assessment and Monitoring (JECAM) SAR inter-comparison experiments provide an opportunity for the potential implementation of cross-validation strateg...

India launched the Chandrayaan-2 satellite on 22 July 2019, with several sensors onboard to map the Lunar surface and subsurface. Among the several sensors, the Dual Frequency Synthetic Aperture Radar (DFSAR) operates in L- and S-band frequencies in full and compact polarimetric modes. This paper analyzes full- and compact polarimetric SAR data acq...

The new era of cloud platform technologies opens up many opportunities for near real-time dissemination of disaster information to the end-users. The present study utilizes the European Space Agency (ESA) Research and Service Support (RSS) CloudToolbox platform to monitor the spatio-temporal dynamics of a flood event. A collective flood monitoring...

Semi-empirical models for radar scattering from vegetation are discussed in this chapter. The evolution of semi-empirical approaches from the dielectric slab model to the Water Cloud Model (WCM) and its modified forms are presented with their theoretical development. A section is dedicated to evaluating the theoretical aspect of WCM parameterizatio...

This chapter provides full- and dual-pol SAR data to assess multi-target inversion approaches for the semi-empirical Water Cloud Model. In addition to comparative analysis between retrieval results from multi-target techniques, analyzing the correlation between the estimated biophysical parameters and the observed ones against single-target approac...

In this monograph, the utilization of SAR data to retrieve biophysical parameters is described for agricultural crops. Crop biophysical parameters include the foliar area (LAI or PAI) and plant biomass, particularly sensitive to environmental and agronomic practices. Timely information about these biophysical parameters and their spatio-temporal va...

Vegetation indices (VI) are often used as a proxy to plant growth indicators. SAR data are usually processed by several downstream users and are often interpreted by non-radar specialists. This paradigm requires the utility of radar-derived vegetation indices prototypical for Analysis Ready Data (ARD) products. This chapter covers the methodologies...

In this chapter, we describe the methodology for crop biophysical parameter estimation using compact-pol SAR data. Here, we detail the modified form of the semi-empirical Water Cloud Model (MWCM). The scattering power components obtained from the \(iS-\Omega \) decomposition are used to invert the Modified WCM (MWCM). Results are analyzed with the...

Classification of crop types using Earth Observation (EO) data is a challenging task. The challenge increases many folds when we have diverse crops within a resolution cell. In this regard, optical and Synthetic Aperture Radar (SAR) data provide complementary information about the characteristics of a target. Therefore, we propose to leverage the s...

Accurate and high-resolution spatio-temporal information about crop phenology obtained from Synthetic Aperture Radar (SAR) data is an essential component for crop management and yield estimation at a local scale. Crop growth monitoring studies seldom exploit complete polarimetric information contained in dual-pol GRD SAR data. In this study, we pro...

This chapter briefly discusses Synthetic Aperture Radar (SAR) imaging principles and the theory of SAR polarimetry. The descriptions of several polarimetric parameters and their expressions are presented in this chapter. SAR imaging principles are introduced, followed by the description of wave and polarimetric scattering concepts. Several polarime...

This chapter is devoted to several modeling aspects of EM wave interactions with agricultural crops. Comprehensive information on physical and empirical approaches for vegetation modeling with Synthetic Aperture Radar (SAR) polarimetric data are presented in this chapter. Development of various physical models starting from complex wave theory appr...

Monitoring land subsidence due to groundwater exploitation, natural oil and gas extraction, improper building foundations close to coastal areas, and tectonic movements are crucial in understanding the behavior of Earth's surface in urban areas. In the context of urban monitoring, uncontrolled constructions and irregular development activities are...

Accurate and high-resolution spatio-temporal information about crop phenology obtained from Synthetic Aperture Radar (SAR) data is an essential component for crop management and yield estimation at a local scale. Crop growth monitoring studies seldom exploit complete polarimetric information contained in dual-pol GRD SAR data. In this study, we pro...

Accurate and high-resolution spatio-temporal information about crop phenology obtained from Synthetic Aperture Radar (SAR) data is an essential component for crop management and yield estimation at a local scale. Crop growth monitoring studies seldom exploit complete polarimetric information contained in dual-pol GRD SAR data. In this study, we pro...

The demand for processing tools increases with the increasing number of Synthetic Aperture Radar (SAR) satellite missions and datasets. However, to process SAR data, a minimal number of free tools are available (PolSARpro, SNAP) that consolidate all necessary pre-processing steps. Bearing this in mind, there is a need to develop specific tools for...

The water cloud model (WCM) can be inverted to estimate leaf area index (LAI) using the intensity of backscatter from synthetic aperture radar (SAR) sensors. Published studies have demonstrated that the WCM can accurately estimate LAI if the model is effectively calibrated. However, calibration of this model requires access to field measures of LAI...

ESAs' Sentinel-1 (S1) mission has reformed the field of agriculture monitoring from space with radar data. The high resolution, large swath and frequent coverage offer precise crop condition monitoring, growth rate and management practices at a global scale. The availability of dense temporal Sentinel-1 SAR data has opened new opportunities in time...

With high-resolution imaging capability and cloud independent acquisition ability, Synthetic Aperture Radar (SAR) has immense potential in estimating soil moisture. However, soil moisture estimation in the presence of vegetation is still a challenging task due to the complex interaction of SAR signal with vegetation and underlying soil. In particul...

Target decomposition methods of polarimetric Synthetic Aperture Radar (PolSAR) data explain scattering information from a target. In this regard, several conventional model-based methods utilize scattering power components to analyze polarimetric SAR data. However, the typical hierarchical process to enumerate power components uses various branchin...

In August 2018, the southern Indian state of Kerala received unusually heavy rainfall leading to large-scale flooding and destruction. Reliable flood inunda-tion maps derived from remote sensing techniques help in flood disaster management activities. The freely available Sentinel-1A/B SAR data have the potential for flood inundation mapping due to...

The demand for processing tools increases with the increasing number of Synthetic Aperture Radar (SAR) satellite missions and datasets. However, to process SAR data, a minimal number of free tools are available (PolSARpro, SNAP), which consolidates all necessary pre-processing steps. Bearing this in mind, there is a need to develop specific tools f...

The future projections of climate change envisage a global increase in extreme precipitation events and subsequent flooding. The reliable and rapid flood maps are the critical parameters in preparing the disaster management plans. This study demonstrated an effective flood mapping framework using freely available multi-temporal Earth Observation (E...

This book presents a timely investigation of radar remote sensing observations for agricultural crop monitoring and advancements of research techniques and their applicability for crop biophysical parameter estimation. It introduces theoretical background of radar scattering from vegetation volume and semi-empirical modelling approaches that are th...

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...

Soil moisture retrieval over the vegetated soil surfaces using Synthetic Aperture Radar (SAR) data is a challenging issue. Presence of vegetation over soil surface makes the interaction of the radar signal with the soil more complex. Several studies used the Water Cloud Model (WCM) to separate vegetation effect on the soil backscatter while estimat...

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...

In radar remote sensing applications, soil moisture retrieval over the vegetated surface is a challenging issue due to complex interaction of radar waves with vegetation layer and the underlying soil. Several studies utilized the Water Cloud Model (WCM) directly or by coupling it with surface inversion models, to compensate vegetation effects while...

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...

Food security can be assured with a reasonable crop yield forecast at a national and regional scale. The agencies require advance estimates of production of major crops at a regional scale for taking various policy decisions. Hence, it is necessary to develop operational systems for crop monitoring and yield forecasting. Unlike the traditional annu...

The present state of the art technologies for flood mapping are typically tested on small geographical regions due to limitation of resources, which hinders the implementation of real-time flood management activities. We proposed a unified framework (GEE4FLOOD) for rapid flood mapping in Google Earth Engine (GEE) cloud platform. With the unexpected...

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...

Estimation of bio-and geophysical parameters from Earth observation (EO) data is essential for developing applications on crop growth monitoring. High spatio-temporal resolution and wide spatial coverage provided by EO satellite data are key inputs for operational crop monitoring. In Synthetic Aperture Radar (SAR) applications , a semi-empirical mo...

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...

Accurate spatio-temporal classification of crops is of prime importance for in-season crop monitoring. Synthetic Aperture Radar (SAR) data provides diverse physical information about crop morphology. In the present work, we propose a day-wise and a time-series approach for crop classification using full-polarimetric SAR data. In this context, the 4...

Crop characterization using Compact-Pol Synthetic Aperture Radar (CP-SAR) data is of prime interest with the rapid advancements of SAR systems towards operational applications. It is noteworthy that as a good compromise between the dual and quad-polarized SAR systems, the CP-SAR offer advantages in terms of the larger swath and lower data rate. The...

Sentinel-1 SAR data preprocessing is essential for several earth observation applications, including land cover classification, change detection, vegetation monitoring, urban growth, natural hazards, etc. The information can be extracted from the 2x2 covariance matrix [C2] of Sentinel-1 dual-pol (VV-VH) acquisitions. To generate the covariance matr...

The Ground-Based Synthetic Aperture Radar (GB-SAR) technique is a reliable tool for deformation measurement due it is highly sensitive to small displacements and frequent coverage property. GB-SAR data processing is not as complex as conventional SAR data processing for displacement mapping using PSInSAR method. The processing involves several step...

Chennai, the capital city of Tamil Nadu state, India experienced a major disastrous flood during Nov-Dec 2015. The city is characterized by mixed land use with high built-up density. The freely available C-band Sentinel-1 temporal GRDH SAR images are used to analyze this flood event. We used the co-polarized (VV) SAR images for mapping the flood ar...

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....

In this paper, the height accuracy of various DEMs such as TanDEM-X Global DEM, newly released TanDEM-X 90 m DEM, TanDEM-X ascending or descending DEM, SRTM 30 m, 90 m DEMs, provisional version of the NASADEM, and the aerial LiDAR DEM are assessed over three different Indian terrains. The test sites deal with flat terrain, flat terrain with forest...

Studies on the sensitivity of microwave scattering to vegetation canopies have led the researchers to conclude that crop biophysical parameters can be modeled from Synthetic Aperture Radar (SAR) backscatter. In this study, we assess different methods of modeling the Leaf Area Index (LAI), an important biophysical indicator of crop productivity, fro...

The 2017 Mw 7.3 Iran-Iraq earthquake occurred in the seismically less active northern Zagros Mountains. In this study, DInSAR technique is used to derive the surface displacements of the earthquake using the Sentinel-1 and ALOS-2 images. One preseismic, three coseismic and a postseismic interferogram are generated. The coseismic interferograms did...

Compact polarimetry (CP) offers a tradeoff with fully polarimetric modes in terms of swath width, power budget, and polarimetric information content. In this letter, a classification comparison is made among real CP, simulated CP (SCP), and quad polarimetric (QP) data acquired from the L-band SAR system onboard the ALOS-2 satellite. The Wishart sup...

Collaborative field experiment for SAR and agriculture.

Accurate and precise topographic information from Digital Elevation Models (DEM) is of fundamental requirement for many geoscience and engineering applications. With a goal of providing accurate global topographic products, German Aerospace Centre (DLR) and Airbus Defence and Space developed X-band TanDEM-X mission. The TanDEM-X Global DEM is gener...

Earthquakes cause destruction and loss of human lives. Mapping the extent of surface displacements due to an earthquake is crucial for the damage assessment. Over the last two decades, Synthetic Aperture Radar Interferometry (InSAR) proved to be a prominent tool in precise mapping and measuring of ground displacements with millimetre-level accuracy...

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...

Remote sensing plays a prominent role in the rapid detection of the flood event at a regional level. In this paper, the potential of AMSR-E images in regional level flood detection was identified. The study area of the research covers a part of Krishna river basin in the Andhra Pradesh state of India. Spatio-temporal database of daily Land Surface...

Persistent Scatterer Interferometry (PSI) is an advanced technique to map ground surface displacements of an area over a period. The technique can measure deformation with a millimeter-level accuracy. It overcomes the limitations of Differential Synthetic Aperture Radar Interferometry (DInSAR) such as geometric, temporal decorrelation and atmospher...

Tuber initiation and tuber bulking stages are critical part of various phenological phases for potato production. Tuber initiation covers the period from the formation of spherical rhizome ends, the flowering and the start of tuber bulking. In general, the tuberization spans from 3 to 5 weeks after emergence and ends with the row closer i.e. canopi...

Climatological variables such as rainfall, temperature have been extensively used by researchers for drought monitoring at a larger spatial region. These variables have a direct influence on the soil moisture which in turn extends the application of soil moisture in drought assessment. With the advancement of technology, various satellites provide...

In this paper, a multi-target inversion scheme is adopted for joint estimation of crop biophysical parameters from dual-pol SAR data. The single-output support vector regression (SVR) method is extended to a multi-output support vector regression (MSVR) method to estimate biophysical parameters. The MSVR is implemented for simultaneous retrieval of...