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Dr. Hari Shanker Srivastava

IIRS, Dehradun, Indian Space Research Organization (ISRO), Department of Space, Government of India, Faculty Member

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Explored Microwave data from Ground based Scatterometer, ISRO C-band Airborne SAR, ERS-1 SAR, ERS-2 SAR, ERS-1/2 tandem mission, L-band JERS-1 SAR, X-C-L-band SIR-C/X-SAR, RADARSAT-1 SAR, ENVISAT-1 ASAR, Fully Polarimetric C-band RADARSAT-2 SAR, C-L-P-band fully polarimetric DLR E-SAR, Hybrid polarimetric C-band RISAT-1 SAR, passive AMSR-E & SMOS...
... for various applications in Agriculture, Soil moisture, Surface roughness, Surface water, Forestry, Wetland, Ecology, Human settlement, Interferometry (InSAR), Polarimetry (PolSAR), Interferometry Polarimetry (PolInSAR) &
Absolute Radiometric Calibration / Validation of ERS-1 SAR & RISAT-1 SAR.

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Hari Shanker Srivastava

falguni bhattacharya

Institute of Seismologic Research

Thota Sivasankar

North Eastern Space Application Center

pavan kumar sharma

Mohamed Musthafa

Indian Institute of Technology Bombay

Laura Bourgeau-Chavez

Michigan Technological University

Gagandeep Singh

University of Windsor

Gagandeep Singh

National Institute of Technology, Warangal

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Papers by Dr. Hari Shanker Srivastava

Explored and Demonstrated Potential Applications of Multi- Parametric Synthetic Aperture Radar in Wetland Studies in Context of

Wetland ecosystems have received little recognition on the vital role that they play for human we... more Wetland ecosystems have received little recognition on the vital role that they play for human well being. As a result of this, there is an alarming loss of wetlands. It is required to arrest the losses and to achieve optimal resource use with balanced priorities of biodiversity conservation. This calls for meaningful and timely information and data on wetland habitats, its fauna, flora and socioeconomic variables of relevance. Traditionally, the source of the spatial information that captures dynamics of a wetland ecosystem has been that of optical remote sensing data. Although optical remote sensing data is found to be very useful for wetland monitoring, cloud cover restricts the availability of satellite data during rainy season, which is main source of water for most of the inland wetlands. Moreover, delineation of several classes of importance for wetland ecosystem is also not clearly differentiable on optical remote sensing data. Synthetic Aperture Radar (SAR) can play an impo...

The Sensitivity of C-Band Hybrid Polarimetric RISAT-1 Sar Data to Leaf Area Index of Paddy Crop

ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018

Active microwave remote sensing data has become an important source to retrieve crop biophysical ... more Active microwave remote sensing data has become an important source to retrieve crop biophysical parameters due to its unique sensitivity towards geometrical, structural and dielectric properties of various crop components. The temporal variability of various crop biophysical parameters during crop cycle has significant impact on the overall crop yield. In this study, two RISAT-1 hybrid polarimetric temporal SAR datasets at ~32° incidence angle were acquired during 2015 Kharif season. The in-situ leaf area index (LAI) values from seventeen paddy fields were measured in synchrony to the satellite passes during both the campaigns. Analysis observed the decreasing trend of backscattering coefficients (σ°RH, σ°RV) with increase in LAI. Results indicate that the sensitivity of hybrid polarimetric parameters towards LAI, also depends on the change in crop structure due to crop growth. This study investigate the sensitivity of backscattering coefficients (σ°RH, σ°RV) and polarimetric parameters (even bounce, odd bounce and volume component) generated from m-δ, m-χ and m-α space decompositions towards LAI using empirical analysis. An increase of 0.16 in R 2 (from 0.63 to 0.79) clearly indicates that the polarimetric parameters (even bounce, odd bounce and volume component) are more sensitive to LAI of paddy crop than the backscattering coefficients (σ°RH, σ°RV). It has been identified that the combined use of backscattering coefficients as well as polarimetric parameters (even bounce, odd bounce and volume component) in the model, can significantly improve the accuracy of the LAI estimation.

An Insight Into the Volume Component Generated from RISAT-1 Hybrid Polarimetric Sar Data for Crop Biophysical Parameters Retrieval

ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018

Polarimetric parameters have been extensively used for target parameters retrieval than backscatt... more Polarimetric parameters have been extensively used for target parameters retrieval than backscattering coefficients. In previous studies, volume component generated from polarimetric SAR data has been considered as the return signal component from vegetation and intern used this for biophysical parameters retrieval. Un-polarized component of the return signal has been considered as volume component. The present study is mainly focused to analyze the volume component generated from C-band RISAT-1 hybrid polarimetric SAR data from wheat crop. Three temporal datasets acquired at ~31° central incidence angle between Jan and Mar 2016 over parts of Bharatpur and Mathura districts located in Rajasthan and Uttar Pradesh (India) have been used in this study. Water Cloud Model with Gaps has been considered for modeling the first Stokes parameter (g0), which represents total intensity of return signal, from wheat crop using LAI and Interaction factor as vegetation descriptors. The vegetation component derived using calibrated Water Cloud Model with Gaps has been analyzed with volume component derived from RISAT-1 hybrid polarimetric SAR data. The analyses observed that a significant difference during lower LAI values and shown comparably during higher LAI values. The higher values of volume component derived from RISAT-1 SAR data than modeled vegetation component indicates that the volume component can also be generated by underneath soil. It is also observed the difference in derived un-polarized component and modeled vegetation component has shown higher correlation with underneath soil moisture than directly correlating with derived un-polarized component. This study indicates that the volume component derived from hybrid polarimetric SAR data has return signals from vegetation as well as underneath soil.

Advances in Radar Remote Sensing of Agricultural Crops: A Review

International Journal on Advanced Science, Engineering and Information Technology, 2018

There are enormous advantages of a review article in the field of emerging technology like radar ... more There are enormous advantages of a review article in the field of emerging technology like radar remote sensing applications in agriculture. This paper aims to report select recent advancements in the field of Synthetic Aperture Radar (SAR) remote sensing of crops. In order to make the paper comprehensive and more meaningful for the readers, an attempt has also been made to include discussion on various technologies of SAR sensors used for remote sensing of agricultural crops viz. basic SAR sensor, SAR interferometry (InSAR), SAR polarimetry (PolSAR) and polarimetric interferometry SAR (PolInSAR). The paper covers all the methodologies used for various agricultural applications like empirically based models, machine learning based models and radiative transfer theorem based models. A thorough literature review of more than 100 research papers indicates that SAR polarimetry can be used effectively for crop inventory and biophysical parameters estimation such are leaf area index, plant water content, and biomass but shown less sensitivity towards plant height as compared to SAR interferometry. Polarimetric SAR Interferometry is preferable for taking advantage of both SAR polarimetry and SAR interferometry. Numerous studies based upon multi-parametric SAR indicate that optimum selection of SAR sensor parameters enhances SAR sensitivity as a whole for various agricultural applications. It has been observed that researchers are widely using three models such are empirical, machine learning and radiative transfer theorem based models. Machine learning based models are identified as a better approach for crop monitoring using radar remote sensing data. It is expected that the review article will not only generate interest amongst the readers to explore and exploit radar remote sensing for various agricultural applications but also provide a ready reference to the researchers working in this field.

Analysis of Monthly Soil Moisture Variations Derived from Amsr-E for the Year 2010 Over Indian Subcontinent

This paper explores the credibility and utility of AMSR-E soil moisture data (AE_Land 3 product) ... more This paper explores the credibility and utility of AMSR-E soil moisture data (AE_Land 3 product) to understand the soil moisture variation over Indian subcontinent in the year 2010. The data product was processed to generate monthly average soil moisture maps. The maps were analyzed to study the soil moisture pattern over the entire region qualitatively. The soil moisture values from the generated maps were compared with the rainfall data and it was found to be very well complementing the actual rainfall variation. The study shows that the soil moisture variation is in line with the seasonal change and the observed rainfall variation.

Estimating wheat yield: an approach for estimating number of grains using cross-polarised ENVISAT-1 ASAR data

SPIE Proceedings, 2006

In this paper an attempt to model wheat yield is made by exploiting characteristic interaction of... more In this paper an attempt to model wheat yield is made by exploiting characteristic interaction of cross-polarised SAR with wheat crop. SAR backscatter from a crop field is affected by the density, structure, volume and the moisture content of various components of plant (viz. head, stem, leaf) alongwith soil moisture. Hence, to effectively handle the influence of each of these components of the plant on SAR backscatter, a plant parameter, termed as Interaction Factor (IF) is conceptualised by combining volume, moisture, height for each of the component and density of plant. For this purpose, detailed experiment over farmers' fields was carried out in synchrony with SAR acquisition involving in-depth measurements on volume, moisture content and height of various components of wheat plant, number of grains, plant density and soil moisture. Stepwise regression analysis revealed that IF Head significantly affects the shallow incidence angle, cross-polarised C-band SAR backscatter. IF Head is also highly correlated to the number of grains. This is attributed to the fact that parameters of the wheat head from which IF Head is calculated, namely moisture, volume and height, determine eventual number of grains. The study offers an approach for estimating wheat yield by retrieving number of grains from shallow incidence angle cross-polarised SAR data.

How far SAR has fulfilled its expectation for soil moisture retrieval

SPIE Proceedings, 2006

Comparative evaluation of the sensitivity of multi‐polarized multi‐frequency SAR backscatter to plant density

International Journal of Remote Sensing, 2006

Page 1. Comparative evaluation of the sensitivity of multi-polarized multi-frequency SAR backscat... more

Multi-frequency and multi-polarized SAR response to thin vegetation and scattered trees

Current science, 2009

This communication highlights the results of a study carried out to understand the Synthetic Aper... more

Use of synthetic aperture radar polarimetry to characterize wetland targets of Keoladeo National Park, Bharatpur, India

Current Science, 2009

Timely and accurate information about various habitats of a wetland ecosystem is necessary for th... more

Soil moisture variation over parts of Saharanpur and Haridwar districts (India) during November-2006 to June-2007 as observed by multi-polarized (VV/HH & VV/VH) ENVISAT-1 temporal ASAR data

Microwave remote sensing is one of the most promising tools for soil moisture estimation owing to... more Microwave remote sensing is one of the most promising tools for soil moisture estimation owing to its high sensitivity towards dielectric properties of the target under consideration. Many ground-based scatterometer experiments were carried out for exploring this potential. After the launch of ERS-1, expectation was generated to operationally retrieve large area soil moisture information. However, along with its strong sensitivity to soil moisture, SAR is also sensitive to other target parameters like surface roughness and vegetation (crop) cover. Single channel SAR was found to be inadequate to resolve the effects of these parameters. Low and high incidence angle RADARSAT-1 SAR was exploited by researchers for incorporating the effects of surface roughness and crop cover in the soil moisture retrieval models. Since the moisture and roughness should remain unchanged between low and high angle SAR acquisitions, the gap period between the two acquisitions should be minimum. However, f...

Study of Hybrid Polarimetric Parameters generated from RISAT-1 SAR data for various Land Cover targets

Hybrid polarimetric synthetic aperture radar (SAR) is having enormous advantages over linear pola... more Hybrid polarimetric synthetic aperture radar (SAR) is having enormous advantages over linear polarimetric like self-calibration, low susceptibility to noise, higher incident angle range coverage, larger swath coverage and lower rotational sensitivity of the target. This makes researchers interested to study the hybrid polarimetric SAR data for various remote sensing applications. In this paper, backscatter signals and scattering decomposition from hybrid polarimetric Radar Imaging Satellite-1 (RISAT-1) SAR data for various land cover targets have been studied. Even though SAR transmits right circular polarized signal, the return RADAR signal may be partially polarized (which means sum of completely polarized and un-polarized signal). The RADAR return signal and scattering decomposition varies for different land cover targets depending on the geometrical, structural and electrical properties of the target under consideration. Here, Stokes classical parameters are used to study the RA...

Comparative evaluation of the sensitivity of multi‐polarized multi‐frequency SAR backscatter to plant density

by Jai Singh PARIHAR, Dr. Hari Shanker Srivastava, and Sushma Panigrahy

International Journal of Remote Sensing, 2006

Interaction of synthetic aperture radar (SAR) with vegetation is volumetric in nature, hence SAR ... more Interaction of synthetic aperture radar (SAR) with vegetation is volumetric in nature, hence SAR is sensitive to the variation in vegetation density. At the same time SAR is also sensitive to other target properties such as canopy structure, canopy moisture, soil moisture and surface roughness of the underlying soil. However, the sensitivity of SAR backscatter to the vegetation density depends upon the frequency, polarization and angle of incidence at which the SAR is operated. This paper provides comparative evaluation of the sensitivity of multi‐frequency and multi‐polarized SAR backscatter to the plant density of Prosopis juliflora, a thorny plant. Monitoring of P. juliflora is of importance as the state forest department introduced it to arrest the spread of desert. In carrying out this study, data from the SIR‐C/X‐SAR mission over parts of Gujarat, India, have been used. In the present study, the variation of multi‐frequency (L and C) and multi‐polarized (HH, VV and VH) SAR backscatter with plant density has been studied. The results clearly indicate that cross‐polarized SAR backscatter at longer wavelength is the appropriate choice for the quantitative retrieval of plant density.

Passive Microwave Remote Sensing of Soil Moisture: A Step-By- Step Detailed Methodology using AMSR-E Data over Indian Sub- Continent

by Dr. Hari Shanker Srivastava and Gagandeep Singh

This paper presents a detailed methodology to process AMSR-E soil moisture data to generate avera... more This paper presents a detailed methodology to process AMSR-E soil moisture data to generate average soil moisture maps of desired durations be it weekly, monthly or yearly over a large geographical area like a continent or a sub-continent. The paper also explores utility of AMSR-E soil moisture product (AE_Land 3 product) to understand the soil moisture variations over Indian subcontinent by analysing daily soil moisture data for entire calendar year of 2009. In order to demonstrate the developed methodology the year 2009 was selected wherein a total of 730 AMSR-E daily scenes (365 each for ascending as well as descending passes) were processed and analysed. Although the absolute values of soil moisture derived from AMSR-E are not showing good agreement with soil moisture status on ground which is due to large variability in soil moisture within the coarse-resolution cell offered by passive sensors [1] but in general AMSR-E derived soil moisture values are well explained on the basis of rainfall data and agricultural practices adopted in different states of Indian sub-continent. The soundness of the detailed methodology proposed in this paper has been well supported by studying the variations in AMSR-E derived soil moisture with seasonal variations and rainfall data. It has been observed that the soil moisture variations are in line with the seasonal changes as well as the rainfall variations.

Land slide hazard zone mapping of Aizawl district using remote sensing and GIS techniques

An approach to validate soil moisture derived from passive microwave sensors using SAR as an interface

Validation of soil moisture derived from space-borne passive microwave sensors remains a challeng... more Validation of soil moisture derived from space-borne passive microwave sensors remains a challenging task owing to the large variability in soil moisture within the coarse-resolution cell offered by passive sensors. In this article, nine spatial/temporal synthetic aperture radar (SAR) data sets from Radar Satellite-1 (Radarsat-1) and Environmental Satellite-1 (Envisat-1) Advanced Synthetic Aperture Radar (ASAR) were used as an interface to upscale the field-level soil moisture to soil moisture at a 25 km × 25 km grid, the scale at which the Advanced Microwave Scanning Radiometer for the EOS (Earth Observing System) (AMSR-E) level-3 soil moisture product is available, leading to a total of 68 such grids where there is a pair of SAR-derived and corresponding AMSR-E-derived values. Out of the these 68 grid cells, each of size 25 km × 25 km, pair data from nine dates, data corresponding to 51 grid cell pairs (from six dates) were used for the development of the approach and data corresponding to 17 grid cell pairs (from three dates) were used for validating the approach. It is observed that while the spatial variation in SAR- and AMSR-E-derived soil moisture is broadly similar, there exists a bias in the difference between AMSR-E- and SAR-derived soil moisture. The root mean square (RMS) difference between AMSR-E soil moisture and SAR-derived soil moisture at 25 km over the model development sample of 51 grid cells, each of 25 km × 25 km, was observed to be 4.2 (%g cm–3). The study shows that the bias is significantly affected by the AMSR-E vegetation/roughness parameter, g, which is an indicator of the prevailing vegetation/surface roughness conditions. This dependence of the bias on g was exploited to arrive at modified soil moisture estimates at 25 km. The RMS difference between the modified AMSR-E soil moisture at 25 km and the SAR-derived soil moisture was observed to be 2.13 (%g cm–3) over a validation sample of 17 grid cells each of size 25 km × 25 km, comprising extreme, dry and wet, and soil moisture conditions. This demonstrative study provides the feasibility of calibrating and improving the soil moisture product from coarse-resolution space-borne passive sensors with the help of soil moisture derived using SAR. The approach is demonstrated for validating passive radiometer-derived soil moisture over bare/crop-covered conditions through an experiment involving 68 25 km × 25 km grid cells spread over nine temporal/spatial Radarsat and Envisat-1 satellite SAR data sets and synchronous ground soil moisture measurements over farmers’ fields, covering a large range of soil/crop conditions prevailing during the nine months of SAR data acquisition. Hence the results reported in this manuscript are encouraging.

ANALYSIS OF MONTHLY SOIL MOISTURE VARIATIONS DERIVED FROM AMSR-E FOR THE YEAR 2010 OVER INDIAN SUBCONTINENT

by Gagandeep Singh and Dr. Hari Shanker Srivastava

Proceedings of International Conference on Sustainable Energy and Built Environment

This paper explores the credibility and utility of AMSR-E soil moisture data (AE_Land 3 product) ... more This paper explores the credibility and utility of AMSR-E soil moisture data (AE_Land 3 product) to understand the soil moisture variation over Indian subcontinent in the year 2010. The data product was processed to generate monthly average soil moisture maps. The maps were analyzed to study the soil moisture pattern over the entire region qualitatively. The soil moisture values from the generated maps were compared with the rainfall data and it was found to be very well complementing the actual rainfall variation. The study shows that the soil moisture variation is in line with the seasonal change and the observed rainfall variation.

Soil moisture variation over parts of Saharanpur and Haridwar districts (India) during November-2006 to June-2007 as observed by multi-polarized (VV/HH & VV/VH) ENVISAT-1 temporal ASAR data

by Thota Sivasankar, pavan kumar sharma, and Dr. Hari Shanker Srivastava

International Journal of Advanced Engineering Research and Science (IJAERS), Jan 2015

Microwave remote sensing is one of the most promising tools for soil moisture estimation owing t... more Microwave remote sensing is one of the most promising tools for soil moisture estimation owing to its high sensitivity towards dielectric properties of the target under consideration. Many ground-based scatterometer experiments were carried out for exploring this potential. After the launch of ERS-1, expectation was generated to operationally retrieve large area soil moisture information. However, along with its strong sensitivity to soil moisture, SAR is also sensitive to other target parameters like surface roughness and vegetation (crop) cover. Single channel SAR was found to be inadequate to resolve the effects of these parameters. Low and high incidence angle RADARSAT-1 SAR was exploited by researchers for incorporating the effects of surface roughness and crop cover in the soil moisture retrieval models. Since the moisture and roughness should remain unchanged between low and high angle SAR acquisitions, the gap period between the two acquisitions should be minimum. However, for RADARSAT-1 the gap is typically of the order of 3 days. To overcome this difficulty, simultaneously acquired ENVISAT-1 ASAR HH/VV and VV/VH data was studied for operational soil moisture mapping. Cross-polarized SAR data has been exploited for its sensitivity towards vegetation for crop-covered fields where as co-polarization ratio has been used to incorporate effect of surface roughness for the case of bare agricultural fields. In order to demonstrate the potential of the developed methodology, an attempt has also been made to study variation of soil moisture status during November-2006 to June-2007 over parts of Saharanpur and Haridwar districts using ENVISAT-1 ASAR data sets acquired at IS1 beam mode. Temporal soil moisture status which reflects the irrigation pattern adopted by the farmers of the study area is matching with the agricultural activities like sowing and harvesting. Study indicates the potential of soil moisture information for agricultural applications like irrigation scheduling.

Study of Hybrid Polarimetric Parameters generated from RISAT-1 SAR data for various Land Cover targets

by Thota Sivasankar, pavan kumar sharma, and Dr. Hari Shanker Srivastava

Hybrid polarimetric synthetic aperture radar (SAR) is having enormous advantages over linear pola... more Hybrid polarimetric synthetic aperture radar (SAR) is having enormous advantages over linear polarimetric like self-calibration, low susceptibility to noise, higher incident angle range coverage, larger swath coverage and lower rotational sensitivity of the target. This makes researchers interested to study the hybrid polarimetric SAR data for various remote sensing applications. In this paper, backscatter signals and scattering decomposition from hybrid polarimetric Radar Imaging Satellite-1 (RISAT-1) SAR data for various land cover targets have been studied. Even though SAR transmits right circular polarized signal, the return RADAR signal may be partially polarized (which means sum of completely polarized and un-polarized signal). The RADAR return signal and scattering decomposition varies for different land cover targets depending on the geometrical, structural and electrical properties of the target under consideration. Here, Stokes classical parameters are used to study the RADAR return signal. m-δ and m-χ space decomposition are used to study the scattering mechanism. Signature study of polarimetric parameters has also been carried out to understand scattering mechanism in terms of even bounce, odd bounce and volume component. It is observed that depolarization effect is more sensitive for vegetation whereas the backscatter signal strength is low from surface water bodies due to specular reflection. It is also observed that volume scattering component is similar in both the decompositions. However, even bounce is over estimated in m-χ as compared to m-δ decomposition for all the land cover targets like water, forest, sugarcane, wheat, fallow, dry river bed and built-up.

ANALYSIS OF MONTHLY SOIL MOISTURE VARIATIONS DERIVED FROM AMSR-E FOR THE YEAR 2010 OVER INDIAN SUBCONTINENT

This paper explores the credibility and utility of AMSR-E soil moisture data (AE_Land 3 product) ... more This paper explores the credibility and utility of AMSR-E soil moisture data (AE_Land 3 product) to understand the soil moisture variation over Indian subcontinent in the year 2010. The data product was processed to generate monthly average soil moisture maps. The maps were analyzed to study the soil moisture pattern over the entire region qualitatively. The soil moisture values from the generated maps were compared with the rainfall data and it was found to be very well complementing the actual rainfall variation. The study shows that the soil moisture variation is in line with the seasonal change and the observed rainfall variation.

Explored and Demonstrated Potential Applications of Multi- Parametric Synthetic Aperture Radar in Wetland Studies in Context of

Wetland ecosystems have received little recognition on the vital role that they play for human we... more Wetland ecosystems have received little recognition on the vital role that they play for human well being. As a result of this, there is an alarming loss of wetlands. It is required to arrest the losses and to achieve optimal resource use with balanced priorities of biodiversity conservation. This calls for meaningful and timely information and data on wetland habitats, its fauna, flora and socioeconomic variables of relevance. Traditionally, the source of the spatial information that captures dynamics of a wetland ecosystem has been that of optical remote sensing data. Although optical remote sensing data is found to be very useful for wetland monitoring, cloud cover restricts the availability of satellite data during rainy season, which is main source of water for most of the inland wetlands. Moreover, delineation of several classes of importance for wetland ecosystem is also not clearly differentiable on optical remote sensing data. Synthetic Aperture Radar (SAR) can play an impo...

The Sensitivity of C-Band Hybrid Polarimetric RISAT-1 Sar Data to Leaf Area Index of Paddy Crop

ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018

Active microwave remote sensing data has become an important source to retrieve crop biophysical ... more Active microwave remote sensing data has become an important source to retrieve crop biophysical parameters due to its unique sensitivity towards geometrical, structural and dielectric properties of various crop components. The temporal variability of various crop biophysical parameters during crop cycle has significant impact on the overall crop yield. In this study, two RISAT-1 hybrid polarimetric temporal SAR datasets at ~32° incidence angle were acquired during 2015 Kharif season. The in-situ leaf area index (LAI) values from seventeen paddy fields were measured in synchrony to the satellite passes during both the campaigns. Analysis observed the decreasing trend of backscattering coefficients (σ°RH, σ°RV) with increase in LAI. Results indicate that the sensitivity of hybrid polarimetric parameters towards LAI, also depends on the change in crop structure due to crop growth. This study investigate the sensitivity of backscattering coefficients (σ°RH, σ°RV) and polarimetric parameters (even bounce, odd bounce and volume component) generated from m-δ, m-χ and m-α space decompositions towards LAI using empirical analysis. An increase of 0.16 in R 2 (from 0.63 to 0.79) clearly indicates that the polarimetric parameters (even bounce, odd bounce and volume component) are more sensitive to LAI of paddy crop than the backscattering coefficients (σ°RH, σ°RV). It has been identified that the combined use of backscattering coefficients as well as polarimetric parameters (even bounce, odd bounce and volume component) in the model, can significantly improve the accuracy of the LAI estimation.

An Insight Into the Volume Component Generated from RISAT-1 Hybrid Polarimetric Sar Data for Crop Biophysical Parameters Retrieval

ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, 2018

Polarimetric parameters have been extensively used for target parameters retrieval than backscatt... more Polarimetric parameters have been extensively used for target parameters retrieval than backscattering coefficients. In previous studies, volume component generated from polarimetric SAR data has been considered as the return signal component from vegetation and intern used this for biophysical parameters retrieval. Un-polarized component of the return signal has been considered as volume component. The present study is mainly focused to analyze the volume component generated from C-band RISAT-1 hybrid polarimetric SAR data from wheat crop. Three temporal datasets acquired at ~31° central incidence angle between Jan and Mar 2016 over parts of Bharatpur and Mathura districts located in Rajasthan and Uttar Pradesh (India) have been used in this study. Water Cloud Model with Gaps has been considered for modeling the first Stokes parameter (g0), which represents total intensity of return signal, from wheat crop using LAI and Interaction factor as vegetation descriptors. The vegetation component derived using calibrated Water Cloud Model with Gaps has been analyzed with volume component derived from RISAT-1 hybrid polarimetric SAR data. The analyses observed that a significant difference during lower LAI values and shown comparably during higher LAI values. The higher values of volume component derived from RISAT-1 SAR data than modeled vegetation component indicates that the volume component can also be generated by underneath soil. It is also observed the difference in derived un-polarized component and modeled vegetation component has shown higher correlation with underneath soil moisture than directly correlating with derived un-polarized component. This study indicates that the volume component derived from hybrid polarimetric SAR data has return signals from vegetation as well as underneath soil.

Advances in Radar Remote Sensing of Agricultural Crops: A Review

International Journal on Advanced Science, Engineering and Information Technology, 2018

There are enormous advantages of a review article in the field of emerging technology like radar ... more There are enormous advantages of a review article in the field of emerging technology like radar remote sensing applications in agriculture. This paper aims to report select recent advancements in the field of Synthetic Aperture Radar (SAR) remote sensing of crops. In order to make the paper comprehensive and more meaningful for the readers, an attempt has also been made to include discussion on various technologies of SAR sensors used for remote sensing of agricultural crops viz. basic SAR sensor, SAR interferometry (InSAR), SAR polarimetry (PolSAR) and polarimetric interferometry SAR (PolInSAR). The paper covers all the methodologies used for various agricultural applications like empirically based models, machine learning based models and radiative transfer theorem based models. A thorough literature review of more than 100 research papers indicates that SAR polarimetry can be used effectively for crop inventory and biophysical parameters estimation such are leaf area index, plant water content, and biomass but shown less sensitivity towards plant height as compared to SAR interferometry. Polarimetric SAR Interferometry is preferable for taking advantage of both SAR polarimetry and SAR interferometry. Numerous studies based upon multi-parametric SAR indicate that optimum selection of SAR sensor parameters enhances SAR sensitivity as a whole for various agricultural applications. It has been observed that researchers are widely using three models such are empirical, machine learning and radiative transfer theorem based models. Machine learning based models are identified as a better approach for crop monitoring using radar remote sensing data. It is expected that the review article will not only generate interest amongst the readers to explore and exploit radar remote sensing for various agricultural applications but also provide a ready reference to the researchers working in this field.

Analysis of Monthly Soil Moisture Variations Derived from Amsr-E for the Year 2010 Over Indian Subcontinent

This paper explores the credibility and utility of AMSR-E soil moisture data (AE_Land 3 product) ... more This paper explores the credibility and utility of AMSR-E soil moisture data (AE_Land 3 product) to understand the soil moisture variation over Indian subcontinent in the year 2010. The data product was processed to generate monthly average soil moisture maps. The maps were analyzed to study the soil moisture pattern over the entire region qualitatively. The soil moisture values from the generated maps were compared with the rainfall data and it was found to be very well complementing the actual rainfall variation. The study shows that the soil moisture variation is in line with the seasonal change and the observed rainfall variation.

Estimating wheat yield: an approach for estimating number of grains using cross-polarised ENVISAT-1 ASAR data

SPIE Proceedings, 2006

In this paper an attempt to model wheat yield is made by exploiting characteristic interaction of... more In this paper an attempt to model wheat yield is made by exploiting characteristic interaction of cross-polarised SAR with wheat crop. SAR backscatter from a crop field is affected by the density, structure, volume and the moisture content of various components of plant (viz. head, stem, leaf) alongwith soil moisture. Hence, to effectively handle the influence of each of these components of the plant on SAR backscatter, a plant parameter, termed as Interaction Factor (IF) is conceptualised by combining volume, moisture, height for each of the component and density of plant. For this purpose, detailed experiment over farmers' fields was carried out in synchrony with SAR acquisition involving in-depth measurements on volume, moisture content and height of various components of wheat plant, number of grains, plant density and soil moisture. Stepwise regression analysis revealed that IF Head significantly affects the shallow incidence angle, cross-polarised C-band SAR backscatter. IF Head is also highly correlated to the number of grains. This is attributed to the fact that parameters of the wheat head from which IF Head is calculated, namely moisture, volume and height, determine eventual number of grains. The study offers an approach for estimating wheat yield by retrieving number of grains from shallow incidence angle cross-polarised SAR data.

How far SAR has fulfilled its expectation for soil moisture retrieval

SPIE Proceedings, 2006

Comparative evaluation of the sensitivity of multi‐polarized multi‐frequency SAR backscatter to plant density

International Journal of Remote Sensing, 2006

Page 1. Comparative evaluation of the sensitivity of multi-polarized multi-frequency SAR backscat... more

Multi-frequency and multi-polarized SAR response to thin vegetation and scattered trees

Current science, 2009

This communication highlights the results of a study carried out to understand the Synthetic Aper... more

Use of synthetic aperture radar polarimetry to characterize wetland targets of Keoladeo National Park, Bharatpur, India

Current Science, 2009

Timely and accurate information about various habitats of a wetland ecosystem is necessary for th... more

Soil moisture variation over parts of Saharanpur and Haridwar districts (India) during November-2006 to June-2007 as observed by multi-polarized (VV/HH & VV/VH) ENVISAT-1 temporal ASAR data

Microwave remote sensing is one of the most promising tools for soil moisture estimation owing to... more Microwave remote sensing is one of the most promising tools for soil moisture estimation owing to its high sensitivity towards dielectric properties of the target under consideration. Many ground-based scatterometer experiments were carried out for exploring this potential. After the launch of ERS-1, expectation was generated to operationally retrieve large area soil moisture information. However, along with its strong sensitivity to soil moisture, SAR is also sensitive to other target parameters like surface roughness and vegetation (crop) cover. Single channel SAR was found to be inadequate to resolve the effects of these parameters. Low and high incidence angle RADARSAT-1 SAR was exploited by researchers for incorporating the effects of surface roughness and crop cover in the soil moisture retrieval models. Since the moisture and roughness should remain unchanged between low and high angle SAR acquisitions, the gap period between the two acquisitions should be minimum. However, f...

Study of Hybrid Polarimetric Parameters generated from RISAT-1 SAR data for various Land Cover targets

Hybrid polarimetric synthetic aperture radar (SAR) is having enormous advantages over linear pola... more Hybrid polarimetric synthetic aperture radar (SAR) is having enormous advantages over linear polarimetric like self-calibration, low susceptibility to noise, higher incident angle range coverage, larger swath coverage and lower rotational sensitivity of the target. This makes researchers interested to study the hybrid polarimetric SAR data for various remote sensing applications. In this paper, backscatter signals and scattering decomposition from hybrid polarimetric Radar Imaging Satellite-1 (RISAT-1) SAR data for various land cover targets have been studied. Even though SAR transmits right circular polarized signal, the return RADAR signal may be partially polarized (which means sum of completely polarized and un-polarized signal). The RADAR return signal and scattering decomposition varies for different land cover targets depending on the geometrical, structural and electrical properties of the target under consideration. Here, Stokes classical parameters are used to study the RA...

Comparative evaluation of the sensitivity of multi‐polarized multi‐frequency SAR backscatter to plant density

by Jai Singh PARIHAR, Dr. Hari Shanker Srivastava, and Sushma Panigrahy

International Journal of Remote Sensing, 2006

Interaction of synthetic aperture radar (SAR) with vegetation is volumetric in nature, hence SAR ... more Interaction of synthetic aperture radar (SAR) with vegetation is volumetric in nature, hence SAR is sensitive to the variation in vegetation density. At the same time SAR is also sensitive to other target properties such as canopy structure, canopy moisture, soil moisture and surface roughness of the underlying soil. However, the sensitivity of SAR backscatter to the vegetation density depends upon the frequency, polarization and angle of incidence at which the SAR is operated. This paper provides comparative evaluation of the sensitivity of multi‐frequency and multi‐polarized SAR backscatter to the plant density of Prosopis juliflora, a thorny plant. Monitoring of P. juliflora is of importance as the state forest department introduced it to arrest the spread of desert. In carrying out this study, data from the SIR‐C/X‐SAR mission over parts of Gujarat, India, have been used. In the present study, the variation of multi‐frequency (L and C) and multi‐polarized (HH, VV and VH) SAR backscatter with plant density has been studied. The results clearly indicate that cross‐polarized SAR backscatter at longer wavelength is the appropriate choice for the quantitative retrieval of plant density.

Passive Microwave Remote Sensing of Soil Moisture: A Step-By- Step Detailed Methodology using AMSR-E Data over Indian Sub- Continent

by Dr. Hari Shanker Srivastava and Gagandeep Singh

This paper presents a detailed methodology to process AMSR-E soil moisture data to generate avera... more This paper presents a detailed methodology to process AMSR-E soil moisture data to generate average soil moisture maps of desired durations be it weekly, monthly or yearly over a large geographical area like a continent or a sub-continent. The paper also explores utility of AMSR-E soil moisture product (AE_Land 3 product) to understand the soil moisture variations over Indian subcontinent by analysing daily soil moisture data for entire calendar year of 2009. In order to demonstrate the developed methodology the year 2009 was selected wherein a total of 730 AMSR-E daily scenes (365 each for ascending as well as descending passes) were processed and analysed. Although the absolute values of soil moisture derived from AMSR-E are not showing good agreement with soil moisture status on ground which is due to large variability in soil moisture within the coarse-resolution cell offered by passive sensors [1] but in general AMSR-E derived soil moisture values are well explained on the basis of rainfall data and agricultural practices adopted in different states of Indian sub-continent. The soundness of the detailed methodology proposed in this paper has been well supported by studying the variations in AMSR-E derived soil moisture with seasonal variations and rainfall data. It has been observed that the soil moisture variations are in line with the seasonal changes as well as the rainfall variations.

Land slide hazard zone mapping of Aizawl district using remote sensing and GIS techniques

An approach to validate soil moisture derived from passive microwave sensors using SAR as an interface

Validation of soil moisture derived from space-borne passive microwave sensors remains a challeng... more Validation of soil moisture derived from space-borne passive microwave sensors remains a challenging task owing to the large variability in soil moisture within the coarse-resolution cell offered by passive sensors. In this article, nine spatial/temporal synthetic aperture radar (SAR) data sets from Radar Satellite-1 (Radarsat-1) and Environmental Satellite-1 (Envisat-1) Advanced Synthetic Aperture Radar (ASAR) were used as an interface to upscale the field-level soil moisture to soil moisture at a 25 km × 25 km grid, the scale at which the Advanced Microwave Scanning Radiometer for the EOS (Earth Observing System) (AMSR-E) level-3 soil moisture product is available, leading to a total of 68 such grids where there is a pair of SAR-derived and corresponding AMSR-E-derived values. Out of the these 68 grid cells, each of size 25 km × 25 km, pair data from nine dates, data corresponding to 51 grid cell pairs (from six dates) were used for the development of the approach and data corresponding to 17 grid cell pairs (from three dates) were used for validating the approach. It is observed that while the spatial variation in SAR- and AMSR-E-derived soil moisture is broadly similar, there exists a bias in the difference between AMSR-E- and SAR-derived soil moisture. The root mean square (RMS) difference between AMSR-E soil moisture and SAR-derived soil moisture at 25 km over the model development sample of 51 grid cells, each of 25 km × 25 km, was observed to be 4.2 (%g cm–3). The study shows that the bias is significantly affected by the AMSR-E vegetation/roughness parameter, g, which is an indicator of the prevailing vegetation/surface roughness conditions. This dependence of the bias on g was exploited to arrive at modified soil moisture estimates at 25 km. The RMS difference between the modified AMSR-E soil moisture at 25 km and the SAR-derived soil moisture was observed to be 2.13 (%g cm–3) over a validation sample of 17 grid cells each of size 25 km × 25 km, comprising extreme, dry and wet, and soil moisture conditions. This demonstrative study provides the feasibility of calibrating and improving the soil moisture product from coarse-resolution space-borne passive sensors with the help of soil moisture derived using SAR. The approach is demonstrated for validating passive radiometer-derived soil moisture over bare/crop-covered conditions through an experiment involving 68 25 km × 25 km grid cells spread over nine temporal/spatial Radarsat and Envisat-1 satellite SAR data sets and synchronous ground soil moisture measurements over farmers’ fields, covering a large range of soil/crop conditions prevailing during the nine months of SAR data acquisition. Hence the results reported in this manuscript are encouraging.

ANALYSIS OF MONTHLY SOIL MOISTURE VARIATIONS DERIVED FROM AMSR-E FOR THE YEAR 2010 OVER INDIAN SUBCONTINENT

by Gagandeep Singh and Dr. Hari Shanker Srivastava

Proceedings of International Conference on Sustainable Energy and Built Environment

This paper explores the credibility and utility of AMSR-E soil moisture data (AE_Land 3 product) ... more This paper explores the credibility and utility of AMSR-E soil moisture data (AE_Land 3 product) to understand the soil moisture variation over Indian subcontinent in the year 2010. The data product was processed to generate monthly average soil moisture maps. The maps were analyzed to study the soil moisture pattern over the entire region qualitatively. The soil moisture values from the generated maps were compared with the rainfall data and it was found to be very well complementing the actual rainfall variation. The study shows that the soil moisture variation is in line with the seasonal change and the observed rainfall variation.

Soil moisture variation over parts of Saharanpur and Haridwar districts (India) during November-2006 to June-2007 as observed by multi-polarized (VV/HH & VV/VH) ENVISAT-1 temporal ASAR data

by Thota Sivasankar, pavan kumar sharma, and Dr. Hari Shanker Srivastava

International Journal of Advanced Engineering Research and Science (IJAERS), Jan 2015

Microwave remote sensing is one of the most promising tools for soil moisture estimation owing t... more Microwave remote sensing is one of the most promising tools for soil moisture estimation owing to its high sensitivity towards dielectric properties of the target under consideration. Many ground-based scatterometer experiments were carried out for exploring this potential. After the launch of ERS-1, expectation was generated to operationally retrieve large area soil moisture information. However, along with its strong sensitivity to soil moisture, SAR is also sensitive to other target parameters like surface roughness and vegetation (crop) cover. Single channel SAR was found to be inadequate to resolve the effects of these parameters. Low and high incidence angle RADARSAT-1 SAR was exploited by researchers for incorporating the effects of surface roughness and crop cover in the soil moisture retrieval models. Since the moisture and roughness should remain unchanged between low and high angle SAR acquisitions, the gap period between the two acquisitions should be minimum. However, for RADARSAT-1 the gap is typically of the order of 3 days. To overcome this difficulty, simultaneously acquired ENVISAT-1 ASAR HH/VV and VV/VH data was studied for operational soil moisture mapping. Cross-polarized SAR data has been exploited for its sensitivity towards vegetation for crop-covered fields where as co-polarization ratio has been used to incorporate effect of surface roughness for the case of bare agricultural fields. In order to demonstrate the potential of the developed methodology, an attempt has also been made to study variation of soil moisture status during November-2006 to June-2007 over parts of Saharanpur and Haridwar districts using ENVISAT-1 ASAR data sets acquired at IS1 beam mode. Temporal soil moisture status which reflects the irrigation pattern adopted by the farmers of the study area is matching with the agricultural activities like sowing and harvesting. Study indicates the potential of soil moisture information for agricultural applications like irrigation scheduling.

Study of Hybrid Polarimetric Parameters generated from RISAT-1 SAR data for various Land Cover targets

by Thota Sivasankar, pavan kumar sharma, and Dr. Hari Shanker Srivastava

Hybrid polarimetric synthetic aperture radar (SAR) is having enormous advantages over linear pola... more Hybrid polarimetric synthetic aperture radar (SAR) is having enormous advantages over linear polarimetric like self-calibration, low susceptibility to noise, higher incident angle range coverage, larger swath coverage and lower rotational sensitivity of the target. This makes researchers interested to study the hybrid polarimetric SAR data for various remote sensing applications. In this paper, backscatter signals and scattering decomposition from hybrid polarimetric Radar Imaging Satellite-1 (RISAT-1) SAR data for various land cover targets have been studied. Even though SAR transmits right circular polarized signal, the return RADAR signal may be partially polarized (which means sum of completely polarized and un-polarized signal). The RADAR return signal and scattering decomposition varies for different land cover targets depending on the geometrical, structural and electrical properties of the target under consideration. Here, Stokes classical parameters are used to study the RADAR return signal. m-δ and m-χ space decomposition are used to study the scattering mechanism. Signature study of polarimetric parameters has also been carried out to understand scattering mechanism in terms of even bounce, odd bounce and volume component. It is observed that depolarization effect is more sensitive for vegetation whereas the backscatter signal strength is low from surface water bodies due to specular reflection. It is also observed that volume scattering component is similar in both the decompositions. However, even bounce is over estimated in m-χ as compared to m-δ decomposition for all the land cover targets like water, forest, sugarcane, wheat, fallow, dry river bed and built-up.

ANALYSIS OF MONTHLY SOIL MOISTURE VARIATIONS DERIVED FROM AMSR-E FOR THE YEAR 2010 OVER INDIAN SUBCONTINENT

This paper explores the credibility and utility of AMSR-E soil moisture data (AE_Land 3 product) ... more This paper explores the credibility and utility of AMSR-E soil moisture data (AE_Land 3 product) to understand the soil moisture variation over Indian subcontinent in the year 2010. The data product was processed to generate monthly average soil moisture maps. The maps were analyzed to study the soil moisture pattern over the entire region qualitatively. The soil moisture values from the generated maps were compared with the rainfall data and it was found to be very well complementing the actual rainfall variation. The study shows that the soil moisture variation is in line with the seasonal change and the observed rainfall variation.

ANALYSIS OF MONTHLY SOIL MOISTURE VARIATIONS DERIVED FROM AMSR-E FOR THE YEAR 2010 OVER INDIAN SUBCONTINENT

by Gagandeep Singh and Dr. Hari Shanker Srivastava

This paper explores the credibility and utility of AMSR-E soil moisture data (AE_Land 3 product) ... more This paper explores the credibility and utility of AMSR-E soil moisture data (AE_Land 3 product) to understand the soil moisture variation over Indian subcontinent in the year 2010. The data product was processed to generate monthly average soil moisture maps. The maps were analyzed to study the soil moisture pattern over the entire region qualitatively. The soil moisture values from the generated maps were compared with the rainfall data and it was found to be very well complementing the actual rainfall variation. The study shows that the soil moisture variation is in line with the seasonal change and the observed rainfall variation.