Jai Singh Parihar

Bio: Jai Singh Parihar is an academic researcher from Indian Space Research Organisation. The author has contributed to research in topics: Normalized Difference Vegetation Index & Kharif crop. The author has an hindex of 22, co-authored 86 publications receiving 1426 citations. Previous affiliations of Jai Singh Parihar include Indian Institute of Remote Sensing.

Rice crop parameter retrieval using multi-temporal, multi-incidence angle Radarsat SAR data

Abstract: Temporal RADARSAT Standard beam SAR data of different incidence angle were analysed to study the temporal backscatter of rice crop for a predominant rice-growing region in West Bengal, India Correlation studies of backscatter with crop growth parameters were carried out Second order polynomial was the best fit obtained for crop age and crop height Shallow angle data (> 40°) was found better correlated to crop height than steep angle (23°) data Inversion algorithm was used to generate spatial maps of crop height and age The results validated over a village showed an over all 90% accuracy

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

Abstract: 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 den...

Remote sensing based crop inventory: A review of Indian experience

Abstract: This paper reviews the approach and techniques of Remote Sensing (RS) based crop discrimination and area estimation including single date approach based on maximum likelihood classification as well as hierarchical/ growth profile for crop classification. Uniqueness of both optical and microwave data for crop identification in operational scenario in Rabi and Kharif season is presented. In the past two decades, studies on RS based crop inventory of more than 20 crops at various spatial scales (village to national) have been conducted. In most of the studies a sampling-based approach using optimally acquired single date satellite data and a supervised classifier has been used. More recently, national scale inventory of wheat and rice using multidate WiFS and Radarsat, Synthetic Aperture Radar (SAR) data have been carried out. Studies on accuracies of area inventory led to understanding of effects of sensor characteristics such as spatial, spectral and radiometric resolution and scene characteristics such as field sizes, acquisition date etc. These experiences in Crop Area and Production Estimation (CAPE) project over past decade suggests that remote sensing inventory has matured in operational use. Future perspective such as utilization of multi-source data and merging techniques, fraction area estimation approaches, as well as integration of conventional field survey information with remote sensing data towards the FASAL concept is also presented.

Evaluation of RADARSAT Standard Beam data for identification of potato and rice crops in India

Abstract: The Canadian satellite RADARSAT launched in November 1995 acquires C-band HH polarisation Synthetic Aperture Radar (SAR) data in various incident angles and spatial resolutions. In this study, the Standard Beam S7 SAR data with 45°–49° incidence angle has been used to discriminate rice and potato crops grown in the Gangetic plains of West Bengal state. Four-date data acquired in the 24-day repeat cycle between January 2 and March 15, 1997 was used to study the temporal backscatter characteristics of these crops in relation to the growth stages. Two, three and four-date data were used to classify the crops. The results show that the backscatter was the lowest during puddling of rice fields and increased as the crop growth progressed. The backscatter during this period changed from −18 dB to −8 dB. This temporal behaviour was similar to that observed in case of ERS-SAR data. The classification accuracy of rice areas was 94% using four-date data. Two-date data, one corresponding to pre-field preparation and the other corresponding to transplantation stage, resulted in 92% accuracy. The last observation is of particular interest as one may estimate the crop area as early as within 20–30 days of transplantation. Such an early estimate is not feasible using optical remote sensing data or ERS-SAR data. The backscatter of potato crop varied from −9 dB to −6 dB during the growth phase and showed large variations during early vegetative stage. Two-date data, one acquired during 40–45 days of planting and another at maturing stage, resulted in 93% classification accuracy for potato. All other combinations of two-date data resulted in less than 90% classification accuracy for potato.

Drought-Induced Reduction in Global Terrestrial Net Primary Production from 2000 Through 2009

Abstract: Terrestrial net primary production (NPP) quantifies the amount of atmospheric carbon fixed by plants and accumulated as biomass. Previous studies have shown that climate constraints were relaxing with increasing temperature and solar radiation, allowing an upward trend in NPP from 1982 through 1999. The past decade (2000 to 2009) has been the warmest since instrumental measurements began, which could imply continued increases in NPP; however, our estimates suggest a reduction in the global NPP of 0.55 petagrams of carbon. Large-scale droughts have reduced regional NPP, and a drying trend in the Southern Hemisphere has decreased NPP in that area, counteracting the increased NPP over the Northern Hemisphere. A continued decline in NPP would not only weaken the terrestrial carbon sink, but it would also intensify future competition between food demand and proposed biofuel production.

Dominant control of the South Asian monsoon by orographic insulation versus plateau heating

Abstract: The Tibetan plateau, like any landmass, emits energy into the atmosphere in the form of dry heat and water vapour, but its mean surface elevation is more than 5 km above sea level. This elevation is widely held to cause the plateau to serve as a heat source that drives the South Asian summer monsoon, potentially coupling uplift of the plateau to climate changes on geologic timescales. Observations of the present climate, however, do not clearly establish the Tibetan plateau as the dominant thermal forcing in the region: peak upper-tropospheric temperatures during boreal summer are located over continental India, south of the plateau. Here we show that, although Tibetan plateau heating locally enhances rainfall along its southern edge in an atmospheric model, the large-scale South Asian summer monsoon circulation is otherwise unaffected by removal of the plateau, provided that the narrow orography of the Himalayas and adjacent mountain ranges is preserved. Additional observational and model results suggest that these mountains produce a strong monsoon by insulating warm, moist air over continental India from the cold and dry extratropics. These results call for both a reinterpretation of how South Asian climate may have responded to orographic uplift, and a re-evaluation of how this climate may respond to modified land surface and radiative forcings in coming decades.