Sushma Panigrahy

Bio: Sushma Panigrahy is an academic researcher from Indian Space Research Organisation. The author has contributed to research in topics: Cropping system & Normalized Difference Vegetation Index. The author has an hindex of 26, co-authored 97 publications receiving 1927 citations. Previous affiliations of Sushma Panigrahy include Indian Institute of Technology Guwahati.

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

Use of hyperspectral data to assess the effects of different nitrogen applications on a potato crop

Abstract: This study was conducted to explore whether hyperspectral data could be used to discriminate between the effects of different rates of nitrogen application to a potato crop. The field experiment was carried out in the Central Potato Research Station, Jalandhar, on seven plots with different nitrogen (N) treatments. Spectral reflectance was measured using a 512-channel spectroradiometer with a range of 395–1075 nm on two different dates during crop growth. An optimum number of bands were selected from this range based on band–band r 2, principal component analysis and discriminant analysis. The four bands that could discriminate between the rates of N applied were 560, 650, 730, and 760 nm. An ANOVA analysis of several narrow-band indices calculated from the reflectance values showed the indices that were able to differentiate best between the different rates of N application. These were reflectance ratio at the red edge (R740/720) and the structure insensitive pigment index (SIPI). To estimate leaf N, reflectance ratios were determined for each band combination and were evaluated for their correlation with the leaf N content. A regression model for N estimation was obtained using the reflectance ratio indices at 750 and 710 nm wavelengths (F-ratio = 32 and r 2 = 0.551, P < 0.000).

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...

Discrimination of rice crop grown under different cultural practices using temporal ERS-1 synthetic aperture radar data

Abstract: Radar remote sensing has a significant role to play in remote sensing based crop inventory programmes due to its independence from cloud cover. In this study, an attempt has been made to evaluate the utility of temporal ERS-1 SAR data to classify rice crop grown in different growing environments. The sites represent four major types of lowland cultivation practice prevailing in India. Results showed more than 90% classification accuracy for all types of wetland rice using three-date SAR data. Data acquired during the early vegetative stage were found essential for high accuracy. The accuracy was mainly affected by the presence of rivers/streams in the scene. High accuracy was obtained for lowland intermediate and irrigated rice areas. A significant effect of wind was observed on the radar backscatter from stagnant water bodies but not on the rice fields during early growth stages. The study indicates the feasibility of operational use of ERS SAR data for estimation of areas of rice crop grown under lowland cultural practice.

Wetlands of India: inventory and assessment at 1 : 50,000 scale using geospatial techniques

Abstract: Conservation and wise use of wetlands has been given priority world over. India harbours diverse types of wetlands. This study highlights the findings of the national-level inventory and assessment of wetlands carried out using RESOURCESAT-1 LISS-III data of 2006–07 at 1 : 50,000 scale. A hierarchical system comprising 19 classes based on Ramsar definition has been used to classify the wetlands of India. The extent of wetlands has been estimated to be 15.26 m ha. Inland wetlands account for 69.22% (10.564 m ha), whereas the coastal wetlands account for 27.13% (4.14 m ha). The high-altitude wetlands (situated > 3000 m asl) in the Himalayan states were also mapped, comprising 126,249 ha of areal extent. The status of wetlands in terms of water spread, turbidity of open water and aquatic vegetation has shown significant variation during preand post-monsoon seasons. This article highlights the detailed results at state level and the status of wetlands in terms of water spread, aquatic vegetation and turbidity of open water in the wetlands in the preand post-monsoon seasons.

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.

Multispectral and hyperspectral remote sensing for identification and mapping of wetland vegetation: a review

Abstract: Wetland vegetation plays a key role in the ecological functions of wetland environments. Remote sensing techniques offer timely, up-to-date, and relatively accurate information for sustainable and effective management of wetland vegetation. This article provides an overview on the status of remote sensing applications in discriminating and mapping wetland vegetation, and estimating some of the biochemical and biophysical parameters of wetland vegetation. Research needs for successful applications of remote sensing in wetland vegetation mapping and the major challenges are also discussed. The review focuses on providing fundamental information relating to the spectral characteristics of wetland vegetation, discriminating wetland vegetation using broad- and narrow-bands, as well as estimating water content, biomass, and leaf area index. It can be concluded that the remote sensing of wetland vegetation has some particular challenges that require careful consideration in order to obtain successful results. These include an in-depth understanding of the factors affecting the interaction between electromagnetic radiation and wetland vegetation in a particular environment, selecting appropriate spatial and spectral resolution as well as suitable processing techniques for extracting spectral information of wetland vegetation.