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Kumar, Vinay

Water Quality Assessment of River Ganga and Chilika Lagoon using AVIRIS-NG Hyperspectral Data

Abstract Views :215 | PDF Views:86

Authors

S. Chander ¹, Ashwin Gujrati ¹, K. Abdul Hakeem ², Vaibhav Garg ³, Annie Maria Issac ², Pankaj R. Dhote ³, Vinay Kumar ³, Arvind Sahay ¹

Affiliations
1 Space Applications Centre, Indian Space Research Organisation (ISRO), Ahmedabad 380 015, IN
2 National Remote Sensing Centre, ISRO, Hyderabad 500 037, IN
3 Indian Institute of Remote Sensing, ISRO, Dehradun 248 001, IN

Source

Current Science, Vol 116, No 7 (2019), Pagination: 1172-1181

Abstract

Remote sensing is a vital tool to assess water quality parameters in water bodies like rivers, lakes, estuaries and lagoons. All these fall under the category of optically complex waters (case 2), where water-leaving radiance is affected by optically active water constituents and bottom substrate. The present study estimates water quality parameters, viz. turbidity, suspended sediment concentration and chlorophyll in River Ganga in Buxar (Bihar), and Howrah (West Bengal) and Chilika lagoon (Odisha) using hyperspectral reflectance data of AVIRIS-NG. Concurrent ground-truth data of water samples were collected and simultaneous spectro-radiometer measurements were made in synchronous with the AVIRIS-NG flight over the study area. Semi-analytical simulation modelling followed by inversion and contextual image analysis-based methods were used for estimating the water quality parameters. Water turbidity maps were generated for both the study sites. Over Ganga river, water was relatively clear in Buxar (6.87–20 NTU, TSS 42–154 mg/l), while it was extremely turbid in Howrah (50–175 NTU, TSS 75–450 mg/l). In Chilika lagoon, water was more turbid in the northern sector, which may be due to the river input and resuspension from shallow bathymetry. The results suggest that the small-scale changes in turbidity due to point sources like river tributaries or sewerage discharges can be identified using hyperspectral data. The imaging spectroscopy data over water are a key source to find out potential locations of water contamination.

Keywords

Hyperspectral Data, Remote Sensing Reflectance, Semi-Analytical Algorithms, Spectroradiometer.

Full Text

References

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Characterization and Retrieval of Snow and Urban Land Cover Parameters using Hyperspectral Imaging

Abstract Views :208 | PDF Views:91

Authors

S. K. Singh ¹, Gaurav Jain ¹, Asfa Siddiqui ², Smruti Naik ¹, B. P. Rathore ¹, Vaibhav Garg ², Snehmani ³, Vinay Kumar ², I. M. Bahuguna ¹, S. A. Sharma ¹, Chander Shekhar ³, Praveen K. Thakur ², Kavach Mishra ², Pramod Kumar ², T. H. Painter ⁴, J. Dozier ⁵

Affiliations
1 Space Applications Centre, Indian Space Research Organisation (ISRO), Ahmedabad 380 015, IN
2 Indian Institute of Remote Sensing, ISRO, Dehradun 248 001, IN
3 Snow and Avalanche Study Establishment, Chandigarh 160 036, IN
4 University of California, Los Angeles, CA, US
5 University of California, Santa Barbara, CA, US

Source

Current Science, Vol 116, No 7 (2019), Pagination: 1182-1195

Abstract

Snow and urban land cover are important due to their role in hydrological management and utility, climate response, social aspects and economic viability, along with influencing the Earth’s environment at local, regional and global scale. Hyperspectral data enable identification, characterization and retrieval of these land-cover features based on physical and chemical properties of compositional materials. AVIRISNG hyperspectral airborne data, with synchronous ground observations using field spectroradiometer and collateral instruments, were collected over two widely varied land-cover types, viz. a relatively homogenous area covered by snow in the extreme cold environment of the Himalaya (Bhaga sub-basin, Himachal Pradesh), and a completely heterogeneous urban area of a metropolitan city (Ahmedabad, Gujarat).

AVIRIS-NG airborne data were analysed to understand the effect of terrain parameters such as slope and aspect on snow reflectance. Snow grain index using visible and near-infrared (VNIR) bands and absorption peak in the near-infrared (NIR) were used to retrieve grain size in parts of the Himalayan region. A radiative transfer model was used to understand the grain size variability and its effect on absorption peak in NIR. Continuum removal was performed for snow spectral observations obtained from airborne, modelled and field platforms to estimate band depth at 1030 nm. Grain size was observed to vary with altitude from 100 to 500 μm using AVIRIS-NG image. In the urban area, the data also separated pervious and impervious surface cover using spectral unmixing technique, identified several urban features over multispectral data such as buildings with red tiled roofs, metallic surfaces and tarpaulin sheets using the material spectral profiles. Two single-frame superresolution methods namely sparse regression and natural prior (SRP), and gradient profile prior (GPP) were applied on AVIRIS-NG data for the mixed environment around Kankaria Lake in the city of Ahmedabad, which revealed that SRP method was better than GPP, and affirmed by eight indices. Preliminary analysis of AVIRIS-NG imaging over snow-covered areas and densely populated cities indicated utility of future spaceborne hyperspectral missions, particularly for hydrological and climatological applications in such diverse environments.

Keywords

AVIRIS-NG, Hyperspectral Imaging, Snow Reflectance, Super-Resolution Method, Terrain Parameters, Urban Land Cover.

Full Text

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Attempt to Unravel the ‘Tangled Bank’: A New-normal Global Meeting

Emerging and Re-emerging Biotic Stresses of Agricultural Crops in India and Novel Tools for their Better Management

Abstract Views :329 | PDF Views:79

Authors

J. Kumar ¹, R. K. Murali-Baskaran ¹, S. K. Jain ¹, P. N. Sivalingam ¹, J. Mallikarjuna ¹, Vinay Kumar ¹, K. C. Sharma ¹, J. Sridhar ¹, P. Mooventhan ¹, A. Dixit ¹, P. K. Ghosh ¹

Affiliations
1 ICAR-National Institute of Biotic Stress Management, Raipur 493 225, IN

Source

Current Science, Vol 121, No 1 (2021), Pagination: 26-36

Abstract

Food security of our country is at risk due to heavy yield losses of agricultural crops caused by pests and diseases known together as biotic stresses. Conventional management practices in vogue are not competent under the current situations obscured by the incitants of biotic stresses which have either enhanced their offensive capabilities due to adaptive mutations or regained their pathogenic/ herbivory potential owing to climate change. Numerous causal agents of biotic stresses are also introduced in the country or new regions of the country either through natural dispersal as invasive species, or on account of quarantine irregularities at national or international levels. Therefore, it is of utmost importance to appraise the impact of these new biotic stresses burgeoned in the recent past and to develop novel technologies for their management. To devise an effective preventive and eradicative strategy for containing these biotic stresses, new research innovations need to be practiced such as deciphering basic/molecular mechanism of host-pathogen/insect interactions; endophytic mechanisms of plant protection; nanotechnology in pest management; host resistance strengthening by gene cloning, recombinant DNA technologies, RNA biology, utilizing gene editing technologies such as CRISPR/Cas9, etc. This article presents a comprehensive account of new biotic stresses of agricultural crops built up in the country and also reviews the novel scientific inventions made worldwide which can be further employed to devise more efficient methods for alleviating impact of these biotic stresses of food crops in the country.

Keywords

Agriculture, Biotic Stress, Crops, Food Security, Management.

Full Text

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