Current Science

Rajashree V. Bothale ¹, P. V. N. Rao ¹, C. B. S. Dutt ¹, V. K. Dadhwal ¹, Devesh Maurya ¹

Affiliations
1 National Remote Sensing Centre (ISRO), Hyderabad 500 037, IN

Abstract

In this article, spatio-temporal dynamics of snowmelt in Antarctica from 2001 to 2014 using OSCAT and QuikSCAT scatterometer data is presented. Melting over Antarctic ice sheet can influence shelf dynamics and stability. Here, we have utilized the sensitivity of scatterometer data to detect the presence of liquid water in the snow caused due to melt conditions. After analysing decadal data, a spatial and temporal variation in the average backscatter coefficient was observed over the shelf areas. An adaptive thresholdbased classification using austral winter mean and standard deviation of HH polarization is used which takes into account the spatial and temporal variability in backscatter from snow/ice. Significant spatiotemporal variability in melt area, duration and melt index was observed. Around 9.5% of the continent experienced melt over the study period. Larsen C and George VI shelves had maximum melt duration. The high correlation between melt duration obtained from satellite data and the positive degree day validates the efficacy of the melt algorithm used in the analysis and sensitivity of OSCAT data in detecting presence of water due to melt. There is seasonal and spatial variation in melt onset. Based on MI, 2004-05 was the warmest summer over the continent with 2011-12 being the coldest summer. Consistent and intensive melting was observed over Amery, Larsen C, George VI, Lazarev and Fimbul shelves. Melting of sporadic nature was observed over Ronne-Filchner, Ross and Riiser-Larsen shelves. The East Antarctic shelves experienced large melt during the study period. This article presents the suitability of OSCAT in melt identification and status of melt over the continent.

Keywords

Ice Shelves, Scatterometer Data, Spatiotemporal Dynamics, Snowmelt.

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M. K. Madhav Haridas ¹, P. V. N. Rao ¹, K. Sreenivas Rao ¹, Prijith Sudhakar ¹

Affiliations
1 National Remote Sensing Centre, Hyderabad 500 037, IN

Abstract

The northern Indian state of Uttarakhand had witnessed an episode of intense forest fire during April–May 2016. The present study analyses the changes in trace gas and other atmospheric constituents induced by the forest fire using satellite data. The study reveals elevated levels of CO, NO₂, ozone and aerosol optical depth (AOD) over the affected region. Higher levels of CO are observed at altitudes of 2–3 km. The column amount of CO has almost doubled from mean background values, whereas NO₂ has increased by almost three times to values normally seen over highly polluted cities. Increase in ozone is only moderate and AOD has risen towards the end of the main phase of the fire episode. Weather research and forecasting simulations of wind and planetary boundary layer height are also performed and the results discussed. The study shows the potential of Earth-Observation Satellites to track and monitor such environmental impacts effectively.

Keywords

Aerosol Optical Depth, Forest Fire, Trace Gas.

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Biswadip Gharai ¹, P. V. N. Rao ², C. B. S. Dutt ³

Affiliations
1 Atmospheric Chemistry and Processes Studies Division, Earth and Climate Science Area, Hyderabad 500 037, IN
2 Remote Sensing Area, National Remote Sensing Centre, Indian Space Research Organisation, Balanagar, Hyderabad 500 037, IN
3 Karnataka State Rural Development and Panchyat Raj University, Gadag 582 101, IN

Abstract

Mesoscale models, in general, are run using the US Geological Survey (USGS) 25-category land use/ land cover (LU/LC) data available at different spatial resolutions. The USGS data over the Indian region suffers from two types of errors, viz. misclassification of LU/LC data and non-availability of up-to-date satellite-based LU/LC data. To improve the accuracy and capture interannual changes better, the LU/LC data generated by the National Remote Sensing Centre (NRSC) using IRS-P6 AWiFS with 56 m basic resolution have been scaled to 5, 2 min and 30 sec resolution which is available at yearly intervals. In the next step, the Indian region of USGS data was replaced with IRS-P6 AWiFS-derived data and made compatible to MM5 and WRF mesoscale models. Thus the resultant product is a global USGS LU/LC data with the Indian region replaced by the information originally derived from AWiFS 56 m resolution imagery, for the years 2004–05 to 2012–13 (nine cycles). This communication describes the required LU/LC data format for MM5 and WRF models and the methodology adopted for compatible product generation. In addition, accuracy of AWiFS-derived LU/LC data converted to 30 sec resolution has also been determined. The present effort will provide the necessary reference for the atmospheric modelling community to address the Indian satellite based model compatible LU/LC data product. These data products are currently available on Bhuvan, the NRSC/ISRO geospatial portal.

Keywords

Land Use/land Cover Data, Land-surface Processes, Mesoscale Model, Spatial Resolution.

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Anurag Mishra ¹, K. Abdul Hakeem ¹, V. V. Rao ¹, P. V. N. Rao ¹, Santanu Chowdhury ¹

Affiliations
1 National Remote Sensing Centre, Indian Space Research Organisation, Hyderabad 500 037, IN

Abstract

This communication presents results of a preliminary study to understand and assess the colour changes in Lonar lake, Buldhana district, Maharashtra, India, using remote sensing data of recent years (2019 and 2020). In addition, the study has utilized IMD gridded weather data and spectral profiles of algal pigments from the published literature. In order to verify whether the colour change is a cyclic event, long-term satellite data of Landsat 8-OLI and Sentinel 2-MSI sensors from 2014 onwards were analysed using spectral response in red and green bands. It was observed that even though a cyclic pattern exists, the colour change events occurred only during the 2019 and 2020 periods. The present analysis showed a change in colour of the lake from green to brown twice during April–June 2019. However, in 2020, there was a change in colour of the lake from green to brown and eventually to pinkish-red, which was not observed earlier. Rainfall and temperature were used to identify possible causes of abiotic stress on algae population of the lake. The study observed light rainfall and reduction in temperature just prior to the colour change event during both the years. In the absence of field data, the published literature on absorption spectra of different algal pigments was reviewed to identify pigments causing brown- and red-coloured appearance of the lake. Though cause of stress on the algae population is not known and is to be precisely identified by field surveys, the change in colour of Lonar lake appears to be caused by pigment(s), like phycoerythrin and carotenoids. However, this needs to be verified in the ground through water quality analysis.

Keywords

Colour Changes, Lake Water, Pigments, Remote Sensing, Water Quality Analysis.

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K. Sreenivas ¹, G. Sujatha ¹, Tarik Mitran ¹, K. G. Janaki Rama Suresh ¹, T. Ravisankar ², P. V. N. Rao ³

Affiliations
1 Soil and Land Resources Assessment Division, National Remote Sensing Centre, ISRO, Balanagar, Hyderabad 500 037, IN
2 Land Resources Use Mapping and Monitoring Group, National Remote Sensing Centre, ISRO, Balanagar, Hyderabad 500 037, IN
3 Remote Sensing Applications Area, National Remote Sensing Centre, ISRO, Balanagar, Hyderabad 500 037, IN

Abstract

Robust data on the spatial distribution of land degradation is important for resource conservation planning. Spatial land degradation status of India was mapped using multi-temporal Linear Imaging Self Scanning Sensor (LISS-III) data acquired from Resourcesat-1/2 during 2005–2006 and 2015–2016 under the Natural Resources Census programme of the Indian Space Research Organisation. Heads-up on-screen visual interpretation of multi-season satellite data was carried out, supported by digital elevation model and other historical maps available. Visual interpretation cues were developed and employed across various partner institutions to achieve consistency in mapping. The outputs were subjected to two-stage quality check. Results indicate that the total land degradation of India was 91.2 M ha (27.77% of the geographical extent of the country) during 2015–2016 against 91.3 M ha during 2005–2006. During the ten-year period, there was an overall decrease of around 0.1 M ha in degraded land. However, noticeable intra- and inter-class changes were observed in land degradation during the ten-year period. Major reclamation was noticed in sand dunes which were converted into crop lands by levelling them. Substantial decrease in severity and extent of salt-affected soils was noticed in Uttar Pradesh.

Keywords

Change detection, land degradation, visual interpretation, sand dunes, soil erosion, spatial distribution.

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K. Sreenivas ¹, G. Sujatha ¹, Tarik Mitran ¹, K. G. Janaki Rama Suresh ¹, T. Ravisankar ², P. V. N. Rao ³

Affiliations
1 Soil and Land Resources Assessment Division, National Remote Sensing Centre, ISRO, Balanagar, Hyderabad 500 037, IN
2 Land Resources Use Mapping and Monitoring Group, National Remote Sensing Centre, ISRO, Balanagar, Hyderabad 500 037, IN
3 Remote Sensing Applications Area, National Remote Sensing Centre, ISRO, Balanagar, Hyderabad 500 037, IN

Abstract

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Keywords

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