Seasonal glacier surface velocity fluctuation and contribution of the Eastern and Western Tributary Glaciers in Amery Ice Shelf, East Antarctica

Glaciers play a crucial role in the study of the climate change pattern of the Earth. Remote sensing with access to large archives of data has the ability to monitor glaciers frequently throughout the year. Therefore, remote sensing is the most beneficial tool for the study of glacier dynamics. Fed by many tributaries from different sides, the Amery Ice Shelf (AIS) is one of the largest ice shelves that drains ice from the Antarctic ice sheet into the Southern Ocean. This study focuses on the eastern and the western tributaries of the AIS. The primary objective of the study was to derive the velocity of the tributary glaciers and the secondary objective was to compare variations in their velocities between the summer and winter season. This study was carried on using the European Space Agency’s (ESA) Sentinel-1 satellite’s Synthetic Aperture Radar (SAR) data acquired from the Sentinel data portal. Offset tracking method was applied to the Ground Range Detected (GRD) product of the Sentinel-1 interferometric wide (IW) swath acquisition mode. The maximum velocity in summer was observed to be around 610 m/yr in the eastern tributary glacier meeting the ice shelf near the Pickering Nunatak, and around 345 m/yr in the Charybdis Glacier Basin from the western side. The maximum velocity in the winter was observed to be 553 m/yr in the eastern side near the Pickering Nunatak whereas 323 m/yr from the western side in the Charybdis Glacier Basin. The accuracy of the derived glacier velocities was computed using bias and root mean square (RMS) error. For the analysis, the publicly available velocity datasets were used. The accuracy based on RMS error was observed to be 85-90% for both seasons with bias values up to 25 m/yr and root mean square error values up to 30 m/yr

Implementing an object-based multi-index protocol for mapping surface glacier facies from Chandra-Bhaga basin, Himalaya

Surface glacier facies are superficial expressions of a glacier that are distinguishable based on differing spectral and structural characteristics according to their age and inter-mixed impurities. Increasing bodies of literature suggest that the varying properties of surface glacier facies differentially influence the melt of the glacier, thus affecting the mass balance. Incorporating these variations into distributed mass balance modelling can improve the perceived accuracy of these models. However, detecting and subsequently mapping these facies with a high degree of accuracy is a necessary precursor to such complex modelling. The variations in the reflectance spectra of various glacier facies permit multiband imagery to exploit band ratios for their effective extraction. However, coarse and medium spatial resolution multispectral imagery can delimit the efficacy of band ratioing by muddling the minor spatial and spectral variations of a glacier. Very high-resolution imagery, on the other hand, creates distortions in the conventionally obtained information extracted through pixel-based classification. Therefore, robust and adaptable methods coupled with higher resolution data products are necessary to effectively map glacier facies. This study endeavours to identify and isolate glacier facies on two unnamed glaciers in the Chandra-Bhaga basin, Himalayas, using an established object-based multi-index protocol. Exploiting the very high resolution offered by WorldView-2 and its eight spectral bands, this study implements customized spectral index ratios via an object-based environment. Pixel-based supervised classification is also performed using three popular classifiers to comparatively gauge the classification accuracies. The object-based multi-index protocol delivered the highest overall accuracy of 86.67%. The Minimum Distance classifier yielded the lowest overall accuracy of 62.50%, whereas, the Mahalanobis Distance and Maximum Likelihood classifiers yielded overall accuracies of 77.50% and 70.84% respectively. The results outline the superiority of the object-based method for extraction of glacier facies. Forthcoming studies must refine the indices and test their applicability in wide ranging scenarios

Metabolic Syndrome in psoriasis: a hospital based cross-sectional study in Central India

Background: Psoriasis is a chronic immune-mediated inflammatory disorder, reported to be associated with obesity, dyslipidaemia and diabetes via common immunological mechanisms. All of these components ultimately increase the risk of metabolic syndrome and cardiovascular morbidities. Aims and Objectives: To assess the association of Metabolic Syndrome (MS) and its components in patients suffering from psoriasis. To study the relationship between the duration and severity of psoriasis and MS. Materials and Methods: A hospital based cross-sectional study was conducted involving 100 adult patients with psoriasis and 100 controls. All participants were evaluated forpsoriasis and the components of MS. Psoriasis was categorized as mild, moderate and severe based on Psoriasis Area and Severity Index (PASI) (<7, 8–12 and >12, respectively). In all patients and controls, body mass index was calculated, blood pressure and waist circumference were measured and fasting blood sugar and lipid profile were estimated. Results: In the present study, a higher prevalence of MS in Psoriasis patients than in controls (38% v/s 23%) was observed. Psoriatic patients had higher prevalence of hypertension (36% v/s 14%). It can be concluded that association of MS and psoriasis is independent of the type, duration and severity of psoriasis. Conclusion: The present study suggests that subjects with psoriasis present a greater risk of MS and should trigger a higher clinical suspicion for their co-existence. Psoriasis is a systemic disease with significant morbidity and mortality. This study emphasizes the critical need for providers to screen psoriasis patients for early diagnosis and treatment of associated MS. However, more number of large population based cohort studies are required to establish stronger association between psoriasis and MS