DSpace Collection:

ESTIMATION OF SOURCE PARAMETERS OF LOCAL .4 EARTHQUAKES IN THE ENVIRONS OF KOLDAM SITE

2026-05-05T12:30:41Z

Title: ESTIMATION OF SOURCE PARAMETERS OF LOCAL .4 EARTHQUAKES IN THE ENVIRONS OF KOLDAM SITE Authors: Kumar, Paidi Vinodh Abstract: The Koldain site falls in the 1-limachal Lesser Himalaya in the vicinity of the Main Boundary Thrust. The Main Central Thrust is located about 80 km northeast of the dam site. The region around Koldam site is marked by the occurrence of moderate to largesized earthquake activity. In this study hypocenter parameters and source parameters of 70 local events (l.3M3.7) have been interpreted from the local earthquake data collected from the region employing a 5-station temporary network. Source parameters of events have been estimated adopting Brune model and using digital data from single station recordings. The seismic moments (M0), source radii and Brune stress drops (z\) vary from 9.83x 1017 dyne-cm to 4.77x 1021 dyne-cm, 132 m to 633 in, and 0.08 bars to 30 bars respectively. Other estimated parameters of local events include: rms stress drops, apparent stress, and/, rms stress drops vary from more than one bar to about 40 bars and were not found to be correlated with Brune stress drops. For majority of events, apparent stress and Brune stress drops are found to be correlated and follow the relation: Ta (bars) = 4.47A °89 The maximum stress drop of 30 bars is observercl at a depth of about 15 km. Apparent stress and Brune stress drops have almost same distribution with focal depths. Maximum envelope encompassing Brune stress drops show an increasing trend with focal depths upto focal depths of 20 km and then shows a decreasing trend and seems to be related to the strength of the crust. The estimates of radiated seismic energy vary from l.lxlo'' to 2.2x 10' and following the relation E (crgs) = 2x10 17 M0(dyne_cm)15. The source radii increased with seismic moments The values of J - < vary from 4.7 Hz to 15.6 I-Iz respectively. The corner frequency, f, and .tax follow almost same trend and decrease with seismic moments. Based on the local earthquake data, two scaling relations: M0 (N-rn/see3) = lxlO15 ç33 (between M0 and corner frequency) and frnax (Hz) = 314.28M&°°79 (between fmax and M0) are proposed for the region studied. These relations can be adopted to constrain the strong ground motion.

Investigation the weaving craft of Kerala and exploring application in space-making

2026-04-27T06:19:37Z

Title: Investigation the weaving craft of Kerala and exploring application in space-making Authors: Dongre, Isha Pramod

UNDERSTANDING THE ROLE OF RITUALISTIC ART FORM IN PLACE MAKING: A STUDY OF THEYYAM

2026-04-27T06:19:19Z

Title: UNDERSTANDING THE ROLE OF RITUALISTIC ART FORM IN PLACE MAKING: A STUDY OF THEYYAM Authors: Viayan, Anusha

PREDICTING URBAN GROWTH OF KATHMANDU VALLEY USING ARTIFICIAL INTELLIGENCE

2026-02-24T10:33:07Z

Title: PREDICTING URBAN GROWTH OF KATHMANDU VALLEY USING ARTIFICIAL INTELLIGENCE Authors: Bharti, Puja Abstract: Globally, urban areas are growing at a tremendous speed. The goal of regulating urban growth has become one of the crucial challenges of the twenty-first century. The Kathmandu Valley illustrates the rising urbanisation trend that is conquering the Himalayan foothills. Kathmandu Valley landscapes have seen tremendous transformation in the last four decades, resulting in significant changes in land use and cover (LULC). My research first detected a pixel-based unsupervised classification technique to classify these images into Four LULC categories using four Landsat images from 1992, 2003, 2013, and 2021 through Remote sensing and GIS technique. LULC noticed the change and then was analysed in light of proximate causes and factors driving those changes. The built-up area was only 71.11 sq. km in 1992 and 80.53 sq. km in 2003. 143 sq. km in 2013 while 156.64 sq. km in 2021. This built-up expansion has occurred with the conversion of agricultural land. The majority of urban growth happened from 2003 to 2013 and still growing along the major roads in a concentric pattern altering the cityscape of the valley. The centrality feature of Kathmandu valley and the massive surge in rural-to-urban migration are the primary proximate causes of the fast expansion of built-up areas and rapid conversions of agricultural regions. Using the QGIS 2.8.3 version MOLUSCE plugin (MLP-ANN) model, this research intends to detect land-use changes in the Kathmandu Valley between 2013 and 2021 as forecast and establish potential land-use changes in the years 2031 and 2041 to create urban growth scenarios in Kathmandu Valley. The prediction model was able to forecast the 2031 and 2041 LULC maps with an overall accuracy of 93.82 percent. The valley has minimal land resources for new development because of its rugged mountainous terrain. Therefore it becomes necessary to comprehend the spatial process of urban growth and forecast future urban growth scenarios. This model optimises the spatial patterns of future urban growth allocation under three scenarios: Business as usual or baseline scenario, environment-friendly, and resource-efficient sustainable development Scenario. The expected spatial patterns reflect where and how the valley's urban growth is likely to go by 2041, and they provide important information on land availability for future land development projects. Compared to 2021, the forecast model shows a maximum rise of 8.32 per cent in the built-up area by 2041. As a result, the study's findings show that employing the LULC and CA-ANN models can assist in identifying future trends, which can help governments, planners, and stakeholders estimate and evaluate the likely repercussions of future policy options. Before making decisions, what-if scenarios for policy implementation are created, which aids in the valley's long-term growth.