Meteorological studies have indicated that high alpine environments are strongly affected by climate warming, and periglacial debris flows are frequent in deglaciated regions. The combination of rainfall and air temperature controls the initiation of periglacial debris flows, and the addition of meltwater due to higher air temperatures enhances the complexity of the triggering mechanism compared to that of storm-induced debris flows.

Coastal zones are dynamic interfaces of land and water of high ecological diversity and critical economic importance. The boundaries, shape and size of this coast change constantly under the influence of both natural and anthropogenic factors. The study area, Tupilipalem is one of the proposal sites for constructing a major port, to be named Dugarajapatnam Port, along the east coast of Andhra Pradesh, India.

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The objectives of the Winter Fog Experiment (WIFEX) over the Indo-Gangetic Plains of India are to develop better now-casting and forecasting of winter fog on various time- and spatial scales. Maximum fog occurrence over northwest India is about 48 days (visibility <1000 m) per year, and it occurs mostly during the December–February time-period. The physical and chemical characteristics of fog, meteorological factors responsible for its genesis, sustenance, intensity and dissipation are poorly understood.

Flood hazard causes great loss to lives and properties leading to disturbance in human society. Flood is the single most hydrometeorological hazard causing substantial losses. To gain better understanding of the flood phenomena especially for planning and mitigation purposes, flood risk analysis is often required. For the present study, the middle part of Panchganga river of Kolhapur district, Maharashtra was selected.

Prediction of earthquake in advance is really a challenging task for the scientific community till now. But research results from various scientists regarding lineament extraction using satellite imageries help us to way forward for earthquake monitoring study. For the present study, Landsat 8 OLI Time series data analyzed by integrating four different remote sensing and GIS software’s for automatic lineament extraction, its change, including lineament lengths and directions study by creating rose diagrams and finally vertical surface transect profile curve drawing.

This study focuses on the local and regional impact of large-scale gold mining in Africa in the context of a mineral boom in the region since 2000. It contributes to filling a gap in the literature on the welfare effects of mineral resources, which, until now, has concentrated more on the national or macroeconomic impacts.

A thorough understanding of movement patterns of a species is critical for designing effective conservation and management initiatives. However, generating such information for large marine vertebrates is challenging, as they typically move over long distances, live in concealing environments, are logistically difficult to capture and, as upper-trophic predators, are naturally low in abundance. Large-bodied, broadly distributed tropical shark typically restricted to coastal and shelf habitats, the great hammerhead shark Sphyrna mokarran epitomizes such challenges.

Order of the Supreme Court of India in the matter of M. K. Balakrishnan & Others Vs Union of India & Others dated 08/02/2017 regarding wetland conservation in India. Supreme Court orders that the Wetlands (Conservation and Management) Rules, 2016 should be notified on or before 30th June, 2017.

In this article, we describe an unmanned aerial system equipped with a thermal-infrared camera and software pipeline that we have developed to monitor animal populations for conservation purposes. Taking a multi-disciplinary approach to tackle this problem, we use freely available astronomical source detection software and the associated expertise of astronomers, to efficiently and reliably detect humans and animals in aerial thermal-infrared footage.

This study was carried out to simulate the forest cover changes in India using Land Change Modeler. Classified multi-temporal long-term forest cover data was used to generate the forest covers of 1880 and 2025. The spatial data were overlaid with variables such as the proximity to roads, settlements, water bodies, elevation and slope to determine the relationship between forest cover change and explanatory variables. The predicted forest cover in 1880 indicates an area of 10,42,008 km², which represents 31.7% of the geographical area of India.

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