Global warming is one of the primary causes contributing to melting glaciers and shrinking of glaciers moth. Because of the glacier retreat, more lakes increase the risk of flooding in people’s homes and lives. Several studies on the surging glaciers have been conducted by researchers using various techniques, as well as with the aid of multiple models like the Normalized Differential Water Index (NDWI). The Number of glacial lakes is increasing in the Himalayan region due to climate change (rise of the temperature). Some glacial lakes are potentially dangerous so monitoring is very necessary. It is necessary to evaluate such vulnerable lakes. Therefore, current work is carried out to identify such glacial lakes present in the Teesta River Basin (Eastern Himalaya). Spatiotemporal Landsat data for the last four decades at intervals of ten years from 1990 to 2020 has been considered which was cloud-free and spatial resolution of 30 meters. The dataset mentioned above was used for lake identification and delineation. The findings indicate the presence of lakes with respective areas of 275 (18.90 km2), 337 (24.92 km2), 295 (22.96 km2), and 419 (31.44 km2). It has also been observed that the growth rate is increasing with approximate water spread from 1990 to 2000 (+129%), 2000 to 2010 (+106%), and 2010 to 2020 (+136%). The present study aimed to identify such glacial lakes based on their water spreading area, which is an essential step followed in the study of GLOF (Glacial Lake Outburst Flood) as it will be helpful in the identification of hazardous lakes. In that study, we found that eleven glacial lakes are in the potentially dangerous category situated in the upper Teesta Basin due to the presence of glaciers, which gives a clear reason for the time-to-time assessment of such lakes. By the conducted study it has been observed that the number of glacial lakes has increased, due to which water spread has also increased in the area. It can also be demonstrated that GIS (Geographical Information System), along with remote sensing, is one of the best tools for assessing and monitoring such change detection and differentiation of hazardous glacial lakes in the cryosphere, along with the supporting data.

This study investigates the physical characteristics of red clay using the IDW approach and linear regression modeling in an area of 268.12 km2, focusing on Kirkuk, Bor, and Jambor structures. Through the analysis of 52 soil samples and the integration of laboratory data with IDW and regression results, several significant findings have emerged. The IDW method combined with linear regression proves to be a cost-effective and efficient approach for obtaining soil property data and generating accurate digital maps of red clay’s physical features. The Silt concentration exhibits a wide range, while the gravel content remains relatively low, indicating the predominance of silt in the soil composition. Analysis of Atterberg limits reveals the soil’s behavior and consistency in response to moisture, with the plasticity index generally falling within the low to medium range due to the considerable silt content in most soil samples. The linear regression model highlights positive correlations between the liquid limit, plastic limit, and plasticity index. Moderately positive relationships exist between the liquid limit and clay content, as well as a weak positive association between the liquid limit and specific gravity. Dry density, on the other hand, shows no significant correlation with other physical variables, suggesting its independence from the measured parameters. The plastic limit demonstrates a stronger relationship with the clay content compared to the liquid limit. Additionally, weak positive correlations are found between the liquid limit, plastic limit, and specific gravity and water content, indicating the influence of moisture on these parameters. Furthermore, gravel exhibits a moderate positive correlation with sand and silt concentrations, while a strong positive correlation is observed between sand and silt contents, underscoring their close association with the soil composition.

The study was carried out on the territory of the Kemerovo region-Kuzbass (Western Siberia, Russia). The purpose of the study was to obtain information on the species diversity and population of big-game animals. The monitoring was carried out on the forest territories of the region’s administrative districts. In the course of remote sensing using an unmanned aerial vehicle, the presence of all types of animals under consideration, except for the bear, was recorded. The deviation of the population number determined using the traditional method of digital technologies varied up to 50%. It was established that environmental measures organized and carried out by the regional administration and hunting farms improved the situation and stabilized the population of the main group of game animals. It was found that when using a sufficiently high sensitivity of the thermal imager (the used thermal imager had a very high sensitivity class ≤ 60 mK at 300 K), long-haired animals, which are characterized by a lower intensity of thermal radiation (for example, wolves) are identified and recognized in the images. The larger the animal and the worse the thermal insulation layer (wool or feathers), the easier it is to identify it in infrared images and the lower the sensitivity requirements of thermal imagers. The ability to recognize and record smaller animals and birds requires additional research on existing technologies. Our research has confirmed the validity of digital remote monitoring methods for managing the wildlife of hunting farms and nature conservation areas of the Siberian Taiga territories.

The study was carried out on the territory of the Kemerovo region-Kuzbass (Western Siberia, Russia). The purpose of the study was to obtain information on the species diversity and population of big-game animals. The monitoring was carried out on the forest territories of the region’s administrative districts. In the course of remote sensing using an unmanned aerial vehicle, the presence of all types of animals under consideration, except for the bear, was recorded. The deviation of the population number determined using the traditional method of digital technologies varied up to 50%. It was established that environmental measures organized and carried out by the regional administration and hunting farms improved the situation and stabilized the population of the main group of game animals. It was found that when using a sufficiently high sensitivity of the thermal imager (the used thermal imager had a very high sensitivity class ≤ 60 mK at 300 K), long-haired animals, which are characterized by a lower intensity of thermal radiation (for example, wolves) are identified and recognized in the images. The larger the animal and the worse the thermal insulation layer (wool or feathers), the easier it is to identify it in infrared images and the lower the sensitivity requirements of thermal imagers. The ability to recognize and record smaller animals and birds requires additional research on existing technologies. Our research has confirmed the validity of digital remote monitoring methods for managing the wildlife of hunting farms and nature conservation areas of the Siberian Taiga territories.