Study of contaminated snow cover using remote sensing in the Eastern Himalayas of Arunachal Pradesh, India.

Snow is considered contaminated when any foreign materials are deposited/mixed with it, which can accelerate melting and significantly impact the snow cover's radiative balance. Such an enhanced melting rate results in a reduction in freshwater sources at the catchment level. In optical remote sensing, snow contamination is widely studied using a normalizing difference index called the snow contamination index.

Vegetation disturbance and regrowth dynamics in shifting cultivation landscapes.

Shifting cultivation, an age-old agricultural practice, is a major factor in forest cover change across Southeast Asia, where repeated cycles of vegetation disturbance and regrowth lead to far-reaching environmental and socio-economic impacts. The present study aims to assess the spatio-temporal patterns of vegetation disturbance and regrowth caused by shifting cultivation in Tripura state of India, over the past three decades, utilizing temporal segmentation of time-series Landsat data. The study analyzed vegetation disturbance and regrowth patterns in a shifting cultivation landscape from 1991 to 2020 using normalized burn ratio trends through LandTrendr, validated by the TimeSync tool.

Flood susceptibility mapping using Sentinel 1 and frequency ratio technique in Jinjiram River watershed, India.

Assam is one of the most flood-prone states in India, and the state frequently experiences catastrophic floods that cause significant damage in terms of loss of life and property. Flood susceptibility is considered the most essential and crucial input for managing floodplains and fostering local and regional development. This study focuses on the generation of flood susceptibility maps using the Frequency Ratio (FR) technique and microwave remote sensing inputs in the Jinjiram watershed which experienced disastrous flooding in 2020.

Optimal energy efficient path planning of UAV using hybrid MACO-MEA* algorithm: theoretical and experimental approach.

Autonomous mission capabilities with optimal path are stringent requirements for Unmanned Aerial Vehicle (UAV) navigation in diverse applications. The proposed research framework is to identify an energy-efficient optimal path to achieve the designated missions for the navigation of UAVs in various constrained and denser obstacle prone regions. Hence, the present work is aimed to develop an optimal energy-efficient path planning algorithm through combining well known modified ant colony optimization algorithm (MACO) and a variant of A*, namely the memory-efficient A* algorithm (MEA*) for avoiding the obstacles in three dimensional (3D) environment and arrive at an optimal path with minimal energy consumption.

Diagnosis of Indigenous Non-Malarial Vector-Borne Infections from Malaria Negative Samples from Community and Rural Hospital Surveillance in Dhalai District, Tripura, North-East India.

The aetiology of non-malaria vector-borne diseases in malaria-endemic, forested, rural, and tribal-dominated areas of Dhalai, Tripura, in north-east India, was studied for the first time in the samples collected from malaria Rapid Diagnostic Kit negative febrile patients by door-to-door visits in the villages and primary health centres. Two hundred and sixty serum samples were tested for the Dengue NS1 antigen and the IgM antibodies of Dengue, Chikungunya, Scrub Typhus (ST), and Japanese Encephalitis (JE) during April 2019-March 2020. Fifteen Dengue, six JE, twelve Chikungunya, nine ST and three Leptospirosis, and mixed infections of three JE + Chikungunya, four Dengue + Chikungunya, three Dengue + JE + Chikungunya, one Dengue + Chikungunya + ST, and one Dengue + ST were found positive by IgM ELISA tests, and four for the Dengue NS1 antigen, all without any travel history.

Validation of a Mobile Health Technology Platform (FeverTracker) for Malaria Surveillance in India: Development and Usability Study.

Background: A surveillance system is the foundation for disease prevention and control. Malaria surveillance is crucial for tracking regional and temporal patterns in disease incidence, assisting in recorded details, timely reporting, and frequency of analysis.

Objective: In this study, we aim to develop an integrated surveillance graphical app called FeverTracker, which has been designed to assist the community and health care workers in digital surveillance and thereby contribute toward malaria control and elimination.

Pattern of forest recovery and carbon stock following shifting cultivation in Manipur, North-East India.

Shifting cultivation has resulted in large-scale deforestation and forest degradation in the tropics; however the abandoned fallows are known to have high potential for carbon capture. The paper is an attempt to determine the forest recovery patterns following shifting cultivation by evaluating the tree species composition, diversity and abundance with respect to topographical factors in Manipur, India. We also used ordination analysis to understand the change in species composition with regard to environmental variables.

Flood inundation mapping and monitoring in Kaziranga National Park, Assam using Sentinel-1 SAR data.

Satellite-based flood assessment for extent and severity is very crucial input before, during, and after a flood event has occurred. Though optical remote sensing data has been widely used for flood hazard mapping, Synthetic Aperture Radar (SAR) data is preferred for detecting inundated areas and providing reliable information during a flood event due to its capability to operate in all weather and day/night time. Availability of cloud-free optical images during monsoon over north eastern India is a rarity.

Evaluation of ecological risk of metal contamination in river Gomti, India: a biomonitoring approach.

The aim of this study was to evaluate the extent of heavy metal pollution in river Gomti and associated ecological risk. River water, sediments and locally abundant mollusk (Viviparus (V.) bengalensis) were sampled from six different sites and analyzed for seven metals: Cadmium (Cd), Chromium (Cr), Copper (Cu), Manganese (Mn), Nickel (Ni), Lead (Pb) and Zinc (Zn).