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Effective management of water resources is crucial for sustainable development in any region. When considering computer-aided analysis for resource management, geospatial technology, i.e., the use of remote sensing (RS) combined with Geographic Information Systems (GIS) proves to be highly valuable. Geospatial technology is more cost-effective and requires less labor compared to ground-based surveys, making it highly suitable for a wide range of agricultural applications. Effectively utilizing the timely, accurate, and objective data provided by RS technologies presents a crucial challenge in the field of water resource management. Satellite-based RS measurements offer consistent information on agricultural and hydrological conditions across extensive land areas. In this study, we carried out a detailed analysis focused on addressing agricultural water management issues in India through the application of RS and GIS technologies. Adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines, we systematically reviewed published research articles, providing a comprehensive and detailed analysis. This study aims to explore the use of RS and GIS technologies in crucial agricultural water management practices with the goal of enhancing their effectiveness and efficiency. This study primarily examines the current use of geospatial technology in Indian agricultural water management and sustainability. We revealed that considerable research has primarily used multispectral Landsat series data. Cutting-edge technologies like Sentinel, Unmanned Aerial Vehicles (UAVs), and hyperspectral technology have not been fully investigated for the assessment and monitoring of water resources. Integrating RS and GIS allows for consistent agricultural monitoring, offering valuable recommendations for effective management. [ABSTRACT FROM AUTHOR]

This study was carried out to understand the pattern of surface energy fluxes over a periodical scale and energy balance closure using Large Aperture Scintillometer and Micrometeorological tower. The standalone technique as 'Scintillometry' which observes the structure parameter of refractive index based on Monin-Obukhov Similarity theory, has the potential to measure the sensible heat flux precisely. This paper discusses the surface energy balance components and energy balance closure over a period of August 2017 to June 2018. The maximum mean energy fluxes Rn, G, H and LE were observed in September (98.6 Wm-2), May (13.9 Wm-2), June (53.3 Wm-2) and August (82.1 Wm-2), respectively. The overall mean ET was observed at the rate of 1.36 mm day-1 during the study period. This scintillometry technique may further use in evapotranspiration modelling from polar orbiting satellite to geostationary satellite over a heterogeneous and undulated landscape. [ABSTRACT FROM AUTHOR]

Accurate and quantitative regional estimates of the carbon budget require an integration of eddy covariance (EC) flux-tower observations and remote sensing in ecosystem models. In this study, a simple remote sensing driven light use efficiency (LUE) model was used to estimate the primary productivity for major cropping systems using multi-temporal satellite data over the Saharanpur district in India. The model is based on radiation absorption and its conversion into biomass. The LUE model was implemented for major crop rotations derived from the time-series of Sentinel-2 and Landsat 8 with monthly satellite-based spatially explicit fields of photosynthetically active radiation (PAR), fraction of absorbed PAR (fAPAR) and down-regulated light use efficiency. Incident PAR and fAPAR were estimated on monthly basis from the ground-calibrated empirical equation using INSAT-3D insolation product and remote sensing–based vegetation indices, respectively. Spatial LUE maps created by down-regulating maximum LUE (EC tower-based) with water and temperature stressors derived from land surface water index (LSWI) and EC-based cardinal temperature, respectively. LUE-based modeled GPP over the sugarcane-wheat system was found higher than the rice-wheat system in Saharanpur district. This is because C4 crop (sugarcane) has very high photosynthetic efficiency compared to C3 crops (rice and wheat). Modeled GPP over the sugarcane-wheat system was found in good agreement with observed EC tower-based GPP (Index of Agreement = 0.93). Further regionally calibrated remote sensing–based LUE model well captures gross photosynthesis rates (GPP) over cropland ecosystem compared to globally modeled MODIS GPP product. [ABSTRACT FROM AUTHOR]

In India, agriculture serves as the backbone of the economy, and is a primary source of employment. Despite the setbacks caused by the COVID-19 pandemic, the agriculture and allied sectors in India exhibited resilience, registered a growth of 3.4% during 2020–2121, even as the overall economic growth declined by 7.2% during the same period. The improvement of the agriculture sector holds paramount importance in sustaining the increasing population and safeguarding food security. Consequently, researchers worldwide have been concentrating on digitally transforming agriculture by leveraging advanced technologies to establish smart, sustainable, and lucrative farming systems. The advancement in remote sensing (RS) and machine learning (ML) has proven beneficial for farmers and policymakers in minimizing crop losses and optimizing resource utilization through valuable crop insights. In this paper, we present a comprehensive review of studies dedicated to the application of RS and ML in addressing agriculture-related challenges in India. We conducted a systematic literature review following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines and evaluated research articles published from 2015 to 2022. The objective of this study is to shed light on the application of both RS and ML technique across key agricultural domains, encompassing "crop management", "soil management", and "water management, ultimately leading to their improvement. This study primarily focuses on assessing the current status of using intelligent geospatial data analytics in Indian agriculture. Majority of the studies were carried out in the crop management category, where the deployment of various RS sensors led yielded substantial improvements in agricultural monitoring. The integration of remote sensing technology and machine learning techniques can enable an intelligent approach to agricultural monitoring, thereby providing valuable recommendations and insights for effective agricultural management. [ABSTRACT FROM AUTHOR]

In this study, CO2 exchange over sugarcane and wheat growing season was quantified by continuous measurement of CO2 fluxes using eddy covariance (EC) system from January 2014 to June 2015. We also elaborated on the response of CO2 fluxes to environmental variables. The results show that the ecosystem has seasonal and diurnal dynamics of CO2 with a distinctive U-shaped curve in both growing seasons with maximal CO2 absorption reaching up to −8.94 g C m−2 day−1 and −6.08 g C m−2 day−1 over sugarcane and wheat crop, respectively. The ecosystem as a whole acted as a carbon sink during the active growing season while it exhibits a carbon source prior to sowing and post-harvesting of crops. The cumulative net ecosystem exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (Reco) were −923.04, 3316.65, and 2433.18 g C m−2 over the sugarcane growing season while the values were −192.30, 621.47, and 488.34 g C m−2 over the wheat growing season. The sesbania (green manure) appeared to be a carbon source once it is incorporated into soil. The response of day-time NEE to photosynthetically active radiation (PAR) under two vapor pressure deficit (VPD) sections (0–20 h Pa and 20–40 h Pa) seems more effective over sugarcane (R2 = 0.41–0.61) as compared to the wheat crop (R2 = 0.25–0.40). A decrease in net CO2 uptake was observed under higher VPD conditions. Similarly, night-time NEE was exponentially related to temperature at different soil moisture conditions and showed higher response to optimum soil moisture conditions for sugarcane (R2 = 0.87, 0.33 ≤ SWC < 0.42 m3 m−3) and wheat (R2 = 0.75, 0.31 ≤ SWC < 0.37 m3 m−3) crop seasons. The response of daily averaged NEE to environmental variables through path analysis indicates that PAR was the dominant predictor with the direct path coefficient of −0.65 and −0.74 over sugarcane and wheat growing season, respectively. Satellite-based GPP products from Moderate Resolution Imaging Spectroradiometer (GPPMOD) and Vegetation Photosynthetic model (GPPVPM) were also compared with the GPP obtained from EC (GPPEC) technique. The seasonal dynamics of GPPEC and GPPVPM agreed well with each other. This study covers the broad aspects ranging from micro-meteorology to remote sensing over C4-C3 cropping system [ABSTRACT FROM AUTHOR]

The current study was planned to identify the epidemiological factors associated with leptospirosis in South Gujarat region using neighborhood controls.~Background~Background~A total of 100 cases of leptospirosis occurred in South Gujarat region during the year 2012 were selected using simple random sampling. Three neighbors of the selected cases formed the controls (n = 300). A pretested structured questionnaire was used for data collection and data were analyzed using Epi Info 2007.~Methods~Methods~There was significant association of illiteracy (odds ratio [OR] =1.82, 95% confidence interval [CI] =1.14-2.89), working in waterlogged fields during the reference season (OR = 4.6, 95% CI = 1.6-17.9), swimming/bathing in canals, open air defecation practices, storage of cow dung in or surrounding house, residence in the house made up of cow dung walls, households with access of food to rodents, injuries over hands/foot during the endemic season (OR = 3, 95% CI = 1.8-4.8), and history of skin disease during the endemic season (OR = 4.2, 95% CI = 2-8.5), with leptospirosis. Only 10% of individuals had gumboots for protection. A total of 83 (83%) cases and 240 (80%) controls had taken oral doxycycline chemoprophylaxis (P > 0.05). Cases had taken chemoprophylaxis for a median 4 weeks (range: 1-8) while controls had taken the same for median 8 weeks (range = 1-8) (P < 0.002).~Results~Results~Although the commonly established factors appear to be associated with leptospirosis, the role of host factors seems to play a more important role in determining susceptibility to leptospirosis in exposed individuals.~Conclusions~Conclusions [ABSTRACT FROM AUTHOR]

Objective:This study aims to understand the demographics, mode of trauma, hospital stay, complications, neurological improvement, mortality and expenditure incurred by Indian patients with spinal trauma and ankylosing spondylitis (AS).Methods:Retrospective analysis of the patient data admitted to a tertiary referral hospital from 2008 to 2013 with the diagnosis of AS and spinal trauma was carried out. The variables studied were demographics, mode of trauma, neurological status, neurological improvement, involved vertebral level, duration of hospital stay, comorbid factors, expenditure and complications during the stay.Results:Forty-six patients with diagnosis of AS with spine trauma were admitted over the last 5 years with a total of 52 fractures. All were male patients; 58.6% had injury because of trivial trauma and 78.2% patients presented with neurological injury. C5 C6, C6 C7, C7 D1 and D12 were the most common injured level. Fractures through intervertebral disc were most common in cervical spine. Of the patients, 52.7% had shown neurological improvement of at least grade 1(AIS). Mean expenditure of patient admitted with spinal cord injury (SCI) with AS is 7957 USD (United States dollar), which is around five times the per capita income in India (as per year 2013).Conclusion:Males with AS are much more prone to spinal fractures than females and its incidence may be higher than previously reported. Domestic falls are the most common mechanism of spinal trauma in this population. High velocity injuries are associated with complete SCI. The study reinforces the need for development of subsidized spinal care services for SCI management. [ABSTRACT FROM AUTHOR]