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A deep analytics for prediction and forecasting of air quality in Chennai
33-53Views:43Air pollution is a global crisis with profound implications for public health and environmental sustainability. In addressing this issue in Chennai, Tamil Nadu, a novel Hadoop-based real-time air pollution prediction system is proposed. This research offers accurate air quality information for specific Chennai regions, aiding decisions and mitigating pollution risks through big data analytics and deep learning for air quality prediction. To expedite air quality prediction, a vast air pollution dataset is rigorously analyzed using a Hadoop-based analytics model. Specific locations in Chennai, including Perungudi, Royapuram, Manali, Alandur, Arumbakkam, Kodungaiyur, and Velachery, are assessed for upto- date air quality evaluations. The core of the research revolves around implementing deep learning models—Long Short-Term Memory, Convolutional Neural Network, and a hybrid Long Short-Term Memory-Convolutional Neural Network model. These models are trained to forecast AQI for selected areas over the next five years, with the hybrid model emerging as the standout performer, achieving 99% of accuracy rate and mean absolute error, mean square error, root mean square error rates of 7.95, 101.71, 9.65. This high accuracy and low error rates empowers policymakers and environmental agencies to make informed decisions, fostering healthier living conditions in Chennai. The integration of big data analytics and deep learning, promises improved air quality management in urban areas globally, addressing similar environmental challenges and enhancing overall quality of life.
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In-flight icing characteristics of unmanned aerial vechicles during special atmospheric condition over the Carpathian-basin
74-80Views:127The in-flight aerial icing phenomena is very important for the Unmanned Aerial Vehicles (UAV) because it causes some serious problems such as reduced lift and increased drag forces, significantly decreased angle of attack, increased weight, structural imbalances and improper radio communications. In order to increase flight safety of UAV’s we develop an integrated meteorological support system for the UAV pilots, mission controllers and decision makers, too. In our paper we show the in-flight structural icing estimation method as a part of this support system based on a simple 2D ice accretion model predictions. We point out the role of the ambient air temperature, cloud liquid water content, airfoil geometry and mainly the true airspeed in the icing process on the wings of UAVs. With the help of our model we made an estimation of geometry and amount of ice accretion on the wing of a short-range and a high-altitude and long-endurance UAVs during a hypothetical flight under a typical icy weather situation with St clouds over the Carpathian-basin (a cold-pool situation case study). Finally we point out that our icing estimation system can easily be adapted for supporting the missions of UAVs.
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Environment protection and its reflection in the environmental consciousness of the inhabitants in a middle-sized town (Vác, Hungary)
83-94Views:137Abstract The paper presents the role of urban environmental protection in sustainable development while analysing the factors influencing the environmental consciousness of the inhabitants of a middle-sized town based on a general model, together with the role of environmental consciousness in solving environmental protection problems at settlement level. My particular research focused on characterising the environmental state of Vác, with a population of 35000 people, and on the knowledge and environmental consciousness of the inhabitants. In the course of the representative questionnaire survey, 439 people gave assessable answers. Questions were related to the most significant environmental problems (air pollution, water contamination, sewage treatment, waste management). Answers were compared to the real situation based on measurements. Results revealed that the knowledge of the inhabitants on local environmental problems is better than the national average. In certain relations (water contamination, sewage treatment), however, it is deficient, thus information transfer was studied separately as well. It can be stated that local governments should make greater efforts in order to inform inhabitants. Environmental attitude of the inhabitants can be regarded as good. Based on the general model, I analysed the tasks of the settlement to improve environmental consciousness in order to increase efficiency of urban environmental protection.
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Prioritizing Watersheds for Flood Risk Assessment in Uttarakhand Himalayas using Geospatial Techniques and TOPSIS Method
54-71Views:28Uttarakhand has a highly diverse topography, with snow-covered peaks, deep canyons, roaring streams, and dusty plains, all drained by various rivers of the Ganges system, India. The present study prioritizes watersheds in the Uttarakhand Himalayas for flood susceptibility using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, supported by GIS and remote sensing data. ALOS PALSAR Digital Elevation Model (DEM) with 12.5-meter resolution was utilized to map topographic features and to analyze 18 morphometric parameters of 28 watersheds. The TOPSIS method prioritized sub-watersheds using AHP criteria weights, which are classified into five priority levels ranging from very low to very high. The Sarju, Ram Ganga, and Song watersheds were identified as having the highest flood risk, placing them in the “Very High” priority class. These watersheds exhibited high drainage density (Dd), stream frequency (Fs), and bifurcation ratio (Rb), indicating a dense and complex drainage network prone to rapid runoff and increased flood potential. The watersheds such as Bandagarh, Parry, and Chandra Bhaga were placed in the “Very Low” priority class due to lower closeness coefficient (Cci) values, suggesting simpler drainage systems and reduced flood risk. The AUC (Area Under Curve) value of 0.789, indicates a good predictive accuracy for the TOPSIS model. The classification helps in pinpointing high-risk areas that require urgent flood management interventions.
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Spatial pattern of soil erosion using RUSLE model and GIS software at the Saf Saf watershed, Algeria
31-47Views:314Soil erosion is one of the problems threatening the Algerian environment. In agriculture, soil erosion leads to the thinning of the topsoil under the effect of the natural erosive forces of water, or under the effect of agricultural activities. The present study aims to estimate average soil loss rate and to identify vulnerable zones. Through the integration of RUSLE model at the Saf Saf watershed, various parameters are utilized such as the rainfall erosivity factor (R), soil erodibility factor (K), slope length - slope factor (LS), crop management factor (C) and practice management factor (P). All these parameters are prepared and processed through a geographic information system (GIS) and remote sensing using various database sources. The results reveal that the river basin has an average annual soil loss of 3.9 t ha−1 yr−1, and annual soil loss of 4.53 million tonnes for the period 1975-2017. Meanwhile, eighty five percent of the study area is experiencing acceptable rate of soil erosion loss, which is ranging between 0 to 5 t ha−1 yr−1. The present study of risk assessment can contribute to understand the spatial pattern of soil erosion in order to use appropriate conservation practices for sustainable soil management.
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GIS-integrated multi-criteria suitability analysis for healthcare facilities site selection in Rajouri district, Jammu and Kashmir, India
12-29Views:356The study aims to develop a Decision Support model for the selection of a suitable site to establish a new healthcare center with adequate facilities based on the analytical hierarchy process (AHP) in the Rajouri district of Jammu and Kashmir. This study utilized AHP and GIS to identify an appropriate location for a new healthcare center. The study employed eight criteria to evaluate potential locations and utilized pairwise comparison to assign weights to each criterion. GIS-based spatial analysis was used to create factor and suitability maps for each criterion. Suitability was evaluated on a scale of 0 to 10 and each factor map was combined using the ArcGIS weighted overlay selection tool. The final map of the study represents the suitable site for a healthcare center in the Rajouri district and it shows the sites from the highly suitable to the least suitable area. In Rajouri district, mostly the central part can be considered very suitable as the population density of this area is higher compared to other areas of the district. The southwestern parts of the district are moderately suitable or least suitable sites for a new healthcare center. The study displays the pattern of the existing location of healthcare centers, mostly, the existing locations are not proper and suitable. Therefore, in the future, the allocation of healthcare centers must be in more adequate areas. Policymakers and healthcare professionals can be benefitted from this study in selecting suitable locations for future hospitals, which could ultimately improve access to healthcare services in the region. Additionally, the study can be contemplated in developing new policies for better transportation system in the study area.