ALBERT

Beschreibung: 〈div〉〈p〉〈em〉A Geographic Information System (GIS) includes of a hardware and software which are used for purposes such as to capture, store, evaluate, administer and distribute spatial data. GIS has a vast array of spatial analysis tools such as GIS viewer, Geodatabase, mapping tools, modelling tools etc. At present GIS is broadly used in conjunction with multi criteria decision analysis method to perform infrastructure studies and transportation studies such as road and rail. Multi criteria decision analysis can be applied in vehicle routing, site selection, scenario evaluation, land suitability, impact assessment, and location allocation for different sectors. According to majority of the literature, main factors considered in designing railway with GIS are land use, slope, drainage and soil. When multi criteria decision analysis is combined with GIS, it considers different geographical data models, spatial dimension of the evaluating criteria and decision alternatives in those criteria. The best route out of various alternate alignments has been designed using GIS thematic maps and network analysis in ArcGIS as a base. As a conclusion, this review study proves that multi criteria decision analysis combined with GIS plays a major role in modern railroad construction. 〈strong〉 〈/strong〉〈/em〉〈/p〉〈/div〉

Beschreibung: 〈p〉〈em〉Air pollution is mainly due to the release of pollutants into the atmosphere which are detrimental to the planet and human health in particular〈/em〉〈em〉.〈/em〉〈em〉 Monitoring for the air quality parameters is important because it may lead to the adverse effects on the environment. The quantitative analysis of the air pollution spreads over the Bangalore city is carried out using two different data sources, one from ground monitoring stations and the other from the satellite derived data. Ambient Air Quality data for Bangalore region recorded by Karnataka State Pollution Control Board (KSPCB) for 2018–2020 were analysed in the open source GIS platform. Air quality parameters like aerosol optical depth (AOD), Nitrogen di-oxide (NO〈sub〉2〈/sub〉) etc. were collected from Moderate Resolution Imaging Spectro-radiometer (MODIS) and Ozone monitoring instruments for spatial analysis. Data were analysed and compared and found that satellite based data of NO〈sub〉2〈/sub〉 from the sensors provide a reliable values in ground-level exposure for a larger urban region.〈/em〉〈/p〉

Beschreibung: 〈p〉〈em〉〈span〉The focus of this research is to distinguish between shifting land-use patterns and their geo-environmental implications in Simhadripuram Mandal, YSR Kadapa district, Andhra Pradesh, India. While the terms Landuse and Landcover (LULC) are sometimes used interchangeably, they have distinct natural meanings. Landuse refers to the function of a piece of land, such as mining, agriculture, or habitation. Landcover refers to the ground's surface cover, which might include vegetation, water, barren soil, and so on. Landuse is a notion that has a lot of qualities. It refers to people's actions on land that are directly related to the land. Landcover, on the other hand, refers to the vegetation that covers the surface of the land. The changes in LULC in Simhadripuram Mandal during the last ten years were studied using satellite imageries. LULC changes have been mapped using remote sensing and GIS modeling. The study is characterized in to five classifications, they are vegetation, fallow land, barren land, waterbodies, and built-up-land. The results reveal from 2009–10 to 2019–20, waterbodies are slightly increased from 2010 to 2020, is 9.29 km〈sup〉2〈/sup〉. Vegetation is increased positively for the past decade to 25.16 Km〈sup〉2〈/sup〉. The unirrigated land has been decreased to 27.1 km〈sup〉2〈/sup〉. Built-up-land is increased from the last decade; it is noted as 22.77 km〈sup〉2〈/sup〉. Fallow land has been decreased to 30.12 km〈sup〉2〈/sup〉.〈/span〉〈/em〉〈/p〉

Beschreibung: 〈p〉〈em〉B〈/em〉〈em〉iodiversity, or the vast diversity of life on Earth, is rapidly vanishing. In the last few decades, there has been a massive loss. Several animal and plant species have declined in recent decades. At an alarming rate, hundreds of thousands of acres of forests have been devastated. Several blue whales, polar bears, pandas, and other well-known animals starved to death. Many yet-to-be-discovered species are also in jeopardy. In recent years, there has been a significant decrease in the number of forests. Surviving species on the planet have a wide range of options for living in diverse settings, each with its own set of behaviors. So, biodiversity is crucial for us. We must preserve it. Humans should find ways to restore balance to our environment. We've identified several contributing factors to the decline in biodiversity, which we can divide into five categories: - land and sea use, pollution, overexploitation of species, changes in the climate, and diseases caused by invasive species. Conservation of diversity is a method for preserving species richness, species diversity, habitat diversity, ecological diversity, and genetic diversity. It maintains our health, prosperity, food, fuel, and services. It shows its vitality in supporting many aspects of development. Here are some innovative and creative ways to aid in the fight against biodiversity loss.〈/em〉〈/p〉

Beschreibung: 〈p〉〈em〉The present study was carried out to identify of the groundwater potential zones (GWPZ) in the Mahanadi River delta of Odisha, India using Remote Sensing (RS), Geographical information system (GIS) and Analytical Hierarchy Process (AHP) approaches. In this study, various thematic maps categorized viz. geology, geomorphology (GM), lineament density (LD), slope, landuse/landcover (LULC), and soils for assessment of GWPZs, which is generated using RS and GIS approach. Further, the relative weights were allocated to various thematic maps using the AHP matrix method and the relative rank 〈/em〉〈em〉assigned to each sub-criterion based on expert advice. Finally, the GWPZ map was prepared by integrating into all these parameters and their respective weights in the GIS software and the study〈/em〉〈em〉 area were categorized into four GWPZs types, i.e. poor, moderate, good, and very good. 〈/em〉〈em〉About 7.12% of area is categorised in the class ‘poor’, 75.66% in ‘moderate’, 9.03% in ‘good’ and 8.19% in ‘very good’ category. The acquired outcomes were validated with the area under well data. The results show that there is a strong positive correlation between the GWPZs with 82% validation high performance and decreases to the low yield potential with poor areas. This study concludes that the AHP model will be a more reliable for the assessment of the GWP. 〈/em〉〈em〉Any groundwater management project carried out in these favourable regions would benefit the stack holders. 〈/em〉〈/p〉

Beschreibung: 〈p〉〈em〉Drainage basin characteristics depends on various factors like geology of the area, soil type, hydrological setting of the area etc. Study of morphometric characters is helpful to know more about lithological structures, geomorphological features and conditions, lineaments and hydrological characteristics of the area which in turn throws light on ground water conditions and movement of the area. Study area is Pattankodoli Nala Basin, 〈/em〉〈em〉bounded by latitude 16°36'31'' N to 16°40'44'' N and longitude 74°18'37'' E to 74°22'39'' E in Survey of India (SIO) Toposheet numbers 47L/6 on the scale 1:50000. Morphometric analysis has been carried out and various morphometric aspects have been studied. On the basis of quantitative analysis of morphometric parameters, it found that the Pattankadoli Nala is 4〈sup〉th〈/sup〉 ordered and the whole river contains 50 streams. The low drainage density and low stream frequency indicates that the drainage nala has less runoff in the channel. The basin is having elongated shape and gentle slope. Both relief and drainage density are low to moderate. It is found that 〈/em〉〈em〉the South Western part of the basin has moderate to good ground water potential and is favorable for artificial recharge site construction.〈/em〉〈/p〉

Beschreibung: 〈p〉〈em〉The applications of Hyper spectral images (HSI) are many, which include agriculture, food quality, remote sensing, medical diagnostics and safety assessment. Hyper spectral image analysis has been used for detecting contaminants and identifying defects in food. It also utilizes advanced software and hardware tools hence allowing users to diagnose and detect pathologies. In this paper an avant-garde investigation about hyper spectral image compression and classification techniques which can be used in various applications like broadcasting of television, remote sensing via satellite, storage and classification of medical images, pictures and documents has been made. Significant increase in multimedia products has created a need to enhance, extract, store and interpret the information received in the most effective manner. The size of a hyper spectral image comprises approximately 138.81 megabytes and hence requires large space for storage. Hence, hyper spectral image compression is of great importance as it reduces the data redundancy and also the hardware space required for storage. Hyper spectral image classification has gained great research attention due to the increasing demand of feature information extraction. This survey focuses on describing the recent advances in spectral–spatial classification of hyperspectral images and various recent advancements in compression techniques for input HSIs.  〈/em〉〈/p〉 〈p〉〈em〉 〈/em〉〈/p〉

Beschreibung: 〈p〉〈em〉Land use and landcover (LULC) change has become a critical component of current methods for not just urban planning but also managing a region's natural resources. The focus of this research is to evaluate the LULC scenario that occurred in Yellanuru Mandal of Anantapur district, AP, India between 2010 and 2020 using Remote Sensing (RS) and Geographical Information Systems (GIS). This study was conducted by gathering Landsat data over a decade, from 2010 to 2020, using ERDAS Imagine 2014 and Arc GIS software, and generating a LULC map using a supervised classification approach. The research region's LULC is divided into five types: vegetation, fallow land, agricultural land, developed land, and water bodies/river. Our findings suggest that satellite data are well adapted to classifying land use/land cover at the subpixel level, where land use categories are linked with homogenous land cover.〈/em〉〈/p〉

Beschreibung: 〈p〉〈em〉Geo-Cells are three dimensional Structures Orthogonally Designed. These are made using Polymers, we have Experimented and Designed Geo-Cells using Recycled High Density Polypropylene (HDPE), to get a Cost Effective Result. These Geo-Cells are then installed under Weak and Soft Soil to create a Low Density Unpaved Road. These Roads help us continue the work of shifting the Blocks from the Manufacturing Site to the Storage Place with Minimum Losses. This Internal Shifting is carried out inside the Casting Yard, where the Soil becomes Quite Soft and Marshy due to Water Absorption. The test conducted for physical properties are grain size distribution and for Engineering properties modified proctor test, atterberg’s limit, CBR test are done for Red Soil. Then the result are tabulated. During the Monsoon Season with the Installation of Recycled HDPE Geo-Cell. We were successfully able to reduce the Cost of the Project and also Increase the Time Efficiency of this Project.〈/em〉〈/p〉

Beschreibung: 〈p〉〈em〉Disasters caused by climate change have wreaked havoc on the environment around the world in recent decades, to the point that even deserts have been flooded. Considering floods as a major disaster across various countries, this research has accumulated different methodologies and techniques to analyze flood mapping according to geography of many regions across the world. This paper discusses about flood plain mapping and analysis of the past two decades. Recently with the help of satellite images and the application of remote sensing and GIS this concept is widely used by various researchers. To simulate these flood plain areas, software such as HEC-HMS, HEC-RAS and ArcGIS are quite popular and widely used. The purpose of this review article is to divide the research into four primary sections: floodplain mapping, analytic method, digital elevation model, and software used.. It was observed that globally according to site and climate conditions the effect of floods changes geographically and as a result, the approaches and techniques employed by various researchers differ from one location to the next and according to their research goals. As a consequence, gaps have been identified, and the authors have applied strategies to tackle their problem. This document serves as an overview of the research's important literature review〈/em〉〈/p〉

Beschreibung: 〈p〉〈em〉Adi is a rural region in India's Karnataka state's Belgaum district.〈/em〉〈em〉 The Co-ordinates are 16.4962° N and 74.3727° E. The area is underlain by basaltic lava flows, known as Deccan Trap. Plagioclase and pyroxene make up the majority of the fine-grained volcanic rock known as basalt, which also contains biotite, olivine, and quartz. Basalt is composed of calcic plagioclase and pyroxene. Plagioclase is seen in the form of laths. Common pyroxene found in basalts is augite. Along with this modal analysis of these rock samples has been carried out. From this it is evident that plagioclase is most abundant mineral followed by augite. Iron oxide and glassy material is also present in considerable amount followed by biotite. Olivine has been found exceptionally. Basalt samples from different flows show different textures, like porphyritic, intergranular and sub ophitic. Laterite covers the uppermost basaltic flow. The flows are equivalent to Panhala Formations of Wai Subgroup. 〈/em〉〈/p〉

Beschreibung: 〈p〉〈em〉By now, the world is shifting its energy source from nonrenewable energy to renewable energy in need of sustainable energy source, mitigating environmental and climatic problems. Renewable energy sources are sufficient and environmentally friendly. Ethiopia has a significant potential in hydro, solar, wind, and geothermal energy source. Particularly, in the study area, Somali region, there is significant amount of solar energy potential ranging from a minimum of 1,772.557983 Wh/m〈sup〉2 〈/sup〉(approximately 1,772 Kwh/m〈sup〉2〈/sup〉) and maximum of 2,476.39502 Wh/m〈sup〉2〈/sup〉 (approximately 2,476 Kwh/m〈sup〉2〈/sup〉) per year. Even though, the zone has not given sufficient consideration to its opportunities. But, currently, in the country’s ten year strategic plan, the government gives significant attention to invest on this abundant energy source. To make this abundant amount of solar energy useful and functional, identifying and selecting suitable site/s for the development of solar power plants are very crucial. This paper focuses on suitability analysis for identifying and selecting suitable site/s using〈/em〉〈em〉 Geographic Information System (GIS) and multi criteria based Analytical Hierarchy Process (AHP)〈/em〉〈em〉 by taking into account factors like solar energy potential〈/em〉〈em〉, 〈/em〉〈em〉slope, aspect, land use land cover, proximity to road, proximity to electric main grid and distribution lines, proximity to river/streams, technical and socio economic aspects. 〈/em〉〈em〉AHP method was adopted to determine the weight of each criterion.〈/em〉〈em〉 〈/em〉〈em〉Suitable areas were identified through a linear overlay of spatially distributed weighted criteria using a GIS solution. Criteria GIS layers were converted into rated value layers using four grades and by combining the rating value layers with the weightings, a site suitability map was developed, in 〈/em〉〈em〉high〈/em〉〈em〉, 〈/em〉〈em〉moderate, 〈/em〉〈em〉low and unsuitable. Accordingly, 〈/em〉〈em〉in the study area, nearly about 11.51% highly suitable for solar farm development and about 77.63% of the study area is moderately suitable. Thus, with some modifications and investment 89.14% of the study area is suitable to deploy solar farm. Contrary to this 10.85% is less or unsuitable for the development of solar farm in the region because of some restrictive factors which are not suitable for solar farm installation and development. 〈/em〉〈em〉〈/em〉〈/p〉

Beschreibung: 〈p〉〈em〉This study was objectively conducted to explore the tree diversity of Langtang National Park (LNP), Nepal and show the correlation between spectral variables and tree biodiversity. Sentinel-2 MSI of LNP in Nepal was acquired from https://scihub.copernicus.eu/. Total 60 samples were collected from forest. Pearson correlation was established to show relationship between tree species diversity and reflectance values. Bagging LASSO algorithm was used to validate the model. Result shows that Shannon-Weiner index was ranging from 2.9 to 3 and it was the highest in dense forest. Altogether, there was 18 tree species in LNP. The highest importance value index was 79.64 of 〈/em〉〈em〉Rhoderndron arborum and it was the least around 3.44 of Prunus cornuta. 〈/em〉〈em〉Classified map of tree species of LNP showed high Kappa statistics with 0.7. The NIR band B6, B7, B8 and B8A performed high separability for tree species. High reflectance values were recorded of Betula alnoides, Qurecus semicarpofolia and Castonopsis hystrix but it was the lowest of Querus lamellose. The higher reflectance value was recorded of Juniperus indica and Sorbus cuspidate in case of shortwave-infrared spectrum (SWIR, Band 11) and SWIR2 (Band 12). The highest negative correlation was recorded between Simpson’s index and B7 with 〈/em〉〈em〉-0.386 and it was the highest positive correlation between Shannon-Weiner Index (H’) and B8 of 〈/em〉〈em〉Sentinel-2 with 0.361. The highest correlation was found between Simpson index and B8A_Entrophy with 〈/em〉〈em〉-0.365. 〈/em〉〈em〉Bagging LASSO model performed better prediction to show correlation between biophysical characteristics and reflectance value of remotely sensed data. 〈/em〉〈/p〉

Beschreibung: 〈p〉〈em〉The purpose of this study was to assess the potability of groundwater resources in some parts of the Anantapur district of the Indian state of Andhra Pradesh. The water quality index, a spatial evaluation of groundwater using a GIS-based interpolation method, and the polluting groundwater index are some of the methods used to analyze water quality and explain the water quality of the studied area. A total of 22 groundwater samples were obtained during the post-monsoon period. The samples were tested for pH, EC, TDS, TH, and the major cations and anions. PIG levels between 0.98 and 1.98, with an average of 1.36, categorize low contamination in 5% of the research area and groundwater that is fit for human consumption. Additionally, 77% of the groundwater samples have drinking qualities that are only slightly acceptable. WQI values ranged from 85.97 to 113.52 mg/L, indicating that 55% and 45% of the samples are safe for drinking, respectively, while the other 45% are not. Groundwater samples are found in the field of rock dominance, according to the Gibbs plot. GIS techniques are being used to analyze the spatial variation of groundwater quality, and the results show that the majority of groundwater samples marginally meet standards for potable water, necessitating prior treatment before use. 〈/em〉〈strong〉〈em〉〈/em〉〈/strong〉〈/p〉

Beschreibung: 〈p〉〈em〉Around the world, disasters are becoming a growing concern. Natural disasters like floods, earthquakes, severe storms and tropical cyclones, droughts, wild land fires, and man-made disasters like hurricanes and tornadoes have damaged the environment as well as destroyed economic and social infrastructure over the previous five decades. The Geographical Information System and Remote Sensing have been used as potential tools for disaster management and monitoring, particularly in the pre, during, and post-disaster stages. Utilizing electromagnetic radiation (EMR) wavelengths and sensors, multi-temporal spatial information can be obtained to simulate the disaster's nature in GIS which can aid to identify and predict the probability of upcoming disasters. For microclimate analysis and damage detection during large-scale natural disasters, the satellite covers a larger area than any other platform. Remote sensing technology for disaster management tasks has been broadened by compact aerial drones. UAVs can be utilitarian for mapping features of disaster impacted related in urban areas in real time.〈/em〉〈/p〉