Devraj Dhakal; Salad Omar Abdi; Kanwarpreet Singh; Abhishek Sharma
Abstract
The highway contributes significantly to human existence by providing safe, dependable, and cost-effective services that are environmentally friendly and promote economic progress. Highway projects need extensive planning to prevent work revisions, save time and cost, and increase job efficiency. Without ...
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The highway contributes significantly to human existence by providing safe, dependable, and cost-effective services that are environmentally friendly and promote economic progress. Highway projects need extensive planning to prevent work revisions, save time and cost, and increase job efficiency. Without a doubt, Highway transportation system must be constantly updated to keep up with technology breakthroughs, environmental change, and rising client needs. Incorporating Remote Sensing (RS) and Geographic Information Systems (GISs) has the potential to go beyond the limitations of RS, which typically collects information about the earth and its peripheries from space, and does not alter, analyze, calculate, query or display geographic engineering maps. Over the last few decades, the fusion of RS and GIS has shown promise, and the researchers are employing it in different stages of the Highway Planning and Development Process (HPDP) such as optimal route analysis, geometric design, operation and management, traffic modeling, accident analysis, and environmental impact analysis (noise pollutions, air pollutions). This paper gives an overall review of the use of RS and GIS on HPDP at various stages of their lifecycles.
Exploitation
M. Mohtasham Seyfi; J. Khademi Hamidi; M. Monjezi; A. Hosseini
Abstract
Methane gas emission, accumulation, and explosion are the most important risk factors in underground coal mines. Hence, having a knowledge of methane gas emission potential in underground coal mines is of crucial importance in preventing the explosion risk, loss of life, and property, and providing miners' ...
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Methane gas emission, accumulation, and explosion are the most important risk factors in underground coal mines. Hence, having a knowledge of methane gas emission potential in underground coal mines is of crucial importance in preventing the explosion risk, loss of life, and property, and providing miners' safety. The purpose of this work is to provide the prediction maps for the C1, C2, and B2 coal seams gas contents, and to identify high gas content panels in the Parvadeh No. 1, Tabas coal mine. For this, the data collected from exploratory boreholes is put into geostatistical analysis in ArcGIS in order to estimate the coal seams gas content in unsampled points using the kriging estimation method. Reviewing the gas content maps has revealed that seams of C1, B2, and C2 have gas contents more than 15 cubic meters per ton in about 84%, 55%, and 22% of the understudied area, respectively. The present work highlights the potential and the need for implementation of a methane pre-drainage system, particularly in deeper longwall panels.
Exploitation
S. Barak; A. Bahroudi; G. Jozanikohan
Abstract
The purpose of mineral exploration is to find ore deposits. The main aim of this work is to use the fuzzy inference system to integrate the exploration layers including the geological, remote sensing, geochemical, and magnetic data. The studied area was the porphyry copper deposit of the Kahang area ...
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The purpose of mineral exploration is to find ore deposits. The main aim of this work is to use the fuzzy inference system to integrate the exploration layers including the geological, remote sensing, geochemical, and magnetic data. The studied area was the porphyry copper deposit of the Kahang area in the preliminary stage of exploration. Overlaying of rock units and tectonic layers were used to prepare the geological layer. ASTER images were used for the purpose of recognition of the alterations. The processes used for preparation of the alteration layer were the image-based methods including RGB, band ratio, and principal component analysis as well as the spectrum-based methods including spectral angel mapper and spectral feature fitting. In order to prepare the geochemical layer, the multivariate statistical methods such as the Pearson correlation matrix and cluster analysis were applied on the data, which showed that both copper and molybdenum were the most effective elements of mineralization. Application of the concentration-number multi-fractal modeling was used for geochemical anomaly separation, and finally, the geochemical layer was obtained by the overlaying of two prepared layers of copper and molybdenum. In order to prepare the magnetics layer, the analytical signal map of the magnetometry data was selected. Finally, the FIS integration was applied on the layers. Ultimately, the mineral potential map was obtained and compared with the 33 drilled boreholes in the studied area. The accuracy of the model was validated upon achieving the 70.6% agreement percentage between the model results and true data from the boreholes, and consequently, the appropriate areas were suggested for the subsequent drilling.
