Advanced GIS

Assessing the risk of soil loss using geographical information system (GIS) and the revised universal soil loss equation (RUSLE)

2024-03-28T11:14:57+00:00

Soil erosion poses a significant environmental challenge in many developing nations, and critically evaluating the threat of soil erosion is paramount for sustainable land management practices. This study aims to identify the contributing factors to erosion and estimate the amount of soil loss in the Bosso Local Government Area of Niger State, Nigeria, using the Revised Universal Soil Loss Equation (RUSLE) model. Factors like rainfall erosivity soil erodibility topography cover and management and support practices were integrated into a Geographic Information System (GIS) environment to generate variable layers. The estimated values of ranged between 438.866 and 444.319 MJmmha-1 h-1 yr-1, 0.06 to 0.015 megajoules per hectare hour megajoules-1 hectare-1 millimeter-1, 0 and 572, 0 to 0.2, and 0 to 1, respectively. GIS raster calculations derived from these factors revealed a mean estimated soil loss rate of 0-6672.83t/h/yr-1 (tons per hectare per year). Notably, rainfall emerged as the most influential factor driving soil erosion within the study area. The study highlights the necessity for immediate intervention to mitigate soil erosion in the study area. Furthermore, to formulate effective conservation and management strategies, this study advocates for further research prioritizing severity analysis areas and estimating sediment loss across the regionSoil erosion poses a significant environmental challenge in many developing nations, and critically evaluating the threat of soil erosion is paramount for sustainable land management practices. This study aims to identify the contributing factors to erosion and estimate the amount of soil loss in the Bosso Local Government Area of Niger State, Nigeria, using the Revised Universal Soil Loss Equation (RUSLE) model. Factors like rainfall erosivity soil erodibility topography cover and management and support practices were integrated into a Geographic Information System (GIS) environment to generate variable layers. The estimated values of ranged between 438.866 and 444.319 MJmmha-1 h-1 yr-1, 0.06 to 0.015 megajoules per hectare hour megajoules-1 hectare-1 millimetre-1, 0 and 572, 0 to 0.2, and 0 to 1, respectively. GIS raster calculations derived from these factors revealed a mean estimated soil loss rate of 0-6672.83t/h/yr-1 (tons per hectare per year). Notably, rainfall emerged as the most influential factor driving soil erosion within the study area. The study highlights the necessity for immediate intervention to mitigate soil erosion in the study area. Furthermore, to formulate effective conservation and management strategies, this study advocates for further research prioritizing severity analysis areas and estimating sediment loss across the region.

Comparative analysis of noise pollution in high traffic zones of Faisalabad and Lahore

2024-02-26T10:46:33+00:00

The chaotic and loud traffic in crowded and densely populated urban areas poses challenges for environmental and urban experts in developing more efficient transportation plans that enhance both quality of life and environmental conditions. Lahore and Faisalabad, being prominent industrial cities in Pakistan, attract a large population due to their industrial importance. However, they encounter significant traffic problems, leading to a noisy and unpleasant environment. Using a Mesteth digital sound meter, noise level samples were gathered from various locations in Lahore and Faisalabad. In Lahore, sites included Jail Road, GPO Mall Road, Badami Bagh Bus Station, Thokar Niaz Baig, Gajumata Bus Station, Shahdra Metro Station, Kalma Chowk flyover, Mochipura Mor, and Babu Sabu toll plaza. In Faisalabad, sites such as GTS Square, Clock Tower, Railway Station, Santayana Road, Allied Mor Bus Stop, Narwala Road, McDonald's Road, D Ground Park, and Chenab Club were sampled. Fieldwork spanned from May 20th to June 23rd, 2022, conducted during morning and evening hours to capture peak and low traffic periods. Measurements were taken at a height of 1.2 meters from the ground and 1 meter away from the traffic flow line as per ISO standards. Data encompassed various zones, including heavy traffic, commercial, semi-commercial, and residential areas. The collected data was organized into Microsoft Excel sheets and subsequently inputted into ArcGIS 10.5 for mapping using Inverse Distance Weighting. After comparing the noise level values of both cities, it can be concluded that Lahore is facing more noise pollution as compared to Faisalabad due to the high noise pollution on the scale. The minimum amount of noise pollution recorded in these cities is 70 dB and the highest amount of noise pollution recorded in these is near 90 dB. This condition is very dangerous because according to the WHO the standard noise level in Pakistan is 75dB.

The relationship between macroeconomic variables and oil prices and analysis of global oil prices

2024-04-17T12:29:04+00:00

This study unravels the complex web of factors influencing OPEC crude oil prices, going beyond the immediate impact of isolated events. To this end, it has developed a multifaceted approach that uses nonparametric regression, correlation analysis, ARIMA forecasting, and spatial analysis with ArcGIS in a combined and integrated manner to reveal the interaction of variables that make up the family of macroeconomic factors and oil prices. The analysis confirms the expected positive correlations between oil prices and factors such as inflation, exchange rates (when the local currency weakens), and GDP (indicating increasing demand with economic growth). But it also explores the more complex relationship between oil production and price. Through the use of visualizations and forecasts, the study offers valuable insights into these relationships and provides projections for future price movements. This comprehensive approach provides a richer understanding of the multifaceted influences on oil prices, informing the decisions of policymakers, industry leaders, and investors navigating the complexities of the global oil market.

Spatial association in students’ residential apartment property characteristics around a university

2024-07-19T12:46:23+00:00

This study aimed at examining the presence of spatial association in residential property characteristics. It considered self-contained residential apartments around a public university in Akure, Nigeria. It is a survey research where data was collected through the use of questionnaires administered to the occupants of the self-contained apartment within a 500-meter radius of the ‘Southgate’ axis of the university. Data collected was analyzed with the use of ArcGIS software where spatial regression was carried out as well as the Anselin Local Indicator of Spatial Association for Cluster/outlier analysis. The result of the analysis revealed that some of the property characteristics have multicollinearity which led to dropping some of them that are represented by their collinear attribute. Distance from the university was observed to have an inverse relationship with the rental prices while other property attributes have a positive influence. From the cluster/outlier analysis, it was revealed that there are significant clustering/outlying in the central and northwestern parts of the study area. The property physical attributes such as kitchen quality, bathroom quality, toilet quality, window quality, and wall quality are high in the northwestern parts where there are new and modern designs while the central part of the study area has low quality of these attributes. The results of the analysis show that the clustering/ outlying, otherwise known as spatial association, among the property attributes are not the same across a particular place and the assumption of a uniform spatial association across the area would be misleading. It is therefore recommended that analysis of real estate investment around an academic institution in Nigeria should consider the property characteristics that influence prices and also adopt spatial clustering analysis to know the specific property characteristics that are to be improved upon on the quality that should be provided to have the best prices with reference to locations. The originality of this research comes in the use of a relatively smaller study area in examining spatial associations among property characteristics. It also considers the clustering/outlying analysis of the qualities of the property characteristics with reference to specific locations which would help real estate developers and analysts on the quality of finishing that should be given to each property attribute at different locations around a university campus in Nigeria.

A Review: Detection types and systems in remote sensing

2024-07-19T08:16:28+00:00

Remote sensing (RS) is the process of capturing, measuring, and digitally storing the reflection, radiation, and scattering values emitted by an object in one or more different band ranges of the broad electromagnetic spectrum and using this data to identify tools. RS is a method used by many professional disciplines and is frequently preferred today. Therefore, it has been the subject of this study. This study aims to conduct in-depth literature research on RS and present the results of related studies. For this goal, studies in the literature were reviewed. In addition, studies connected to RS or types were scanned in the Vosviewer application, and maps were constructed based on the locations, years, and keywords of the studies done.