Application of Data Integrity Algorithm for Geotechnical Data Quality Management

The aim of this research work is to ensure the integrity and correction of the geotechnical database which contains anomalies. These anomalies occurred mainly in the phase of inputting and/or transferring of data. The algorithm created in the framework of this paper was tested on a dataset of 70 core drillings. In fact, it is based on a multi-criteria analysis qualifying the geotechnical data integrity using the sequential approach. The implementation of this algorithm has given a relevant set of values in terms of output; which will minimalize processing time and manual verification. The application of the methodology used in this paper could be useful to define the type of foundation adapted to the nature of the subsoil, and thus, foresee the adequate budget

Exploring the Relationship between LST, LULC and NDVI in Saïss Plain using Geospatial Techniques

Land use/land cover (LULC) change has been confirmed that have a significant impact on climate through various pathways that modulate land surface temperature (LST) and precipitation. However, there are no studies illustrated this link in the Saïss plain using remote sensing data. Thus, the aim of this study is to monitor the LST relationship between LULC and vegetation index change in the Saïss plain using GIS and Remote Sensing Data. We used 18 Landsat images to study the annual and interannual variation of LST with LULC (1988, 1999, 2009 and 2019). To highlight the effect of biomass on LST distribution, the Normalized Difference Vegetation Index (NDVI) was calculated, which is a very good indicator of biomass. The mapping results showed an increase in the arboriculture and urbanized areas to detriment of arable lands and rangelands. Based on statistical analyzes, the LST varies during the phases of plant growth in all seasons and that it is diversified due to the positional influence of LULC type. The variation of land surface temperature with NDVI shows a negative correlation. This explains the increase in the surface temperature in rangelands and arable land while it decreases in irrigated crops and arboriculture

Spatiotemporal Analysis of Groundwater Resources in the Saïss Aquifer, Morocco

In recent decades, the Saïss plain, in the northwest of Morocco, has experienced a noticeable increase in water demand due to a very significant population growth and economic development, as well as the climate change effects. With the aim of reaching optimal and dynamic management of these water resources, it is essential to have comprehensive and reliable information on the state of the aquifer systems in the region. To achieve this, we assessed a geostatistical analysis of groundwater level data, and created a multivariate regression model. Indeed, in this study, a spatiotemporal analysis of groundwater depth based on piezometric measurements of 45 wells was carried out for the period from 2005 to 2020. It compares and evaluates eight geostatistical interpolation methods and solves the problem of data gaps of the piezometric measurement by completing the chronological series of the groundwater level between 2005 and 2020 using the ARIMA model. The results demonstrate that the variation in the groundwater level between 2005 and 2020 indicates that the water table level is decreased in certain areas, but it has improved or remained constant in other areas. These results emphasize an urgent need for a dynamic management for the conservation of groundwater resources in certain areas of the region under this study

Land Surface Temperature in Response to Land Use/Cover Change Based on Remote Sensing Data and GIS Techniques: Application to Saïss Plain, Morocco

In order to analyze the impact of land use and land cover change on land surface temperature (LST), remote sensing is the most appropriate tool. Land use/cover change has been confirmed to have a significant impact on climate through various aspects that modulate LST and precipitation. However, there are no studies which illustrate this link in the Fez-Meknes region using satellite observations. Thus, the aim of this study was to monitor LST as a function of the land use change in the Saïss plain. In the study, 12 Landsat images of the year 2019 (one image per month) were used to represent the variation of LST during the year, and 2 images per year in 1988, 1999 and 2009 to study the interannual variation in LST. The mapping results showed that the land use/cover in the region has undergone a significant evolution; an increase in the arboriculture and urbanized areas to detriment of arable lands and rangelands. On the basis of statistical analyses, LST varies during the phases of plant growth in all seasons and that it is diversified due to the positional influence of land use type. The relationship between LST and NDVI shows a negative correlation (LST decreases when NDVI increases). This explains the increase in LST in rangelands and arable land, while it decreases in irrigated crops and arboriculture

Contextualizing the Smart City in Africa: Balancing Human-Centered and Techno-Centric Perspectives for Smart Urban Performance

The continuous growth of urban populations and the complexities of their current management in Africa have driven local governments to explore new technologies to optimize their urban and territorial performance. These governments and related stakeholders’ resort to the term “smart city” to orient the current urban planning policies and practices to be more efficient and adequate. Nevertheless, the issue that remains is how to contextualize this global term that has not yet been fully adopted by African cities that have claimed to be “Smart”. This contextualization becomes more complex in this critical context, where the city has not yet reached an ideal performance. Therefore, to reach this prospective African smart city, a critical review of how it would be both human-centered and techno-centered is imperative. This paper would review accordingly the above argument and set key performance indicator-based methodology on how to evaluate the smartness of a city in the African context.Applied Science, Faculty ofNon UBCEngineering, School of (Okanagan)ReviewedFacultyResearche