Toward Smart Urban Management: Integrating Geographic Information Systems and Geology for Underground Bearing Capacity Prediction in Casablanca City, Morocco

Abstract

To effectively manage the sustainable urban development of cities, it is crucial to quickly understand the geological and geotechnical attributes of the underground. Carrying out such studies entails significant investments and focused reconnaissance efforts, which might not align seamlessly with large-scale territorial planning initiatives within a city accommodating more than 3 million inhabitants, like Casablanca in Morocco. Additionally, various specific investigations have been conducted by municipal authorities in recent times. The primary aim of this study is to furnish city managers and planners with a tool for informed decision-making, enabling them to explore the geological and geotechnical properties of soil foundations using Geographic Information Systems (GISs) and geostatistics. This database, initially intended for utilization by developers and construction engineers, stands to economize a substantial amount of time and resources. During the urban planning of cities and prior to determining land usage (five- or seven-floor structures), comprehending the mechanical traits (bearing capacity, water levels, etc.) of the soil is crucial. To this end, geological and geotechnical maps, along with a collection of 100 surveys, were gathered and incorporated into a GIS system. These diverse data sources converged to reveal that the underlying composition of the surveyed area comprises silts, calcarenites, marls, graywackes, and siltstones. These formations are attributed to the Middle Cambrian and the Holocene epochs. The resultant geotechnical findings were integrated into the GIS and subjected to interpolation using ordinary kriging. This procedure yielded two distinct maps: one illustrating bearing capacity and the other depicting the substratum. The bearing capacity of the soil in the study zone is rated as moderate, fluctuating between two and four bars. The depth of the foundation remains relatively shallow, ranging from 0.8 m to 4.5 m. The outcomes are highly promising, affirming that the soil in Casablanca boasts commendable geotechnical attributes capable of enduring substantial loads and stresses. Consequently, redirecting future urban planning in the region toward vertical expansion seems judicious, safeguarding Casablanca’s remaining green spaces and the small agricultural belt. The results of this work help to better plan the urban development of the city of Casablanca in a smarter way, thus preserving space, agriculture, and the environment while promoting sustainability. In addition, the databases and maps created through this paper aim for a balanced financial management of city expenditures in urban planning.

1. Introduction

Population development causes urban expansion [1]. This is represented by the creation of new towns, the reorganization of agglomerations, and the growth of already existing cities. However, before using a piece of land, it is crucial to understand its underground properties through geological and geotechnical analysis. The safety and effectiveness of using the Earth’s surface are determined by the results of these surveys. The main stage in creating sustainable and smart cities is to carry out a natural structure analysis through in-depth surveys [2]. As a result, town planning must be adapted to the geology of the sites, thus introducing the science of urban geology in the daily decisions of planners and engineers. Urban geology is the application of geological knowledge for the planning and management of metropolitan areas, including the analysis and interpretation of rocks, soil, and groundwater for planning and designing civil structures. Unfortunately, the value of this science is not yet fully recognized by the ones responsible for the management and improvement of cities, despite its benefits in terms of cost and environmental improvement [3]. The provision of existing underground databases to administrations and planners allows for obtaining information about difficult-to-access or fully urbanized areas, such as the need-to-know underground information for a road construction project in a fully urbanized zone. This is without mentioning the time savings and economic profit that these types of databases bring.

At the level of the literature review, many urban geological studies have been conducted and give excellent applications for urban and environmental geology [4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20]. They have well dealt in detail with the impact of geology on urban planning, while a few also introduced geophysics as a useful tool for urban planners. Most of these works have not detailed the geotechnical parameters and their important roles in the field of urban planning, but some have been content with the correlations between the already existing geological and hydrogeological maps and urban planning schemes, in addition to the analyses of the known geohazards caused mainly by the phenomenon of urbanization [21,22,23,24,25,26]. A few studies have researched underground geotechnical characteristics in relationship with urban planning, like the paper of Solofo, et al. published in 2018, which focused on the city of Antananarivo in Madagascar [27], but it remained modest regarding the detailed explanation of the validity of geostatistical techniques for geotechnical data and the modeling of histograms and variograms of the data, as well as the evaluation of conditions related to the types of foundations used. The mapping of the geotechnical data must be presented to different users in a format that can be used in urban planning [28]. For this reason, several studies have been carried out to investigate the most appropriate way of presenting geological data on maps of urbanized areas. For this, the introduction of Geographic Information Systems (GISs) has greatly facilitated this task and made new applications, especially since GISs have been a subject of multiple scientific papers that study urban planning, geology, and also hydrogeology [29,30,31,32,33,34].

The present work focuses on the city of Casablanca in Morocco. Given its very high percentage of urbanization during the last decades [35,36], Casablanca has known a mushrooming urban sprawl that has ravaged a large agricultural belt and several green spaces. With a continuing rural exodus and a significant urban sprawl, the city will soon be facing a land and a plot crisis. This urban development, which leads to increased land consumption, generates significant costs related to the geotechnical assessment of the land. Indeed, the administrations engage several contracts with laboratories to obtain geological data before construction. This is performed even for road projects or sanitation projects. These analyses, unfortunately, consume a lot of time and sometimes generate optional expenses for adjacent projects. The knowledge of subsoil characteristics as well as the creation of large-scale databases will allow for the following: (i) a probable reorientation of Casablanca’s urban planning toward verticality; (ii) cost savings in laboratory expenses; (iii) better time management; and (iv) the avoidance of any potential risks due to ignorance of underground conditions. Few projects or papers have addressed the geotechnical aspect of the city of Casablanca, despite Mariama, et al. in 2018 [37] discussing the importance of urban subsurface databases for the city of Casablanca, but the work did not cover the geotechnical aspect of the subsoil, particularly the mechanical properties of the soil. The idea of the present work is to use Casablanca’s lands in the most sustainable way, thus adapting its urban planning toward an efficient use of underground characteristics. It also emphasizes the importance of the creation of underground databases that allow urban planners better management. To achieve this, it is essential to check the geotechnical characteristics of the soil, essentially the bearing capacity and the level of the substratum. A huge geotechnical database has been created concerning the city of Casablanca, but, unfortunately, these data are scattered over various organizations and laboratories. Indeed, identical tests are conducted within the same vicinity, resulting in additional costs, even though the geological features remain relatively consistent within a small radius.

In this project, we leverage the pre-existing surveys conducted in the Casablanca region to produce comprehensive geotechnical and geological data maps for the entire research area; thus, the costs of using geotechnical test laboratories will also be minimized. While it is accurate that the individual expenses associated with these tests may not always be high, their collective expenditure can be significant. Using existing surveys collected from different stakeholders, Geographical Information Systems (GISs), and geostatistical techniques, two maps of soil and bedrock capacity for the whole study area have been generated. These maps serve a valuable purpose for planners, developers, and builders alike. In the realm of urban planning and zoning, these maps enable the assessment of the pros and cons associated with different land uses. This, in turn, aids in the preservation and optimal utilization of land resources. In spatial planning, geotechnical and geological maps play a crucial role in making informed decisions regarding proposed activities, whether they should proceed or be declined. Frequently, a soil survey is not deemed necessary prior to the creation of a master plan or even after the establishment of a site layout. However, in today’s context, geotechnical studies are considered a prerequisite. Any engineering structure, like a building, bridge, road, drainage network, dam, etc., requires detailed knowledge of the geological, geotechnical, and engineering geological properties of the foundation and the materials used for construction in order to recognize, control, and/or prevent related hazards [6]. Also useful for the builder, geotechnical and geological maps give him an idea of the problems of foundations conditioning the types of buildings and their heights.

The specificity of this work compared with others already published in the literature review is that it emphasizes the importance of the geotechnical studies of the underground in order to build in a smarter way. This work combines fieldwork, coordination between the various private and public stakeholders in the local administration of the study area, and the use of geographic information systems and geostatistical data. It also shows that it is possible to rely on simple maps summarizing the geotechnical conditions of large areas to manage urban plots.

Geostatistics coupled with geotechnical information provide decision-makers with useful maps of the subsoil for smart urban planning. This preliminary work comes from the perspective of providing Moroccan administrations with their own geotechnical and geological database for a smarter future urban projection.

2. Materials and Methods

2.1. Study Area

The study area is in the southeastern part of the Casablanca prefecture, which belongs to the central part of the wilaya of Greater Casablanca (Figure 1). The latter is located on the Atlantic coast in northwestern Morocco around the latitude and the longitude of 33°35′ N, 7°25′ W.

Casablanca is characterized by an average temperature of 10 °C in winter and 28 °C in summer, with a temperate and humid climate. Its average annual precipitation is between 100 and 443 mm. According to the last census, the population of Casablanca has exceeded four million inhabitants. The surface of the study area is about 33 km², and it belongs to the Benmsick prefecture, Fida Mers sultan prefecture, Sidi Moumen district, Moulay Rachid district prefecture, and Mediouna province, as shown in Figure 1 in the orange outline.

2.2. Data Acquisition

In this study, both geological and geotechnical maps of Casablanca city were used. The information was extracted from the map’s sheets using geostatistical tools in Arcgis. Many other data were utilized in order to verify and validate the exactitude of the given information. The used data are listed in

Table 1. The used data of the study area.

Data Type	Year	Procedure
Geological map sheets of Casablanca Mohammadia (1/100,000)	1982–1983	Digitization, observing and comparing
Geotechnical map sheets of Eastern Casablanca Mohammedia (1/50,000)	1953–1954	Digitization, observing and comparing
100 Geotechnical soundings surveys georeferenced in the Lambert conform conic projection	1990–2020	Digitization and Geostatistics

.

2.3. General Methodology

The two geological and geotechnical maps at a scale of 1/100,000, representing Casablanca and the surrounding areas (Casablanca–Mohammadia), were required to have an exact idea about the formations existing in the entire study area. All maps were georeferenced according to the geographical coordinate system of Merchich-Zone 1 and the Lambert Conformal Conic projection. The quadratic average error was verified, and it matched the norms well. After georeferencing maps, the data management tools and the spatial analyst tools in the arc toolbox were used to cut the maps on the actual studied zone of the prefecture of Casablanca.

The methodology, illustrated in Figure 2, involved a series of procedural steps. It initiated with the comprehensive collection of all accessible data, followed by the processes of georeferencing and data digitization.

Subsequently, upon the establishment of the digital database, its utilization phase commenced. An integral step within this framework encompassed the validation of geological and geotechnical data, a pivotal procedure enabling the enhancement of the geomodeling process before embarking on data processing. Furthermore, the utilization of Arcgis Pro 10.8.2 software played a paramount role, expediting the iterative procedures necessary to converge toward the final model.

In the subsequent sections of this paper, we will employ geostatistical interpolation techniques, notably ordinary kriging, for data processing purposes. The methodology employed relies on several assumptions, including the following critical considerations:

• The foundations are superficial.
• The shape of the foundations is square or rectangular.
• The ground is horizontal, and the foundations are vertical and not inclined.
• The geometry and mechanical properties of the soil are homogeneous.
• The contact between the sole and the ground is rough.
• The characteristics of the applied load are vertical and centered.
• The absence of a water table at different depths.

2.4. Geotechnical and Topographical Context

Both geological and geotechnical maps were georeferenced according to the Lambert Conic Conformal projection. Figure 3 shows the different formations exiting in the studied area.

The study area belongs to the domain of the northern coastal Meseta, characterized by its Paleozoic pleated substratum, flush or shallow, which was more or less completely peneped before the deposit of the permo-triassic formations. As shown in Figure 3, the near soil of the study area consists of calcarenite silts, marls, graywackes, and siltstones.

Table 2. Geological components of the study area.

Geological Formations	Index	Geological AGE
Gray silts	A1	Actuel to rharbien	Holocene
Brown silts	q(1-6lb)	Soltanien to villafranchien	Pleistocene
Red silts	q(1-6lr)
Laminated gray dune calcarenites	q3d	Maarifien
Dune calcarenites	q4d	Masoudien
Beige sandy marl	m2	Inferior Burdigalien	Miocene
Graywackes and Siltstones	Km1	The Average cambrien

lists all the types and ages of the existing geological formations.

On the other hand, the geotechnical map clearly shows the dips of the different geological layers, the different existing faults, the sliding scars, and also the different boreholes executed while establishing this card. Indeed, the purpose of the present work is essentially to characterize the geotechnical parameters conditioning the civil engineering construction, especially the depth of the substratum and the bearing capacity of the underground. For this reason, a preliminary study of the geological, geotechnical, and also topographical characteristics is paramount.

For the topographical characterization, more than 15,200 points on the sides of the study area were inserted into a single database, spread over the entire study area at a density of 460 points per km². Empty areas correspond to built-up zones. These points were used to generate a topographic map of the area using the generate 2D Grid function in the GDM71 MultiLayer 2014 software, as shown in Figure 4 below. This map is very important before beginning geological investigations of the site, as it gives a detailed idea about the topography. Figure 4B is a 3D model of topographical levels.

2.5. Substratum Definition and Bearing Capacity Calculation

In geology, the substratum is defined as the soil layer that has good mechanical characteristics and can take up the forces soliciting the structure and transmitting through the foundations.

The mechanical characteristics of soil are mainly defined by a geotechnical parameter named bearing capacity. It is defined as the capacity of a soil to withstand the pressure exerted on it by loads. This pressure is calculated by making the ratio between the mass and the surface of the ground. This parameter has lately been a subject of much scientific research using different methodologies [25,26,27,28,29,30,31]. Indeed, if the pressure exerted by the equipment is greater than the bearing capacity of the ground, there will be a settlement of the latter until finding the balance capacity bearing—pressure. The resistance of the soil increases with the embedding of the foundation to a certain critical value, after which it becomes constant as a function of the depth.

The extensive literature has explored various approaches to calculate bearing capacity of shallow foundations, including experimental studies and numerical modeling [38,39,40,41,42,43,44,45,46,47,48].

In general, the bearing capacity of shallow foundations is typically assessed using the equation introduced by Terzaghi in 1943 [45].

The equation for the bearing capacity of a rigid strip footing subjected to a vertical load is commonly expressed by Equation (1) as follows:

$$\mathrm{q}\text{’}\mathrm{u}=i_c{S}_c\mathrm{C}{N}_c+{\displaystyle \frac{1}{2}}{S}_{\gamma }\mathsf{\gamma }B{N}_{\gamma }{i}_{\gamma }+S_q\mathsf{\gamma }\mathrm{D}{N}_q{i}_q$$

(1)

where

$i_c,i_{\gamma },i_q$: coefficients of the inclination of loads on the vertical.

$S_c,S_{\gamma }{,S}_q:$ shape coefficients of the foundation.

$N_c,N_{\gamma },N_q$: dimensionless parameters whose values are related to internal friction angle ϕ and soil cohesion in place c (kPa).

γ: Apparent weight (kN/m³).

This equation encompasses three distinct components: a surface term, a cohesion term, and an overloading term, all of which are intricately linked to the soil’s friction angle.

Apart from the kriging method that is used in the present work in order to evaluate the bearing capacity of the underground using data from the geotechnical boreholes, the parameter of bearing capacity may also be calculated by using the following function, related to superficial foundations, the most used foundation method in urban areas. The hole bearing capacities used in the present work were calculated using laboratory parameters.

2.6. Structuring the Database

The data used in this work are in the form of geotechnical surveys, as shown in a georeferenced map in Figure 1. They were collected from various organizations, companies, consulting firms, as well as public and private organizations that have previously worked in the region.

In total, not less than 100 soundings were obtained on an urban surface of approximately 33 km², with an average density of 3 observation points per km². However, the analysis of these data has shown that their content and quality are highly variable, which finally led to the use of 51 polls among 100 soundings so as not to affect the reliability of the database. The elimination of these soundings was mainly due to the absence of some information, like, for example, the geographical coordinates, the bearing capacity, or sometimes non-homogenous information in the same soundings. The boreholes were georeferenced and projected in the Lambert conformal conic projection.

It is also important to note that the study area spans an area of 33 km², as shown in Figure 1, which contains the surveyed points distributed over an irregular area. After data interpolation, the results will spread over a square area that is somewhat more spread out and regular.

This is due to the kriging effect, which for each interpolation point generates a set of results that surround the studied point. For this, we chose to map the results onto a square area that represents the limit of the data generated by the software and allows us to know the technical characteristics sought in a larger area.

In fact, the quality of the geological descriptions of the underground reconnaissance works depends to a large extent on the objectives. The data inventory revealed a great deal of heterogeneity in the means used, which required a limitation of the data used in the database, namely:

• The level of good soil (m): indispensable parameter in the implementation and dimensioning of any civil engineering works.
• Soil bearing capacity q (bars): bearing capacity “q”. This characteristic of the soil is essential; the higher it is, the better. But still, it must be homogeneous under all the foundations; otherwise, a differential settlement will inevitably occur and induce pathologies.
• For the ground, the angle of friction (φ), and the cohesion (C) Ref. [49].

Each survey point has been defined geographically by its coordinates (x,y). Surveys without coordinates were not considered. Nevertheless, some of them, whose layout is shown on the reports, have been located following field visits and in situ GPS coordinates; although this step presupposes an error in the acquisition of coordinates, a calibration was performed in parallel with the aerial catch of the area. The urban database was developed from three complementary databases: Excel and Access for entering data from survey results, and Arcgis Pro 10.8.2 software for digitization, map mapping, data processing, and modeling. After the data capture, two maps were generated using the geostatistical interpolation tools available in the Arcgis Pro 10.8.2 software: the ground level map and the ground bearing capacity map.

These maps are used for the implementation of any new project, including construction, servicing, roads, etc., and even in the urban planning of the area and in the establishment of future development plans.

2.7. Geostatistical Techniques

Geostatistical techniques (such as the kriging method) are based on statistical models, which include autocorrelation, defined as the statistical relationships between the measured points. Not only can they produce a forecast area, but they can also provide measures for the certainty or accuracy of these predictions. To make a prediction using the geostatistical method, the first task is the discovery of dependency rules. These methods have been the subject of a lot of scientific papers. Subsequently, these techniques will be used for the development of the four maps: bearing capacity of soil, substratum lift, the cohesion of the soil, and the angle of the crop.

For checking dependency rules and consistency between the metadata used, the creation of data histograms as well as the display of voronoi maps in Figure 5 and Figure 6, trend analysis, and semi-variograms is very important.

An extensive examination of the available data is necessary before processing in order to create an approximation that is as representative of the phenomena as possible. Using statistical methods, data can be viewed and analyzed for the purpose of exploring geographical correlations, identifying anomalous values, and detecting trends or drifts in the data.

The distribution of the data, illustrated by the histograms in Figure 5, shows a heterogeneous aspect between the different existing data, with the four histograms being generally primordial, sometimes discontinuous, showing the absence of a range of values and reappearing at the level of other values. This is in full conformity and very well explained by the weathering between a rocky structure and the non-cohesive one, rather soil. Kurtosis values ranging from 1.17 to 5.4 clearly show asymmetry in the data distribution.

The Thiessen polygons, or Voronoi maps, shown above in Figure 7, illustrate how a space is geographically divided into polygons based on how close the data source points are to one another. Every polygon on the Voronoi map has a corresponding source point, represented by a dot on the map; all points inside that polygon are colored the same because they are closer to that point than they are to any other source point. This provides a sense of the zones of influence’s spatial distribution prior to data interpolation. These maps, as shown in the figure above, were generated for four parameters: the bearing capacity, the substratum, the cohesion, and the angle of friction. We can see from the Voronoi maps that for the same polygon subdivision, the values of the various interpolated parameters change. This allows us to draw a number of conclusions before proceeding with the choice of interpolation method.

The trend analysis tool shown in Figure 8 identifies the presence of a drift, which is considered the average trend of the variable. For all four variables, the trend maps reveal the presence of drifts evaluated by second-order polynomials, which assume that our dataset is not stationary.

Examining the variographic surface derived from the various variables under investigation, as depicted in Figure 9 below, reveals a pronounced anisotropic behavior at a large distance, with significant variability even in the 0-angle direction—roughly equivalent to the horizontal direction of the ground. Semi-variograms occasionally show parabolic data, while other times they show heterogeneous data.

In the present work, the geostatistical method used is the ordinary Kriging tool, which adopts the assumption that there is a spatial conjunction that can account for surface variations in the direction or distance linking the sampling locations. It is particularly valuable in situations where a directional deviation or spatial correlation of distance is known to exist in the data. Science concerning mining and geology frequently incorporates it [50,51].

The weighted sum of the data is the conventional formula used in interpolation methods:

$$\widehat{Z}\left(s_0\right)={\sum }_{i=0}^N{\mathsf{\lambda }}_{i}Z\left(s_i\right)$$

(2)

where $Z\left(s_i\right)$ is the value found at the $i_{th}$ location, ${\lambda }_i$ is the unknown weighting of the value found at the $i_{th}$ location, $s_0$ is forecast location, and N is the number of values.

On the other hand, with the kriging method, the weights are based not only on the distance between the points recorded and the forecast location but also on the general spatial organization of the points recorded, as explained before.

3. Results

3.1. Bearing Capacity Calculation Using Geostatistics

The ground lift map of the study area presented in Figure 10 was developed by the regular kriging tool available on the Arcgis Pro 10.8.2 software. This made it possible to determine the resistance of the soil at any point of the zone, assuming that the footings of the foundations are superficial. As the map shows, the ground lift varies between a minimum of 2 bars and a maximum of 4 bars. The majority of the soil is characterized by a capacity between 2 bars and 2.4 bars dominating the central and eastern parts of the area. The lift between 2.4 and 3 bars is located on the northern and southern peripheries, while the higher lifts between 3 and 4 bars occupy the northwest part. This confirms the results that give the range of lift for each type of lithology in

Table 3. Suitability of bearing capacity.

Land Suitability Classes
	Suitable	Moderately Suitable	Non-Suitable
Bearing capacity (kPa)	>350	350–150//150–50	<50

. As already discussed in Section 2.6, the results of the studied area will be modeled on a perfectly square surface, as shown below in Figure 9. This is due to the interpolation effect, which generates average results for each interpolated survey.

The juxtaposition of the capacity results on the lithological log confirmed that the weakest bearings are often housed in sandy geological formations, calcareous, gravelly, and clayey, while the most important bearings refer to formations of sandstone, schist, and travertine limestone. The geotechnical aspect of formations is not independent of their geological aspects. According to the land suitability classes for construction depending on the soil bearing capacity, most of the studied area is qualified as moderately suitable to suitable, as shown in Table 3.

The error map in Figure 11 shows values going from 0.23 to 1.12, which largely falls within the scope of the acceptable. The polling points with the smallest interpolation error are marked in white, and as one moves away from the polls, the error increases, which is quite logical.

3.2. Calculation of “Substrate Depth” by Geostatistical Methods

Using the same ordinary kriging techniques as before, the substratum map was generated (Figure 12). The deepest substratum is at a depth of 4.5 m, and the nearest is at a depth of 0.8 m. The majority of the terrain is characterized by a close substratum between 1.45 and 2.06 m.

The error map Figure 13 shows values ranging from 0.38 to 1.78, which largely falls within the scope of the acceptable. Polling points have the smallest interpolation error, and as one moves away from the polls, the error increases.

If we concatenate data of bearing capacity, substratum, and geological formations with the stratigraphical log of the studied area, most of the ground has a bearing capacity between 2 and 2.4 bars located in a substratum between 1.45 m and 2 m. According to the synthetic log, the principal formation lodging the foundations will be made of clay, which is a sedimentary rock defined by its mechanical properties of plasticity when wet and its ability to harden when dried or fired. This make of clay is an average substratum regarding its bearing capacity.

To summarize, these present studies have shown that soil lift ranges from a minimum of 2 bar to a threshold of 4 bar, while the level of the substratum varies between 0.8 m and 4.5 m. The juxtaposition of the lift results on the lithological map confirmed that the weakest lifts are often housed in sandy, limestone, gravelly, and clayey geological formations, while the most important lifts refer to sandstone, shale, and travertine limestone formations. The geotechnical aspect of the formations is not independent of their geological aspects.

As an example of urban planning in the present studied area, we have taken the urban management planning of Moulay Rachid Borough, as shown below in Figure 13, which constitutes just a part of the studied area and not the whole zone. This example of city planning indicates the different separation of urban places that exists in every zone and that are as follows: Zone E, Zone A, Zone C, Zone I, Zone D, and Zone CV. Everyone has a specific regulation, which is organizing the type of construction (industrial, dwelling, villas, green spaces, etc.).

Also, it discusses the height of civil constructions; for example, in Zone A7s, the height of the construction is fixed to 26.5 m (seven floors), while for Zone D, the maximum height is 8 m (one to two floors).

These kinds of decisions cannot be made without referring to geological and geotechnical data. Such results as those in the present work help urban managers to better schedule their urban planning, thus preserving space, time, and green spaces. Urban geology provides information on urban geologic environments as a scientific basis for planners and engineers for rational land use planning and urban development [10].

4. Discussion

To better manage the urban development of sustainable cities, a preliminary geotechnical and geological study is essential. The present work has led to the creation of a geotechnical and geological database of the studied area in Casablanca using GIS and geostatistics. The goal is to create a database and geotechnical maps, which developers and construction engineers can use directly without performing new geotechnical studies, thus saving a considerable amount of time and money. Also, the purpose is to analyze the urban development of Casablanca and concatenate it with geological data. This can help us profit from the capacity of soil and construct more vertically to save agricultural and green spaces.

Indeed, a study launched in 2014 [35] confirmed the very expansive character of the city of Casablanca, as shown in Figure 14. In fact, there have been notable accelerations in urbanization over time, and the rate of expansion has not remained constant. Specifically, between 1956 and 2011, when the city saw a demographic explosion, and the rate of expansion has been estimated to be 2.3 km²/year.

Figure 14 maps the urban sprawl of the entire Casablanca prefecture between 1900 and 2011. The section studied in this article and mapped in Figure 1 represents the southeastern part of the city of Casablanca.

That said, the town planning of Casablanca must turn into vertical and green planning. However, this step necessarily involves the verification of the capacity of Casablanca soils to support buildings with “n” floors. For this, sufficient knowledge of the geological and geotechnical parameters of the study area is required. Among these parameters, the most important are the soil lift and the level of the substratum that were the subject of this study.

The present work shows that the characteristics of Casablanca’s soil are really encouraging for vertical buildings. The future smart Casablanca can be seen in green and vertical urban development, thus ensuring minimum consumption of agricultural land and maximum environmental and ecological conservation. This work aims to make the city of Casablanca, Morocco’s metropolis, a recognized urban model that follows the example of developed countries. The second perspective of this work is to generalize this work in the whole of Morocco in partnership with the most important laboratory in the country, which has the maximum of geological data of Morocco.

5. Conclusions and Perspectives

In conclusion, this research provides critical geotechnical and geological insights into the southeastern area of Casablanca, employing advanced GIS and geostatistics techniques to analyze subsurface data. The study produced two essential maps: one detailing the depth of the substratum and the other illustrating the soil’s bearing capacity. These maps, combined with a comprehensive database of subsurface conditions, offer a detailed understanding of the geological makeup of the area, including layers of calcarenite, silts, marls, graywackes, and siltstones, with formations dating from the Middle Cambrian to the Holocene. The data reveal that soil bearing capacities in the region are moderate, ranging between two and four bars, while the depth of the foundation varies from 0.8 m to 4.5 m.

These findings carry significant implications for the future development of Casablanca. The soil in the study area demonstrates commendable geotechnical attributes, making it suitable for withstanding substantial loads and stresses. Consequently, the study suggests that future urban planning should prioritize vertical expansion, allowing for more efficient land use and minimizing the encroachment on the city’s remaining green spaces and surrounding agricultural belt. This shift toward vertical construction would not only help preserve these valuable resources but also support the long-term sustainability of the city’s development.

Moreover, the scalable database developed through this research holds the potential to revolutionize urban planning processes in Casablanca. By continuously updating and expanding this geotechnical and geological database, city planners and decision-makers can make informed, data-driven decisions without the need for costly laboratory analyses. This approach provides a more cost-effective and resource-efficient method for urban development, aligning with the goals of sustainable and responsible city planning.