Planning Strategies and Design Concepts
Mapping Land Use Change to Analyze Urbanization and its Impact on Urban Floods in Tebessa City, Algeria.
2025 Volume 13 Issue 3 Pages 30-55
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2025 Volume 13 Issue 3 Pages 30-55
Rapid urbanization poses significant challenges for cities worldwide, particularly in managing natural hazards such as floods. In Tebessa, Algeria, accelerated and unplanned urban expansion over recent decades has markedly increased the city’s exposure to flood risks, making it the national leader in the number of buildings located within flood-prone zones. However, the direct link between urban growth and flood vulnerability in Tebessa remains underexplored. This study addresses this gap by examining the impact of urbanization-driven land use changes on flood risk over a 33-year period (1990–2023). Employing multi-temporal Landsat satellite imagery and the Land Use Change Detection Tool, the study maps urban expansion and assesses its spatial and temporal relationship with flood-prone areas. Post-classification comparison of images from 1990, 2001, 2012, and 2023 reveals a 47% increase in urban areas and a 39.39% rise in flood-affected zones, accompanied by a 42.06% reduction in bare land. These results indicate that rapid urbanization, often at the expense of natural drainage areas, is a primary factor in the intensification of urban flooding. The study highlights the effectiveness of remote sensing and GIS technologies in analyzing urban dynamics and provides actionable insights for urban planners. Integrating these tools into planning processes is essential for promoting sustainable development and effective flood risk mitigation in Tebessa and other similarly affected cities.
In the twenty-first century, the phenomenon of urbanization has garnered increasing attention from environmental experts. The global urban population has seen a significant surge, with half of Earth's inhabitants residing in urban areas by the turn of the 21st century (Annez and Buckley, 2009; Fonseka, Zhang et al., 2019). This rapid urbanization trend is poised to continue, particularly in Africa and Asia, where the United Nations Population Fund predicts that urbanization will bring about substantial social, economic, and environmental challenges (UNFPA, 2018).
The expansion of urban areas, characterized by burgeoning populations and infrastructure, has led to a notable decline in green spaces juxtaposed with a surge in impervious surfaces (Desta and Wordofa, 2025; Fang, Homma et al., 2024; Valy, 2010). Consequently, many regions face heightened flood risks due to population growth and rapid urban development, exacerbated by factors such as valley-side construction (Choubin, Moradi et al., 2019; Feng, Zhang et al., 2021; Hanani, Riniwati et al., 2024). These floods have deleterious effects on both human communities and the environment, including land degradation, increased casualties and property damage, and adverse impacts on ecosystems and public health (Kikegawa, Genchi et al., 2003; Meineke, Dunn et al., 2014).
Remote sensing technologies have emerged as invaluable tools for monitoring Earth's surface, enabling the generation of extensive datasets crucial for assessing natural resources and ecosystem dynamics (Nadège, Bertrand et al., 2023; REPSAHEL, 2015). The utilization of multi-date satellite imagery has gained prominence since the early 1970s for analyzing changes in land cover (Peter, 1995). Various remote sensing techniques have been explored to understand the spectral and spatial evolution of land cover units over time (Mallick, Kant et al., 2008; Tin‐Seong, 1995; Wang and Xu, 2010). Particularly, the detection of changes, especially those driven by anthropogenic activities such as urbanization, has become a focal point in land-use studies (Carine, Marc et al.; Coppin, Jonckheere et al., 2004; Radke, Andra et al., 2005).
The integration of remote sensing with Geographic Information Systems (GIS) offers a powerful approach to monitor land surface changes, particularly in urbanized areas (Gamba, Dell'Acqua et al., 2006). In the case of the city of Tebessa, like many Algerian urban centers, rapid urban growth has caused major spatial and environmental transformations (National Economic and Social Council, 2003). The local authorities of Tebessa revised their master plan for urban planning and development in 2012 to address the challenges of land availability for future urbanization (URBA-BA, 2018) which has recently made it the focus of particular attention by urban policies, which have gone so far as to give it an event-driven consecration (creation of 05 new urban poles in the Wilaya of Tebessa by Executive Decree N° 11-237 and Executive Decree N° 11-239 of July 9, 2011 (Official Journal of the Algerian Republic, 2011) which declared that the operation related to the construction of public housing and associated facilities in some Wilayas is in the public interest). A large number of projects have also been launched, including major housing programs and facilities within these new urban centers which are still ongoing to this day, including: 5 700 housing units + public facilities in urban pole N° 28 "El Dokkan", in addition to more than 5 230 housing units with multiple public facilities + the university campus in urban pole N° 03 "Boulhaf-Dyr" ... etc. Although these urban poles have been subjected in their urban design to the supervision of certified experts and technicians, given that this city is ranked first among Algerian cities in terms of the number of buildings constructed in areas exposed to floods, which was estimated at 17 236 buildings (National Economic and Social Council, 2003), in addition to its geomorphological features, including the dense hydrographic network present within its urban fabric, which exacerbates the risk of flooding (TALBI, GHERZOULI et al., 2023), it still suffers from recording significant losses resulting from seasonal rainfall every year within these new expansions. As the civil protection services of the Wilaya recorded on 10/25/2021 in pole N° 03 in Boulahf-Dyr, precisely at the level of the 3 240 AADEL housing program that was delivered to its beneficiaries on 08/07/2021, heavy losses caused by floods, which led to the cessation of citizens' movement for a few days, which made it difficult for residents to adapt to such Circumstances, despite the attempts made to reduce these risks: such as the ORSEC plan (Executive Decree N° 19-59 of 02/02/2019 (Official Journal of the Algerian Republic, 2019) and the General Prevention Plan (Law N° 04-20 of 25/12/2004(Official Journal of the Algerian Republic, 2004), they all failed in the face of the flood phenomenon that continues to threaten its stability. Which made this problem a fertile ground for conducting research on this city in order to understand the relationship between flood risks and urbanization by analyzing the change in land use due to urbanization and its impact on floods.
Despite the increasing frequency and severity of urban flooding globally, the relationship between urban expansion and flood disaster risk remains insufficiently examined in many developing regions, particularly in North Africa. In Tebessa City, Algeria, there is a notable lack of comprehensive studies that utilize geospatial technologies such as remote sensing and Geographic Information Systems (GIS) to assess this relationship. Existing research has largely focused on major urban centers or areas with extensive historical flood data, often excluding secondary cities like Tebessa (Dewan and Yamaguchi, 2009b; Douglas, Alam et al., 2008). This study addresses that gap by analyzing how urban expansion from 1990 to 2023 has influenced flood risk in Tebessa. Unregulated urban growth typically increases impervious surfaces, disrupts natural drainage, and encroaches on floodplains, thereby heightening vulnerability (Jha, Bloch et al., 2012). In rapidly urbanizing areas of the Global South, such dynamics are accelerated in the absence of integrated planning and are rarely subjected to spatial analysis (UN-HABITAT, 2016). By applying remote sensing and GIS, this research provides a spatially explicit understanding of land use and land cover (LULC) change and its implications for flood risk. It also contributes to broader efforts to assess hydrological hazards in semi-arid urban contexts increasingly impacted by climate change (IPCC, 2022). As the first study of its kind in Tebessa, it offers a replicable methodology and practical insights for urban planning, disaster risk reduction, and climate adaptation across similar data-scarce regions in North Africa.The methodology includes the use of Landsat images and change detection techniques, including image pre-processing, land use classification and change measurement. The resulting land use maps for the years 1990, 2001, 2012 and 2023 identify three main land use categories: urban area, flooded area and bare land. This study is organized into four sections: The first section is devoted to framing some theoretical elements related to change detection; The second section is devoted to the scope of the study and the methodology used; This is followed by the third section, in which the results obtained are presented and interpreted; Finally, the conclusion will close the study.
Change detection has become a tool for examining the impact of urbanization on flooding. It is a fundamental remote sensing technique that involves comparing an object or phenomenon across multiple time periods to determine changes in its condition (Singh, 1989) . This approach typically utilizes multi-temporal satellite imagery to detect biophysical transformations in land cover, serving as one of the primary applications of remote sensing technologies. Satellite-based sensors, particularly those on Earth-orbiting platforms, are well-suited for this task due to their consistent image quality and frequent data acquisition capabilities (Mölders, 2011). Change detection is useful in various contexts, including land use change analysis, damage assessment, disaster monitoring, and environmental change analysis (Nelson, 1983). The underlying principle is that variations in land cover lead to differences in radiance values that are significant compared to other brightness variations, such as atmospheric conditions, sun angle, and soil moisture (Attri, Chaudhry et al., 2015; Jensen and Cowen, 1999). Selecting appropriate data, like Landsat images from the same season, can mitigate these confounding effects (Singh, 1989).
Remote sensing also plays a crucial role in urban analysis, especially in understanding the impacts of urbanization on flood risk (Li, Sun et al., 2022). While urban growth in developing countries often improves living standards, it also contributes to significant environmental issues—chief among them being heightened flood risk due to land use transformation, environmental degradation, and encroachment upon natural waterways (Li, Sun et al., 2022; Thanh Son, Thi Thu Trang et al., 2022). Therefore, the integration of remote sensing and GIS allows researchers to study spatial and temporal changes in land use and perform digital analysis and processing, providing insights into the relationship of urbanization with environmental issues (Abdullahi and Pradhan, 2017; Li, Sun et al., 2022). GIS is also essential for mapping, modeling, and analyzing these changes (Atanga, Tankpa et al., 2023; Bhatta, 2010; Chomani, 2023). In the context of urban analysis and its impact on flood risk, several methods have been developed and used to pre-process, interpret, and extract data from remote sensing sources (Abdullahi and Pradhan, 2017; Bhatta, 2010; Chomani, 2023; Franci, Mandanici et al., 2015). Therefore, a number of methods have been proposed to detect land cover changes using digital data, which may assist in resource inventory updates. Principal component analysis, change vector analysis, image difference/ratio, vegetation index difference, and comparison of land cover classifications are some of these techniques (Singh, 1989) . The two main components of digital change detection methods are (1) the data transformation process (if any) and (2) the analytical methods used to identify areas of significant change. Furthermore, Nelson (Nelson, 1983) identified two basic methods for detecting changes: (1) comparing classifications that were independently generated at different dates, and (2) analyzing data across multiple time periods at the same time.
In brief, three main methods were adopted, which were collected from previous research and aligned with the aim of the study:
The quality of the results depends directly on the size of the study and the quality of the images (Atanga, Tankpa et al., 2023). Additionally, the choice of technique is influenced by the specific objectives of the study, the spatial and spectral resolution of the available data, the heterogeneity of the landscape, and the expertise of the analyst (Mas, 2000) ( See Figure 1).
The city of Tebessa is situated in eastern Algeria, within the Eastern Highlands region, strategically located approximately 39 km from the Tunisian border. It is intersected by several national roads (Figure 2):
Additionally, Tebessa is traversed by a railway line connecting it to Annaba and the Djbal Al-Onq phosphate mine in Bir El Ater, as well as another line leading to Tunisia via El-Kouif. The city is also served by a domestic airport situated in its northern vicinity (URBA-BA, 2018).
Tebessa city lies within the sub-basins of Wad El Kébir, which is fed by several wadis and chaabats (intermittent streams) flowing through the urban area. These include Wad Raffana, Wad Nagues, Wad Zaarour, Wad Segui, Wad El anba, Wad El Gnater Sous, and Wad Chabro (Department of Sanitation and Environmental Protection, 2014) (Figure 2).
The Wadis in the study area are prone to receiving significant sediment loads. The Quaternary deposits are characterized by pebbly, silty, encrusted formations with gentle slopes, while runoff occurs in impermeable black or green marls of the Cretaceous period (Department of Sanitation and Environmental Protection, 2014).
Tebessa is located at 8.11 degrees east longitude and 35.4 degrees north latitude, placing it within the warm temperate (Mediterranean) region with a continental climate (HADJLA, 2016). This city is recognized as the administrative center of a border state since the administrative reorganization of 1974. It spans an area of 184 square kilometers and serves as the principal city of a daira (district) comprising the Tebessa commune. The commune is situated in the northeastern part of the Tebessa state, bordered by Boulhaf-Dyr to the north, El-Kouif to the northeast, Hammamet to the northwest, El-Malabiod and Elogla El-Malha to the south, Bekkaria to the east, and Bir-Moqaddam to the west (URBA-BA, 2018).
Since Tebessa is characterized by a dense water network consisting primarily of Wadis that penetrate the city’s existing urban fabric, it faces major challenges in confronting shocks, harmful changes and major risks that affect the city’s security and sustainability (URBA-BA, 2018). According to the previous study (HADJLA, 2016), the risk of flooding is a recurring event in this city, which has drawn the attention of studies related to the urban area and has become problematic due to natural causes (such as climate changes that cause floods and human and material losses, in addition to the topographic and climatic characteristics that characterize the region, and since rainfall is characterized by irregularity at the spatial and temporal level in this region, it leads to irregular rainfall and sometimes in large quantities that lead to major disasters such as flood risks), and also human causes that in turn contributed to the exacerbation of this phenomenon (such as the rapid urbanization of the city, which was a response to the population increase, especially during the seventies, which represented the stage of demographic explosion, as the city's population increased from 62 639 to 200 256 people between 1977 and 2018. As for the urban fabric, its area increased to 4 843.65 hectares in 2018 after it was 1 637 hectares in 1988 (HADJLA, 2016; URBA-BA, 2018).
In an attempt to reduce the risks of floods, the competent authorities have made several attempts through:
1- The general plan for flood prevention in accordance with Law N° 04-20 of 13 Dhu al-Qi'dah 1425 corresponding to December 25, 2004 (Official Journal of the Algerian Republic, 2004), related to disaster prevention and management within the framework of sustainable development, which includes all the rules and procedures and aims to reduce exposure to the risk in question and prevent the effects resulting from the occurrence of this risk.
2- In addition to the emergency organization plan in accordance with Executive Decree N° 19-59 of 26 Jumada al-Awwal 1440 corresponding to February 2, 2019 (Official Journal of the Algerian Republic, 2019), which specifies the methods of preparing and managing organization plans through emergency preparedness to ensure that disaster response is not hindered by chaos or poor communication while maintaining calm and moving confidently through the wilderness of the crisis through an emergency operations plan to chart the best course of action during emergencies. Preventive measures for life safety also include the following: Evacuation, Shelter, Shelter in place, and Closure.
But despite all these attempts exploited by the Algerian government to reduce the problems of floods, the Civil Protection Directorate of Wilaya of Tebessa continues to record (Figure 3), year after year, a significant number of economic damages and human losses due to seasonal rains that cause recurring floods, according to the figure showing the statistics of the number of civil protection interventions against flood risks in this city.
This study aims to elucidate the spatial growth process in Tebessa City and its implications for flood risks from 1990 to 2023. Sequential Landsat multispectral images were acquired from the United States Geological Survey (USGS). These images were selected to ensure consistency in phenological and atmospheric conditions (Lu and Weng, 2007). Technical characteristics of the obtained images are detailed in Table 1.
| Image | Sensor | Date | Bands | Bands Used | Spatial resolution (m) |
|---|---|---|---|---|---|
| Image 01 | Landsat 4-5 TM C2 L1 | 29-03-1990 | 1-2-3-4-5-6-7 | 3-4-5-7 | 30 |
| Image 02 | Landsat 7 ETM + C2 L1 | 19-03-2001 | 1-2-3-4-5-6-7 | 3-4-5-6-7 | 30 |
| Image 03 | Landsat 7 ETM + C2 L1 | 13-01-2012 | 1-2-3-4-5-6-7-8-9-10-11 | 2-3-4-5-6-7-11 | 30 |
| Image 04 | Landsat 8-9 OLI/TIRS C2 L1 | 25-04-2023 | 1-2-3-4-5-6-7-8-9-10-11 | 3-4-5-6-7-11 | 30 |
Additional reference documents include urban development master plans from 1998 and 2012. Additionally, four satellite images (1990, 2001, 2012, and 2023) provided by USGS in natural color were utilized. The use of historical images facilitated the identification of areas beyond urban perimeters and not covered by urban development plans. Satellite image processing, including classification and post-classification, was conducted using ArcMap 10.8 software (Congedo, 2021).
MethodologyThe adopted methodology encompasses digital image pre-processing and processing. This involves the comparison of land use unit maps from 1990, 2001, 2012, and 2023 to better discern and extract land use classes from Landsat images utilizing the Supervised Classification method. The process was conducted in five stages (Figure 4):
i) Pre-processing of satellite images.
ii) Identification of land use units.
iii) Digital processing of Landsat images from 1990, 2001, 2012, and 2023.
iv) Execution and validation of supervised classification results using the maximum likelihood method.
v) Quantification of change.
This structured approach ensures a systematic analysis of land use dynamics over the specified period.
The pretreatment stage aims to mitigate differences arising from atmospheric conditions and sensor positioning inherent in raw or acquired satellite images. Initially, acquired images underwent geometric correction to facilitate their alignment. Georeferencing was performed image by image, utilizing the Landsat OLI/TIRS image as a reference due to its high quality.
Atmospheric correction was conducted using the "Apply FLAACH Setting" tool in ENVI 5.3 software. Additionally, radiometric correction was carried out using the "Radiometric Calibration" option within the same software. These procedures, encompassing radiometric and atmospheric corrections, yielded images with uniform radiometric information, devoid of noise (Figure 5).
Identification of Land-use classesThe landscape unit, or image facies, is defined as a collection of surfaces exhibiting common characteristics such as spectral, morphological, and textural properties on an image. The reflected radiation, known as the surface's spectral signature, varies across different wavelengths. Water bodies, bare soil, and various habitats exhibit distinct spectral signatures across different channels. Landsat TM, ETM, and OLI satellite images are characterized by 6, 7, and 11 bands, respectively, each capturing unique information based on differences in wavelengths. Through color composition, this information is synthesized and utilized to discriminate between different land use types. After several color compositions, the near-infrared (NIR), red, and blue bands (4-5-3) of the 1990, 2001, 2012, and 2023 images were selected for their optimal discrimination of land-use features (Figure 5).
Supervised pre-classification and selection of training sitesThe selection of training sites involves delineating parcels or portions representing all land cover types obtained after the 4-5-3 and 5-7-4 color compositions of LANDSAT images. Studies have shown that the color compositions of bands 4-5-3 and 5-7-4 offer the best discrimination of land cover types. Sites were chosen based on accessibility, and spectrally representative pixels were selected for each training site (Kouassi, 2014; Usselmann, 1999). Automatic extraction of pixel values within the defined polygons and calculation of their mean and standard deviation were performed to produce the spectral signature of each class from the selected bands of Landsat TM, ETM, and OLI images.
Supervised classification using the maximum likelihood methodGiven our comprehensive understanding of the study area, supervised classification was chosen. This method applies the same treatment to each pixel independently of neighboring pixels. The Maximum Likelihood algorithm was selected for the classification of bands 4-5-3 TM and ETM+ bands 5-7-4 OLI of the color composition. This technique automatically generates classification rules based on learning, requiring reference samples (training plots) for each class and a discriminant attribute space (Tormos, 2010).
The method calculates the probability of a pixel belonging to a given class and assigns the pixel to the class with the highest probability. If the probability does not reach the expected threshold, the pixel is classified as "unknown." The quality of the classification obtained was assessed using parameters calculated by the confusion matrix, including overall accuracy and the Kappa coefficient. Additional measures of classification reliability such as accuracy for the user, accuracy for the producer, errors of omission, and errors of commission were also evaluated (Congalton, 1991).
Post-processing:
Following image classification, the confusion matrix was executed to identify errors, assess separability between classes, and determine overall accuracy.
Vectorization and mapping:
The raster land-use map underwent conversion into vector data to facilitate management within GIS analysis software. Figure 4 presents a methodological synthesis outlining the approach adopted in our case study for mapping land use units from remote sensing data generated within a GIS environment.
Confusion matrix:
The confusion matrix serves to elucidate the various forms of conversion experienced by land-use units between two time points, t1 and t2, and to characterize the changes that occurred. It provides a concise representation of alterations in the state of elements within a system over a specified period (Bamba, Mama et al., 2008). Each cell of the matrix contains the value of a variable that transitioned from an initial class x to a final class y during the period from t1 to t2. In this study, the confusion matrix was derived from values obtained through the overlay of land-use maps in ArcGIS software (utilizing the "Intersect polygons" algorithm of the Geoprocessing extension) and processed in Excel.
Thematic maps corresponding to the years 1990, 2001, 2012, and 2023 were generated through image classification. The accuracy of the classification was assessed using overall accuracy and kappa values. Changes in land use and land cover in Tebessa City result from a variety of factors, including anthropogenic and natural influences. The evaluation results of the classification are summarized in Table 2.
| Confusion matrix | ||
|---|---|---|
| Image year | Kappa coefficient (Khat) | Overall accuracy (%) |
| 1990 | 0.9209 | 94.59% |
| 2001 | 0.8830 | 91.89% |
| 2012 | 0.9599 | 97.29% |
| 2023 | 0.8458 | 89.18% |
Confusion matrices were calculated for the four maps, demonstrating acceptable levels of accuracy. The overall accuracies were found to be 94.59%, 91.89%, 97.29%, and 89.18% for the years 1990, 2001, 2012, and 2023, respectively. Additionally, the Kappa coefficients were calculated, with measured values of 0.9209, 0.8830, 0.9599, and 0.8458 for the respective years (Branger, 2009) .
These results indicate a high level of reliability in the classification process, providing confidence in the accuracy of the thematic maps generated for each period.
Built-up change mappingThe maps displayed in Figure 6 depict the outcomes of supervised classification utilizing the maximum likelihood method on Landsat sensor images from 1990, 2001, 2012, and 2023.
An initial cartographic analysis of the results, as illustrated in Figure 8, reveals a pronounced increase in the building class alongside a notable decrease in the bare land class. The expansion of urbanized areas has occurred in virtually all directions during the period spanning from 1990 to 2023. Consequently, there has been a significant decline in natural vegetation in favor of man-made structures. This trend can be attributed to the persistent pressures exerted on these formations.
Between 1990 and 2001, the spatial expansion of the urban fabric exhibited a consistent pattern. Two primary directions guided this spatial evolution (refer to Figure 6 and Figure 7): concentrically radiating around Tebessa's historic center and linearly extending westward along RN 10 and northward along RN 16.
Throughout the period from 2001 to 2012, the spatial growth of the urban area witnessed multiple extensions, characterized by continuous development particularly toward the southwest (leading to the expansion of Skanska, 600, and Djbal-Anoual districts), northwest (with the enlargement of Fatma-Zohra district), and northward (expansion of El-Djorf and El-Mizeb districts).
In the most recent period (2012-2023), urban expansion primarily occurred away from the historic center, resulting in the establishment of new urban hubs (Land use Plan N° 9A and Land use Plan N°28) following the revision of the Tebessa- Hammamet- Elkouif- Bekkaria- Boulhafdyr Intercommunal Master Plan for Urban Development (URBA-BA, 2018).
The effect of urbanization on flooding Relationship between land use and floodingTo identify areas prone to floods or flooded areas, urban planning instruments such as the master plan for urban development of Tebessa city and its land occupation plans (LUPs) were utilized, along with records of past flood events reported by the city’s civil protection, and aided by geographic information systems (GIS). Figure 8 illustrates the spatial distribution of floods and the frequency of events based on the urban perimeter of the study area.
Between 1990 and 2023, out of 39 LUPs in Tebessa, 29 were affected by flooding, according to reports from the Civil Protection and Hydraulic Direction. Seven LUPs experienced 1 to 5 floods, while 8 LUPs were affected by more than 5 floods, with 14 experiencing 10 or more floods.
The city's urban fabric is situated on a dense hydrographic network, as depicted in Figure 8, which is a significant factor contributing to the frequent flooding in this region (TALBI, GHERZOULI et al., 2023). Some events, notably those in August, September, and October 2015, and May, August, September, and October 2018 (Department of Sanitation and Environmental Protection, 2014), resulted in intense flooding and widespread geographical impact.
The maps in Figure 9 display the spatiotemporal distribution of floods from 1990 to 2023 based on the land-use plans of the Tebessa urban development master plan.
The number of flooded LUPs increased from 10 between 1990 and 2001 to 17 between 2001 and 2012, and then to 20 after 2015, while the total number of LUPs nearly tripled from 10 in 1990 to 29 in 2023 (Table 3 and Figure 10).
During the 1990-2001 period, flooding was primarily concentrated in the historic city center and outlying districts (LUPs N° 01, 02, 03, 12, 13, 14, 15, 16, 18, and 17), largely comprising densely populated areas. Excessive urban densification in central districts, where flooding is frequent, led to settlement in water drainage areas.
Between 2001 and 2012, with the emergence of new urban expansion in Tebessa, the areas prone to flooding gradually expanded, encompassing 17 LUPs such as LUPs N° 04, 05, 07, 9, 11, 22, and 26.
From 2012 to 2023, the urban perimeter of the city expanded notably, with the introduction of new ministerial housing programs in new areas (LUP N° 28 and LUP N° 9A), exacerbating the flood risk situation. This expansion led to flooding affecting additional LUPs, including LUPs N° 08, 10, 18A, 19, 20, 21, 23, 28, and 30.
| Designation | Zone | Total area (ha) | Easement area (ha) | Net area (ha) | |||
|---|---|---|---|---|---|---|---|
| Urbanized area | U.A | 2629.41 | 928.14 | / | |||
| Development area | D.A.1 | 578.16 | 1680.42 | 116.03 | 145.19 | 462.13 | 1086.56 |
| D.A.2 | 148.51 | 0 | 148.51 | ||||
| D.A.3 | 390.24 | 0 | 390.24 | ||||
| D.A.4 | 297.39 | 40.18 | 257.21 | ||||
| D.A.5 | 266.12 | 13.94 | 252.18 | ||||
| Future urbanization area | F.U.A.1 | 434.91 | 38 | 396.91 | |||
| F.U.A.2 | 98.89 | 33 | 65.89 | ||||
| Non-developable area | N.D.A | 1973.07 | |||||
| Urban perimeter area | 4843.65 | ||||||
After classification, multi-buffer rings were created for each 1 km distance from 1 to 16 km from the center of Tebessa city outwards. The primary objective of applying the multi-buffer ring method was to determine spatial and temporal relationships.
To provide a comprehensive overview of the changes occurring between 1990 and 2023, the rates of change for the various land-use units were calculated and summarized in Table 4 and Figure 12.
1990 to 2001: There was an increase in the Urbanized area and Flooded area by 0.85% and 20.10%, respectively, along with a regression in the Bare land by -22.27%.
2001 to 2012: During this period, the Urbanized area and Flooded area increased by 4.83% and 13.36%, respectively, while the Bare land decreased by -9.28%.
2012 to 2023: Similar trends persisted, with an increase in the Urbanized area and Flooded area by 1.80% and 5.92%, respectively, and a regression in the Bare land by -10.50%.
| Classes | Area (%) | Annual change (%) | ||||||
|---|---|---|---|---|---|---|---|---|
| 1990 | 2001 | 2012 | 2023 | 1990-2001 | 2001-2012 | 2012-2023 | 1990-2023 | |
| Urbanized area | 6.63 | 7.48 | 12.30 | 14.12 | 0.85 | 4.83 | 1.80 | 7.49 |
| Flooded area | 28.56 | 48.67 | 62.03 | 67.96 | 20.10 | 13.36 | 5.92 | 39.39 |
| Bare land | 54.86 | 32.58 | 23.29 | 12.79 | -22.27 | -9.28 | -10.50 | -42.06 |
Figure 11 shows that
In 1990, the bare land had the largest surface area, covering 54.86 %, followed by flood-prone areas with 28.56 %, and urbanized areas with only 6.63%.
By 2001, the flooded area and urbanized area expanded, reaching 48.67 % and 7.48 %, respectively, while the bare land decreased to 32.85 %.
In 2012, both flooded areas and urbanized areas continued to expand, reaching 62.03 % and 12.30 %, respectively, while the bare land further reduced to 23.29 %.
Finally, in 2023, the flooded area reached its peak during the study period, covering 67.96 %. The urbanized area expanded to 14.12%, while the bare land decreased to 12.79 %, indicating a significant transformation of land use over time.
Figure 11 illustrates the relationship between urban area and flood area in 1990, 2001, 2012, and 2023. It is evident that as the urban expansion in the study area increases, so does the area prone to flooding. This observation is consistent with the empirical data and statistics provided by both the Directorate of Civil Protection and the Directorate of Reconstruction, Architecture, and Construction. Whenever the urban fabric of the city expands through urban planning initiatives, there is a noticeable rise in the frequency of civil protection interventions, as well as an increase in human and material losses during flood events.
This correlation underscores the significant impact of urbanization on flood risk within the study area. As urban areas expand, they often encroach upon natural drainage systems and alter the hydrological dynamics of the region, leading to increased vulnerability to flooding. Understanding this relationship is crucial for effective urban planning and flood risk management strategies, which should aim to balance urban development with the preservation of natural floodplains and the implementation of resilient infrastructure measures.
Specifically, the analysis indicates that:
Bare land has experienced a substantial decline, decreasing by 47% over its surface area. This decline suggests a significant conversion of bare land into other land use types, likely including urbanized areas or flooded regions.
In contrast, the surface areas occupied by buildings and flooded areas have shown considerable increases, collectively rising by 53%. This trend reflects the expansion of urbanized areas and the proliferation of flood-prone regions within the study area (Figure 13).
Overall, the continuous increase in the surface area of buildings underscores the pressing need for policymakers and decision-makers to address the seriousness of the situation. The expanding urban footprint poses various challenges, including increased vulnerability to flooding, strain on infrastructure, and environmental degradation. Therefore, proactive measures are essential to mitigate the adverse impacts of urbanization, such as implementing effective land use planning strategies, promoting sustainable development practices, and enhancing resilience to natural hazards.
This analysis underscores the importance of informed decision-making and proactive intervention to manage urban growth effectively and safeguard the long-term sustainability of the study area.
This study aimed to analyse the relationship between flood risks and urbanization in Tebessa city, Algeria, by examining land use changes due to urbanization and their impact on floods over a 33-year period (1990-2023). The results provide valuable insights into the complex interplay between urban expansion, land use transformation, and flood vulnerability in a rapidly growing medium-sized Algerian city.
Land Use Change Dynamics:
Our analysis revealed two contrasting spatial and temporal trends: a progressive increase in urban areas (47%) and flooded areas (39.39%), accompanied by a regressive trend in bare land (-42.06%). These findings align with global urbanization patterns observed in developing countries, where rapid urban growth often occurs at the expense of natural landscapes (Seto, Fragkias et al., 2011). The significant reduction in bare land is particularly concerning, as it suggests a loss of permeable surfaces that could naturally mitigate flood risks.
The expansion of urban areas in Tebessa follows patterns similar to those observed in other medium-sized cities in developing countries. For instance, Haregeweyn, Poesen et al. (2013) reported comparable urban growth rates in Bahir Dar, Ethiopia, where built-up areas increased by 31% between 1957 and 2009. However, the rate of urban expansion in Tebessa (47% over 33 years) appears to be more rapid, highlighting the intense urbanization pressure faced by this border city.
Urbanization and Flood Risk:
The parallel increase in urban areas and flooded areas (47% and 39.39%, respectively) suggests a strong correlation between urbanization and flood vulnerability. This relationship has been observed in numerous studies worldwide. For example, (Du, Van Rompaey et al., 2015) found that rapid urbanization in Shenzhen, China, led to a 22.3% increase in flood-prone areas over a 30-year period. Our findings in Tebessa show an even more pronounced increase in flood-prone areas, possibly due to the city's unique topographical and hydrological characteristics.
The spatial distribution of floods within Tebessa's urban perimeter provides further insights into the urbanization-flood risk nexus. Out of 39 Land Use Plans (LUPs) in Tebessa, 29 were affected by flooding, with 14 experiencing 10 or more flood events. This widespread impact suggests that flood risk is not confined to specific areas but is a city-wide challenge. Similar patterns have been observed in other rapidly urbanizing cities in developing countries. For instance, (Jiang, Zevenbergen et al., 2018) reported that urbanization in Guangzhou, China, led to an increase in flood-prone areas across multiple districts, emphasizing the need for comprehensive flood management strategies.
Temporal Evolution of Flood Risk:
The temporal analysis of flood-affected LUPs reveals a progressive increase in the number of flood-prone areas from 1990 to 2023. This trend aligns with findings from other longitudinal studies on urbanization and flood risk. For example, (Ogato, Bantider et al., 2020) observed a similar pattern in Dire Dawa city, Ethiopia, where flood-prone areas expanded in tandem with urban growth between 1985 and 2015.The concentration of flooding in the historic city centre and outlying districts during the 1990-2001 period, followed by the expansion to new urban areas in subsequent years, highlights the evolving nature of flood risk in Tebessa. This pattern suggests that while initial urban development may have exacerbated flood risks in established areas, continued expansion has created new vulnerabilities in previously less affected zones. This finding underscores the importance of integrating flood risk assessments into urban planning processes, as emphasized by (Bloch, Jha et al., 2012) in their global review of urban flood risk management practices.
Urban Density and Flood Vulnerability:
Our analysis indicates a complex relationship between urban density and flood vulnerability. The excessive urban densification in central districts, where flooding is frequent, has led to settlement in water drainage areas. This observation aligns with studies from other contexts, such as (Brody, Gunn et al., 2011), who found that high-intensity urban development in Texas, USA, was associated with increased flood damage.
However, the relationship between density and flood risk is not straightforward. Some studies, such as (Zhang, Villarini et al., 2018), suggest that higher urban densities can lead to more efficient land use and potentially reduce overall flood risk at the city scale. The Tebessa case study highlights the need for context-specific assessments of how urban form and density interact with local hydrological conditions to influence flood vulnerability.
Implications for Urban Planning and Flood Risk Management:
The findings of this study have significant implications for urban planning and flood risk management in Tebessa and similar rapidly growing cities:
Integration of flood risk in urban planning: The strong correlation between urban expansion and increased flood-prone areas underscores the need to integrate flood risk assessments into urban planning processes. This aligns with recommendations from global best practices, such as those outlined by (Bloch, Jha et al., 2012) in their World Bank report on urban flood risk management.
Preservation of natural drainage systems: The significant loss of bare land (-42.06%) suggests a reduction in natural flood mitigation capacity. Urban planners should prioritize the preservation and restoration of natural drainage systems, as advocated by (Soz, Kryspin-Watson et al., 2016) in their study on integrated urban flood risk management.
Adaptive urban design: The varying flood vulnerability across different LUPs indicates the need for adaptive urban design approaches that consider local topographical and hydrological conditions. This echoes recommendations by (Soz, Kryspin-Watson et al., 2016) on integrating resilience thinking into urban flood management.
Multi-temporal analysis for risk assessment: The study demonstrates the value of multi-temporal analysis in understanding the evolving nature of flood risk. This approach should be incorporated into regular urban monitoring and evaluation processes, as suggested by (Dewan and Yamaguchi, 2009a) in their study on land use change and flood risk in Greater Dhaka.
This study demonstrates the significant impact of rapid urbanization on flood risk in Tebessa city. By highlighting the spatial and temporal dynamics of land use change and its relationship to flood vulnerability, it provides a foundation for more informed urban planning and flood risk management strategies. These findings underscore the urgent need for integrated approaches that balance urban development with flood resilience, not only in Tebessa but in rapidly growing cities across Algeria and beyond.
In conclusion, the study highlights significant transformations in land use patterns within the city of Tebessa from 1990 to 2023, driven primarily by urbanization dynamics and associated demographic pressures. The adoption of supervised classification methods facilitated the accurate delineation and analysis of land use units, revealing substantial shifts in urban morphology and landscape composition over the study period.
The findings underscore the progressive disappearance of bare land in favor of urbanized areas, accompanied by a notable expansion of flood-prone zones across Tebessa's urban perimeter. This trend reflects the intensifying interface between urban development and hydrological processes, exacerbated by the absence of vegetative cover within the city's boundaries. The depletion of vegetation diminishes natural flood mitigation capacities, exacerbating flood risks and amplifying the vulnerability of urban populations to inundation events.
The study underscores the urgent need for proactive land management strategies and targeted interventions to reduce flood risks and enhance urban resilience. This is achieved through a set of key recommendations that can be summarized at two main levels:
1. Local-Level Policy Recommendations: The Case of Tebessa
Risk-Averse Urban Planning and Land Regulation:
To enhance flood resilience and sustainable urban development, it is essential to strengthen and enforce existing planning tools, such as the Urban Development Master Plan and the Land Use Plan, to prevent urban expansion into floodplains and wadi corridors. Informal settlements built within or along wadis should be removed, and any alterations to the natural courses of these water channels—such as culverting or covering—must be strictly prohibited. Additionally, the establishment of green buffer zones along wadis and investment in ecosystem-based flood management strategies, like vegetation restoration, can serve as effective measures to mitigate flood risks while supporting environmental sustainability.
Flood Preparedness through Structural and Behavioral Adaptation
To reduce vulnerability in flood-prone areas, it is important to promote adaptive building designs, such as elevating ground floors or designating them for non-residential uses like storage or parking. Building community resilience should also be a priority through public awareness campaigns and training programs that prepare residents for potential flood events. Furthermore, institutionalizing the use of remote sensing and GIS-generated flood risk maps can greatly enhance decision-making for housing development, infrastructure projects, and urban expansion, ensuring that growth is guided by accurate, up-to-date risk assessments.
Institutional Strengthening for Water Management
Effective flood risk governance necessitates the establishment of a specialized regional flood risk authority with legal and financial autonomy. This body should be tasked with overseeing hydrological risk zones and coordinating closely with urban planning institutions. Such an authority would enhance institutional capacity and accountability, ensuring a more integrated and strategic approach to water and flood risk management at the regional level.
2. General level Policy Recommendations: for Broader Application
Mainstream Flood Risk in Urban Planning Frameworks
Urban planning policies should incorporate hydrological risk assessments, supported by remote sensing and GIS technologies, to inform land use zoning and infrastructure development decisions. These tools enable planners to identify vulnerable areas and make evidence-based decisions that reduce exposure to flood hazards. In flood-prone cities such as Tebessa, the application of these technologies can be instrumental in steering future urban expansion away from high-risk floodplains, thereby enhancing long-term urban resilience and minimizing potential damage from extreme weather events.
Foster a Culture of Living with Water
It is important to acknowledge that completely eliminating flood risk is unrealistic; therefore, emphasis should be placed on promoting behavioral adaptation, participatory planning, and active stakeholder engagement. In cities like Tebessa, residents can play a crucial role in risk reduction by modifying building designs and adhering to zoning regulations that are informed by flood risk maps. These community-driven measures, when supported by transparent planning processes and accessible risk information, can significantly reduce both individual and collective vulnerability to flooding.
Institutionalize Flood Risk Mapping and Communication
Governments and municipalities should mandate the regular production and public dissemination of high-resolution flood risk maps as a foundational tool for effective flood management. These maps should serve multiple critical functions, including guiding insurance pricing, setting infrastructure resilience standards, informing public awareness campaigns, and supporting emergency response planning. By institutionalizing their use across sectors, authorities can ensure that flood risk data is consistently integrated into both short-term preparedness efforts and long-term urban development strategies.
In summary, the findings of this study provide valuable insights into the complex interplay between land use dynamics, urbanization, and flood risk within the city of Tebessa. By addressing these interconnected challenges through holistic and participatory approaches, policymakers can foster more resilient and sustainable urban development pathways, ensuring the well-being and safety of present and future generations in Tebessa and beyond.
This study can also serve as a basis for a future study focused on finding practical solutions to improve urban resilience against flood risks by simulating urban design parameters for Tebessa city.
S.T, L.G and S.F wrote the mains manuscript text, and T.S prepared figures 1-12, tables 1-4. This work is original and has been carried out by the authors, all authors have contributed, all authors agree with the text and its submission, and No part has been published elsewhere unless acknowledged in the text. The manuscript has not been submitted to another journal.
The authors declare that they have no conflicts of interest regarding the publication of the paper.
The authors would like to acknowledge the help of the Directorate of urbanism, architecture and construction (DUAC), and Civil Protection and the Directorate of Water Resources of the Wilaya of Tebessa for their help in providing documents and statistics.
