Spotlight: Syrine Souissi on using satellite data to protect Sfax’s heritage

Sfax, Tunisia, tells two different stories of urban change, the expansion of its port and the Taparura development area, and the relative stability of its historic Medina. Syrine Souissi, a geospatial data engineer and PhD researcher jointly affiliated with Sorbonne University and the University of Sousse, investigated these contrasting patterns in her hometown over 36 years. Using Landsat time series, climate reanalysis data and six urban spectral indices through the Digital Earth Africa Data Cube, her research shows how Earth observation can help distinguish urban expansion from change within historic urban landscapes, providing valuable evidence for sustainable urban planning and cultural heritage management.

Could you tell us about your academic background and research focus, and what drew you personally to studying Sfax’s historic urban core?

I am a geospatial data engineer and PhD researcher in Geography, Landscape and Territorial Development, jointly affiliated with Sorbonne University in France and the University of Sousse in Tunisia. My research focuses on cultural landscapes, heritage preservation and the use of geospatial technologies, particularly remote sensing and GIS, to support sustainable landscape management.

My interest in Sfax’s historic urban core is both academic and personal. As someone originally from Sfax, I have a strong connection to the city’s cultural identity and architectural heritage. The coexistence of the traditional Medina and the European-era urban fabric makes Sfax a particularly interesting case for investigating urban transformation and heritage preservation. Through my research, I aim to demonstrate how Earth observation can help us understand these changes and support the sustainable management of historic urban landscapes.

How did you first encounter Digital Earth Africa, and why was it a good fit for this research?

I was introduced to Digital Earth Africa by Paul Passy, co-director of Géotéca and a co-author of the study. With a background in Python programming, time-series analysis and previous experience working with geospatial data cubes and cloud computing, I was already familiar with the potential of these technologies for Earth observation research. Digital Earth Africa was a natural choice because it provides access to analysis-ready satellite data and cloud-based processing tools covering the African continent. As my research focuses on study areas in Tunisia, the platform offered an opportunity to apply my technical skills to investigate long-term urban transformation while benefiting from the accessibility and computational capabilities of a continental-scale data cube.

Your study brought together researchers and institutions in Tunisia and France. How did the collaboration take shape, and what role did Digital Earth Africa play?

The collaboration developed through my jointly supervised PhD between Sorbonne University in France and the University of Sousse in Tunisia, within the Partenariat Hubert Curien Utique project, a bilateral Franco-Tunisian research initiative. The main objective was to explore how emerging Earth observation technologies could be used to study cultural landscapes and heritage assets in Sfax, a historic Mediterranean and African city.

The collaboration brought together complementary expertise in geography, cultural heritage, remote sensing and geospatial technologies. Digital Earth Africa supported this shared research framework by providing access to analysis-ready satellite imagery and cloud-based processing capabilities, helping us investigate urban transformation across Sfax’s historic urban landscape.

What was the main goal of the study, and why was it important to track urban growth and environmental conditions over 36 years?

Our main goal was to understand how urban growth and environmental conditions in Sfax evolved between 1985 and 2021, with particular attention to its Historic Urban Landscape (HUL). By combining satellite imagery, spectral indices and essential climate variables, we aimed to identify patterns of urban expansion and explore their relationship with environmental change.

We also compared the performance of different spectral indices in detecting and monitoring built-up areas, particularly within the complex urban fabric of Sfax’s historic core. This helped us assess which indices were most suitable for studying urban transformation in a heritage context.

Tracking these changes over 36 years provides valuable insight into the city’s long-term evolution and can support more informed decisions on sustainable urban planning and cultural heritage preservation.

Which Digital Earth Africa datasets and tools were most important to your analysis, and how did the Data Cube support your workflow?

The most important datasets were Landsat Collection 2 Level 2 products, including Surface Reflectance and Land Surface Temperature, and ERA5 reanalysis data, which provided air temperature, precipitation and wind variables. Together, these datasets allowed us to investigate urban and climate dynamics in Sfax from 1985 to 2021.

We used several Digital Earth Africa functions, including load_ard, geomedian_with_mads and calculate_spectral_indices, alongside the Water Observations from Space product for water masking. The platform’s JupyterLab environment, supported by Dask parallel processing, helped us develop automated Python workflows to analyse large volumes of Earth observation data.

The platform also allowed us to integrate external geospatial products, particularly the Global Human Settlement Layer (GHSL), into the same analytical environment. This enabled us to combine different data sources and evaluate six urban spectral indices for detecting built-up areas, including within Sfax’s complex historic urban fabric.

Overall, the Digital Earth Africa Data Cube reduced data preparation and processing effort while providing a flexible, scalable and reproducible environment for a 36-year analysis of urban and climate dynamics.

What did comparing six urban spectral indices reveal, particularly about change in Sfax’s historic core?

Digital Earth Africa enabled us to calculate and compare six urban spectral indices using consistent Landsat time-series data over 36 years. This provided a common framework for assessing how well the indices detected built-up areas. By integrating external datasets such as the Global Human Settlement Layer, we could also evaluate their performance within Sfax’s complex urban fabric.

The indices did not perform equally, particularly in the Historic Urban Landscape, where the dense and heterogeneous built environment makes it difficult to distinguish features spectrally. The comparison highlighted the importance of selecting indices according to the characteristics of the urban landscape rather than relying on a single indicator.

Another important finding was the contrast between substantial urban expansion around the wider city—particularly near the port and the Taparura development area—and the relatively limited spatial change within the historic core. This suggests that, despite major transformations in the surrounding areas, Sfax’s historic urban fabric remained comparatively stable in spatial extent over the study period.

Why does long-term monitoring matter for Sfax and for other historic African cities facing similar pressures?

Long-term Earth observation monitoring is essential for understanding how historic cities evolve under the combined pressures of urban expansion, climate change and environmental transformation. In Sfax, analysing 36 years of satellite observations allowed us to distinguish the relatively stable historic urban core from the more dynamic changes taking place around it. This long-term perspective provides scientific evidence that can support urban planning, heritage preservation and sustainable development.

Beyond Sfax, many historic African cities face similar challenges, often with limited access to consistent historical environmental and urban data. Platforms such as Digital Earth Africa can help address this gap by making Earth observation data and advanced analytical tools more accessible to researchers and decision-makers across the continent.

One promising direction is to strengthen the connection between Earth observation and cultural heritage research. By combining satellite time series, geospatial analytics and local knowledge, we can develop more comprehensive approaches to monitoring historic urban landscapes. This interdisciplinary perspective has significant potential to support more resilient and sustainable African cities and demonstrate the wider value of Earth observation for heritage management.

From your experience, what are the main challenges in using Earth observation for urban and climate research in Africa, and how could platforms like Digital Earth Africa help?

One of the main challenges is translating Earth observation data into reliable indicators of urban and environmental change, particularly in complex urban landscapes. Our study of Sfax showed that the performance of urban spectral indices varies with the characteristics of the built environment, highlighting the need for locally adapted and validated methods.

Another challenge is integrating different datasets—including satellite time series, climate reanalysis products and external geospatial data—while maintaining consistency and reproducibility. Digital Earth Africa helps address these challenges through analysis-ready datasets, cloud-computing capabilities and flexible Python-based workflows.

Looking ahead, there is significant potential to develop more Real World Examples based on scientifically robust and validated methods, integrate higher-resolution observations and field data, and expand Earth observation applications to cultural heritage monitoring. These developments could strengthen the connection between scientific research and practical decision-making across Africa.

If you could request one new feature or improvement from Digital Earth Africa to support your future research, what would it be?

I would like to see Digital Earth Africa develop a dedicated Real World Example for monitoring cultural and historic urban landscapes, integrating satellite time series, climate indicators and heritage-related geospatial data. Supported by scientifically validated methods, such a workflow could give researchers and heritage managers adaptable tools to assess environmental pressures and urban transformation. It could also create new opportunities to apply Earth observation to cultural heritage preservation across Africa.

What advice would you give a young African researcher who wants to use Digital Earth Africa data to study urban growth and climate change in their own city?

My advice is to start with a clear research question rooted in the specific challenges of your city, rather than focusing on the technology itself. Digital Earth Africa provides an environment for exploring satellite time series, climate data and geospatial analysis through its open-access datasets and Real World Examples.

I would encourage young researchers to build their Python and remote sensing skills, critically evaluate the methods they use, and complement satellite observations with local knowledge and field data whenever possible. Most importantly, do not hesitate to adapt existing workflows, experiment with new approaches and contribute your findings and methods to the wider African Earth observation community. Africa offers tremendous opportunities for innovative, locally driven research with meaningful societal impact.

Read the study: Souissi, S., Cohen, M., Passy, P. & Allouche Khebour, F. (2026). Assessing Trends and Interactions of Essential Climate Variables in the Historic Urban Landscape of Sfax (Tunisia) from 1985 to 2021 Using the Digital Earth Africa Data Cube. Remote Sensing, 18(2), 364. https://doi.org/10.3390/rs18020364