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

Cloud-based Earth observation platforms, such as data cubes, enable reproducible analyses of long-term satellite time series for climate and urban studies. In parallel, Essential Climate Variables (ECVs) provide a standardised framework for monitoring climate dynamics, with urban land cover and temperature being particularly relevant in historic urban contexts. This study analyses long-term trends and statistical associations between satellite-based ECVs and urbanisation indicators within the Historic Urban Landscape (HUL) of Sfax (Tunisia) from 1985 to 2021. Using the Digital Earth Africa (DEA) data cube, we derived six urban spectral indices (USIs), land surface temperature, air temperature at 2 m, wind characteristics, and precipitation from Landsat and ERA5 reanalysis data. An automated and reproducible Python-based workflow was implemented to assess USI behaviour, evaluate their performance against the Global Human Settlement Layer (GHSL), and explore spatio-temporal co-variations between urbanisation and climate variables. Results reveal a consistent increase in air and surface temperatures alongside a decreasing precipitation trend over the study period. The USIs demonstrate comparable accuracy levels (≈88–90%) in delineating urban areas, with indices based on SWIR and NIR bands (NDBI, BUI, NBI) showing the strongest statistical associations with temperature variables. Correlation and multivariate regression analyses indicate that temporal variations in USIs are more strongly associated with air temperature than with land surface temperature; however, these relationships reflect statistical co-variation rather than causality. By integrating satellite-based ECVs within a data cube framework, this study provides an operational methodology for long-term monitoring of urban-climate interactions in historic Mediterranean cities, supporting both climate adaptation strategies and the objectives of the UNESCO HUL approach.

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Journal
Remote Sensing
Published
2026-01-21
DOI
https://doi.org/10.3390/rs18020364
Primary Topic
Urban Heat Island Mitigation
Type
article
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article

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

Paul Passy, Syrine Souissi, Marianne Cohen, Faiza Allouche Khebour
Remote Sensing
Urban Heat Island Mitigation
article

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

Paul Passy, Syrine Souissi, Marianne Cohen, Faiza Allouche Khebour
article en

Abstract

Cloud-based Earth observation platforms, such as data cubes, enable reproducible analyses of long-term satellite time series for climate and urban studies. In parallel, Essential Climate Variables (ECVs) provide a standardised framework for monitoring climate dynamics, with urban land cover and temperature being particularly relevant in historic urban contexts. This study analyses long-term trends and statistical associations between satellite-based ECVs and urbanisation indicators within the Historic Urban Landscape (HUL) of Sfax (Tunisia) from 1985 to 2021. Using the Digital Earth Africa (DEA) data cube, we derived six urban spectral indices (USIs), land surface temperature, air temperature at 2 m, wind characteristics, and precipitation from Landsat and ERA5 reanalysis data. An automated and reproducible Python-based workflow was implemented to assess USI behaviour, evaluate their performance against the Global Human Settlement Layer (GHSL), and explore spatio-temporal co-variations between urbanisation and climate variables. Results reveal a consistent increase in air and surface temperatures alongside a decreasing precipitation trend over the study period. The USIs demonstrate comparable accuracy levels (≈88–90%) in delineating urban areas, with indices based on SWIR and NIR bands (NDBI, BUI, NBI) showing the strongest statistical associations with temperature variables. Correlation and multivariate regression analyses indicate that temporal variations in USIs are more strongly associated with air temperature than with land surface temperature; however, these relationships reflect statistical co-variation rather than causality. By integrating satellite-based ECVs within a data cube framework, this study provides an operational methodology for long-term monitoring of urban-climate interactions in historic Mediterranean cities, supporting both climate adaptation strategies and the objectives of the UNESCO HUL approach.

Remote SensingVol. 18(2)
Université Sorbonne Nouvelle (FR), Université Paris Cité (FR), Sorbonne Université (FR), Sorbonne Paris Cité (FR), Université Paris 1 Panthéon-Sorbonne (FR), University of Sousse (TN)
Sustainable cities and communities, Climate action
Openalex Percentile: Top 84%
Urban Heat Island Mitigation
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