In this paper we explore the potential of Digital Earth Africa (DE Africa) coastlines products for the calculation of one of the Erosion Warning Indicator Namely Long-Term shoreline trend indicator. The parameter is calculated and estimated based on the relationship between the cross-shore annual shoreline positions and the annual observation. DE Africa provide information related on the coastal dynamics for the period of 23 years. Here, we analyse the Digital Earth Africa (DE Africa) coastlines products V0.4.2 by performing the regression modelling to calculate the long-term shoreline trend indicator. The methodological approach proposed allowed to extract the long-term trend of shoreline changes at continental, national and local scales. The results indicated that the Africa’s coastline have been both retreating and advancing. Such processes impacted the African population of about 709775 living within 1 km of the shoreline and low-lying flat areas.

Africa’s Coastline Long-Term Monitoring Using Remote Sensing and GIS Techniques

Anselme Muzirafuti
2025-01-01

Abstract

In this paper we explore the potential of Digital Earth Africa (DE Africa) coastlines products for the calculation of one of the Erosion Warning Indicator Namely Long-Term shoreline trend indicator. The parameter is calculated and estimated based on the relationship between the cross-shore annual shoreline positions and the annual observation. DE Africa provide information related on the coastal dynamics for the period of 23 years. Here, we analyse the Digital Earth Africa (DE Africa) coastlines products V0.4.2 by performing the regression modelling to calculate the long-term shoreline trend indicator. The methodological approach proposed allowed to extract the long-term trend of shoreline changes at continental, national and local scales. The results indicated that the Africa’s coastline have been both retreating and advancing. Such processes impacted the African population of about 709775 living within 1 km of the shoreline and low-lying flat areas.
2025
979-8-3315-7482-6
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11570/3341652
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