Contribution to study the state of vegetation cover of some forests in the region of Djelfa with vegetation index by using GEE

TAMRI, Nouar

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Contribution to study the state of vegetation cover of some forests in the region of Djelfa with vegetation index by using GEE

TAMRI, Nouar

المكان (URI): http://dspace.univ-djelfa.dz:8080/xmlui/handle/112/7994

التاريخ: 2025

الخلاصة:

Contribution to study the state of vegetation cover of some forests in the region of Djelfa with vegetation index and using GEE. This work studies the state of the vegetation cover of the Senalba forest massif, located in the Djelfa region. The main objective was to assess and analyze its cover over a specific period (2015– 2025), by utilizing satellite data available on the Google Earth Engine (GEE) platform and applying the NDVI and SAVI vegetation indices. The results highlight a significant variability in vegetation cover density, influenced by both ecological factors and persistent anthropogenic pressures. Some areas show signs of regeneration, while others reveal concerning degradation that could compromise the ecological balance and the sustainability of forest resources. The comparative analysis of NDVI and SAVI confirmed the importance of combining these two indices in semi-arid ecosystems to obtain a more reliable assessment of vegetation cover, particularly in areas where bare soil is highly exposed.

الوصف:

This study focuses on the state of the vegetation cover of a forest massif of great importance in the Djelfa region. Its overall objective was to assess and analyze vegetation dynamics in the Senalba Chergui and Senalba Gharbi forests that make up this massif over a specific period. The use of satellite data via the GEE platform and the application of vegetation indices such as NDVI and SAVI provided quantitative and spatial information on the evolution of the vegetation cover in this region. The results highlighted a spatio-temporal variability in vegetation cover density, reflecting the combined influence of several ecological factors, more precisely bark beetle infestations observed in recent years, and anthropogenic pressures. Some areas showed a notable improvement in vegetation, while others revealed degradation that could compromise the ecological balance and the sustainability of forest resources. The spatio-temporal analysis of NDVI and SAVI values between 2015 and 2025 provides valuable information on the ecological dynamics of the Senalba forest massif. A general decline in both indices across several classes reflects a progressive reduction in vegetation cover density, which can be interpreted as a symptom of ecological degradation. In areas where soil exposure is significant, NDVI tends to underestimate vegetation cover. In this context, the use of SAVI allows for a more reliable evaluation, confirming that the observed decreases are indeed related to an actual loss of canopy and not to bare soil reflectance. The concordance of both indices therefore strengthens the interpretation of forest degradation and highlights the importance of combining NDVI and SAVI in semi-arid ecosystems. From an ecological perspective, the reduction of vegetation cover implies a disturbance of ecosystem services, particularly soil stabilization and the provision of wildlife habitats. The fragmentation observed in degraded areas may further exacerbate biodiversity loss. Conversely, zones that have maintained stable, or even slightly increasing, NDVI and SAVI values indicate regeneration dynamics, probably linked to natural recovery processes or reforestation efforts within the forest massif. This research confirms the relevance of remote sensing tools and vegetation indices as reliable means for monitoring forest ecosystems in semi-arid environments. Furthermore, the use of GEE proved particularly effective for managing large databases, facilitating both temporal analysis and spatial mapping at different scales. Looking forward, integrating climatic and socio-economic data, as well as higher-resolution satellite imagery, would enhance the understanding of forest dynamics and guide management strategies more effectively. It is therefore recommended to combine these technological approaches with field monitoring and participatory management to ensure the long-term preservation and enhancement of the Senalba forests. In conclusion, this study contributes to a better understanding of the degradation state of the Senalba Chergui and Gharbi forests and represents a contribution to the creation of a modest database that can serve as a foundation for future work studying the diversity of forest formations the Djelfa region.

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