Wildfire Severity and Vegetation Dieback Assessment in Algerian Forest, 2019-2022

Supplementary file 1_Multi-index analysis for wildfire severity and vegetation dieback assessment in semi-arid forest ecosystems.docx contains remote sensing analysis results from a study in the Ouled Yagoub State Forest, Algeria. The dataset, authored by Oussama Meghithi and shared on figshare under CC-BY-4.0, uses Landsat 8 OLI and Sentinel-2 imagery from 2019 to 2022 to assess wildfire impacts and vegetation decline. It employs ten spectral indices across themes of vegetation dynamics, burned-area severity, and forest dieback.

Use Cases

• Assessing wildfire risk and severity based on NDVI and dNBR classifications described in the study.
• Monitoring post-fire vegetation recovery based on multi-temporal dNBR comparisons.
• Identifying areas of gradual physiological stress and dieback using indices like GNDVI, SIPI, and NDWI.
• Improving identification of vegetation loss and soil exposure in sparse zones using SAVI, MSAVI, and OSAVI indices.

Strengths

• Analysis uses a multi-index approach with ten spectral indices across three complementary themes.
• Provides specific percentages for risk and severity classes, such as 38.04% of the massif in high to very high wildfire-risk classes.
• Compares pre- and post-fire conditions using imagery from 2019 to 2022.

Limitations

• The dataset is a 63.8 KB DOCX file, suggesting it contains textual analysis and figures rather than raw geospatial data tables.
• Column-level documentation is absent; field semantics must be inferred after download.
• The spatial scope is limited to a single state forest in northeastern Algeria.

Provenance

Source

Oussama Meghithi

Collection Method

Remote sensing analysis of Landsat 8 OLI and Sentinel-2 images processed in Google Earth Engine.

Time Range

2019 to 2022

Freshness

Last updated 2026-05-13 04:41:30; freshness should be verified.

Geography

Ouled Yagoub State Forest, Khenchela Province, northeastern Algeria