Analyzing wildfire patterns and climate interactions in Campania, Italy. A multi-sensor remote sensing study

Wildfire dynamics and their interactions with climatic variables pose significant challenges in Mediterranean ecosystems. This study investigates spatiotemporal wildfire patterns in Campania, southwestern Italy, for the period 2001–2020 during the peak fire season (June–September). Burned area, land cover/use, land surface temperature (LST), and normalized difference vegetation index (NDVI) products of moderate resolution imaging spectroradiometer (MODIS) as well as the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) dataset are employed. First, the Mann–Kendall test and Sen's slope estimator are applied to each land cover/use class within each province. Next, Pearson's correlations among NDVI, LST, and precipitation are estimated at the pixel level, and their interconnections with fire activity are studied at the province level. The results reveal significant declines in grasslands across all provinces, with the strongest (−17.69 km2/year) in Avellino, and increases in grassy woodlands, e.g., +16.51 km2/year in Avellino and + 11.41 km2/year in Benevento. LST shows the strongest positive correlation with burned area in Caserta (r = 0.67), while NDVI correlates negatively with fire, with the highest magnitude in Avellino (r = −0.70). Precipitation–fire relationships are generally weak to moderate and negative, with the strongest in Benevento (r = −0.52). NDVI–LST correlations are significantly negative across all provinces, with the strongest (r = −0.79) in Benevento, highlighting vegetation stress under thermal extremes. To complement the regional assessment, a case study of the 2017 wildfire on Ischia Island is also presented, employing Sentinel-2 imagery for differenced normalized burn ratio (dNBR) mapping and dynamic world land cover data for detecting short-term post-fire land cover changes. The findings highlight the importance of integrating low to high-resolution satellite images to capture both broad-scale climate–fire interactions and localized fire dynamics, supporting improved wildfire susceptibility assessment in Mediterranean landscapes.