Multi-Sensor NDVI and VCI-Based Drought Assessment in the Ceyhan Basin, Türkiye: AVHRR-MODIS Comparison and Land-Cover Effects

Drought is one of the most complex natural hazards affecting Mediterranean basins, and its monitoring requires approaches capable of capturing both temporal evolution and spatial heterogeneity. In this study, remote-sensing-based drought assessment was carried out for the Ceyhan Basin, Türkiye, using the Normalized Difference Vegetation Index (NDVI) and the Vegetation Condition Index (VCI). Vegetation dynamics were analyzed using AVHRR-3g NDVI data for 1981–2016 and MODIS MOD13Q1 NDVI data for 2000–2016, and the effects of spatial resolution, temporal coverage, and land-cover heterogeneity on drought interpretation were evaluated. To support class-based analysis, CORINE land-cover data were integrated into the assessment, allowing agricultural, forest, and semi-natural vegetation types to be examined separately. The comparison of NDVI datasets showed that the main sensor-related divergence between AVHRR and MODIS products were associated with seasonal patterns, whereas anomaly series were relatively more consistent. Basin-averaged VCI results indicated recurrent vegetation stress, generally corresponding to low- to moderate-intensity drought conditions. Land-cover-based analyses further demonstrated that vegetation response varied substantially among classes, reflecting differences in ecological structure, phenology, and spatial fragmentation. Overall, the findings show that drought in the Ceyhan Basin is better characterized as a gradually developing and spatially differentiated process rather than a persistent severe event. The study also highlights that the explanatory power of vegetation-based drought monitoring increases when multiple datasets, land-cover information, and sensor-related limitations are considered together.