10.26165/JUELICH-DATA/WD5YUJJuan QuirosJuanQuiros0000-0001-6524-7504IBG-2Airborne solar-induced chlorophyll fluorescence (SIF) and plant available water datasets across multiple crops and yearsJülich DATA2026Agricultural Sciencesfluorescence emission efficiency, mild water stress assessment, water management, airborne imaging spectroscopy, plant-water relations, agricultureRemote sensing of vegetationJuan QuirosJuanQuirosIBG-22026-01-052026-01-052026-01-13171843852866644572366851065286400619526753897964234382622215193187538602402860819318625615092112174123894456150922866643639468160813220224213263738text/csvtext/csvimage/tiffimage/tiffapplication/zipped-shapefileimage/tiffimage/tiffimage/tiffapplication/zipped-shapefileimage/tiffimage/tiffimage/tiffapplication/zipped-shapefileimage/tiffimage/tiffimage/tiffapplication/zipped-shapefileimage/tiffimage/tiffimage/tiffapplication/zipped-shapefileimage/tifftext/csvapplication/vnd.openxmlformats-officedocument.spreadsheetml.sheet1.0This dataset was compiled to support the analysis of spatial and interannual relationships between solar-induced chlorophyll fluorescence (SIF) and soil water availability in agricultural systems under contrasting crop, phenological, and water-management conditions. It comprises multi-year airborne SIF observations and derived canopy-normalized fluorescence emission efficiency (eSIF), together with high-resolution soil information used to estimate plant available water (PAW). The dataset includes (i) two tabular datasets in CSV format summarizing seasonal precipitation regimes and crop phenology, including phenology class assignments derived from enhanced vegetation index (EVI) time series, (ii) annual raster layers of top-of-canopy SIF and leaf-level eSIF retrieved from airborne imaging spectroscopy, and (iii) year-specific vector datasets of individual soil units containing associated values of PAW capacity (PAWcap), estimated actual PAW, spatially aggregated SIF and eSIF metrics, as well as phenology category. Covering five growing seasons (2018–2022) and multiple crop types under rainfed and irrigated conditions, the dataset enables reproducible investigations of how crop physiological responses captured by SIF relate to soil water availability across space, time, and phenological stages.