Demonstration Case Name Multi-Hazards in the Downstream Area of the Adige River Basin. Dataset Name/Title NDVI observations for Common and Winter Wheat, Maize and Soybean – Adige River-Fed Downstream Irrigated Plain, 2022 Dataset Description NDVI (Normalized Difference Vegetation Index) and Bare Soil Index (BSI) observations at the crop field level for Common and Winter Wheat, Maize, and Soybean. The dataset contains one row per crop field representing the average crop field NDVI, covering 10 distinct dates between March 9 and August 26, 2022. All observations are located in a plain area that relies on the Adige River for cropland irrigation, and are integrated with Hydrologic Soil Group data. Dataset column names: id crop_type HSG: Hydrologic Soil Group area_sqm: crop field area in square meters avg_ndvi_YYYYmmdd: average crop field NDVI for the specific date (e.g., 2022 March 9, 20220309) avg_bsi_YYYYmmdd: average crop field BSI for the specific date (e.g., 2022 March 9, 20220309) Key Methodologies Crop field-level NDVI values were calculated by averaging pixel-level NDVI derived from Sentinel-2 L2A observations within the irrigated districts fed with the Adige River waters (data courtesy of ANBI Veneto). Crop field-level NDVI values were linked to specific crops using in situ crop type information (data obtained from Regional Local Agencies). The observations in the dataset result from a multi-step data cleaning process. Raw observations were excluded if more than 50% of their pixels were unavailable e.g., due to cloud cover; remaining observations were filtered using a Bare Soil Index (BSI) threshold of 0.08 (Mzid et al., 2021), to distinguish vegetated from non vegetated (soil) pixels. Finally, fields associated with alternating crops required further processing, in order to disentangle double entries and assure that the satellite observation referred to the correct crop. Temporal NDVI profiles were inspected to identify two green-up periods separated by at least one observation identified as bare soil (BSI > 0.08). To disentangle alternating crop field, the following assumptions were made: if soybean was one of the reported crops, the vegetation period following the bare-soil break was attributed to soybean, while the preceding growth phase was assigned to the initial crop (e.g., winter wheat or maize); in cases where no double cropping was reported but a second green-up phase was evident, it was assumed to result either from an unreported second crop or from spontaneous vegetation regrowth after harvesting. In such instances, only observations preceding the bare-soil interval and considered relevant to the declared crop growing season were retained for analysis. Temporal Domain 2022 Spatial Domain The dataset is provided over the [10.7, 45.0, 12.3, 45.6] spatial domain (min longitude, min latitude, max longitude, max latitude in WGS84, EPSG:4326). Key Variables/Indicators Normalized Difference Vegetation Index (NDVI); Bare Soil Index (BSI) Data Format csv Source Data NDVI and BSI were obtained from ESA Copernicus Sentinel-2 L2A Crop field level information on farmer declared crop were obtained from the Veneto Agency for Payments in Agriculture (AVEPA, Agenzia Veneta per i Pagamenti, https://www.avepa.it/web/avepa) Hydrologic Soil Group at 1:250000 scale data were obtained from the Agenzia Regionale per la prevenzione e protezione ambientale Veneto (ARPAV, Agenzia Regionale per la Prevenzione e Protezione Ambientale del Veneto - Regional Agency for Environmental Prevention and Protection of Veneto, https://www.arpa.veneto.it/), and follow the classification scheme outlined in USDA National Engineering Handbook (USDA-NRCS, 2009) Irrigated districts were provided by courtesy of ANBI Veneto (Associazione Nazionale Bonifiche Irrigazioni - National Association of Land Reclamation and Irrigation) Accessibility https://doi.org/10.5281/zenodo.15189872 Stakeholder Relevance The NDVI is a valuable indicator of vegetation health due to its ability to capture chlorophyll activity and biomass dynamics through the differential reflectance between red and near-infrared wavelengths. This index is widely recognized for its robustness in monitoring vegetation vigor, phenological stages, and crop stress. Associating field-level NDVI values with specific crops may enable the identification of patterns linked to co-occurring natural hazards, such as extreme dry and hot events. Moreover, the availability of information on soil hydraulic properties (retrieved from the Hydrologic Soil Group) allows for the identification of relationships between crop average NDVI values and soil properties, potentially allowing for adaptation strategies related to crop performance during dry and hot events. The reliability of the dataset has been further enhanced through a dedicated data cleaning methodology, allowing to distinguish between vegetated and non vegetated crop fields as well as identifying alternating crops. Limitations/Assumptions In cases where a field was associated with more than one crop, a disaggregation technique was applied based on assumptions about crop growth phases. Additional Outputs/Information The dataset access is currently restricted due to pending related publication. Contact Information Albergo, Edoardo (CMCC Foundation - Euro-Mediterranean Center on Climate Change, National Biodiversity Future Center) - Data curatorFurlanetto, Jacopo (CMCC Foundation - Euro-Mediterranean Center on Climate Change, National Biodiversity Future Center) - Data curatorMasina, Marinella (CMCC Foundation - Euro-Mediterranean Center on Climate Change)- Data curatorMaraschini, Margherita (CMCC Foundation - Euro-Mediterranean Center on Climate Change) - Data curatorFerrario, Davide Mauro (CMCC Foundation - Euro-Mediterranean Center on Climate Change) - Data curatorTorresan, Silvia (CMCC Foundation - Euro-Mediterranean Center on Climate Change, National Biodiversity Future Center) - Data manager