DOI: 10.5281/zenodo.13785996
title: DBSCAN 3D Clusters of SPEI-90 days Values – Italian NUTS3 (ITH31, 32, 34, 35, 36, 37), 1950–2023

description: Science Case Name 



Multi-Hazards in the Downstream Area of the Adige River Basin. 





Dataset Name/Title 



DBSCAN 3D Clusters of SPEI-90 days Values – Italian NUTS3 (ITH31, 32, 34, 35, 36, 37), 1950–2023





Dataset Description 



Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm output based on the daily Standardized Precipitation Evapotranspiration Index (SPEI) with a 90-day timescale for elevation lower than 1500 m a.s.l. (https://doi.org/10.5281/zenodo.13778103) applying the threshold SPEI-90 days ≤ -1.





Key Methodologies 



The DBSCAN algorithm included in the scikit-learn package in Python environment (https://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html) was used to detect the spatio-temporal clusters of droughts, taking the SPEI index as input. Three parameters guide the DBSCAN clustering procedure: the neighbourhood parameter (ε), which defines the search radius around a point (a SPEI index value); the spatio-temporal ratio (r), which controls the importance of spatial distance relative to temporal lag when computing the Euclidean distance between data points; the density threshold parameter (μ), representing the minimum number of neighbouring SPEI pixels required for a point to be considered as a core point (a point representing a suitable point to generate a new drought cluster).

The selected parameter values are: neighbourhood parameter (ε) = 30, spatio-temporal ratio (r) = 3 and density threshold (μ) = 10. These parameters were selected based on their physical significane and then refined through the comparison with the drought historical events retrieved from newspapers, official technical reports and regional council resolutions.





Temporal Domain 



1950–2023





Spatial Domain 



The spatial domain of the dataset is represented by the Italian Provinces identified by the NUTS3 codes ITH31 (Verona), ITH32 (Vicenza), ITH34 (Treviso), ITH35 (Venezia), ITH36 (Padova), ITH37 (Rovigo) considering elevation lower than 1500 m a.s.l..





Key Variables/Indicators 



Spatio-temporal clusters of dry/drought events





Data Format 



Comma Separated Values (CSV) 





Source Data 



E-OBS dataset (v29.0e), https://zenodo.org/records/13778103





Accessibility 



Zenodo, https://doi.org/10.5281/zenodo.13785996





Stakeholder Relevance 



Both the SPEI index and its adoption as an input in the DBSCAN algorithm used to identify drought spatio-temporal clusters represent a key step to identify the spatio-temporal footprints of hazard events. The identification of spatial patterns enables a greater understanding of hazard dynamics, it can be coupled with other hazard footprints (e.g., heatwaves) and fosters the use of EO data by providing a robust meteorological-based event identification to be then further refined by the use of higher spatial resolution EO data capable of capturing subtle spatial patterns (e.g., soil moisture as influenced by droughts, or land surface temperature as a response to different land uses during hot events).





Limitations/Assumptions 



Excludes areas above 1500 m a.s.l.





Additional Outputs/information



Daily SPEI-90 Days Values - Elevation Below 1500 m a.s.l. (https://zenodo.org/records/13778103)The dataset access is currently restricted due to pending related publication.





Contact Information 



Maraschini, Margherita (CMCC Foundation - Euro-Mediterranean Center on Climate Change) - Data managerMasina, Marinella (CMCC Foundation - Euro-Mediterranean Center on Climate Change) - Data curatorFurlanetto, Jacopo (CMCC Foundation - Euro-Mediterranean Center on Climate Change, National Biodiversity Future Center) - 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