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opencc-by-4.0Jun 2023View details →

Initial Sample of HYPERNETS Hyperspectral Water Reflectance Measurements for Satellite Validation at Lake Garda, GAIT site (Italy)

The HYPERNETS project (www.hypernets.eu) has the overall aim to ensure that high quality in situ measurements are available to support the (VNIR/SWIR) optical Copernicus products. Therefore, it established a new autonomous hyperspectral spectroradiometer (HYPSTAR® - www.hypstar.eu) dedicated to land and water surface reflectance validation with instrument pointing capabilities. In the prototype phase, the instrument is being deployed at 24 sites covering a range of water and land types and a range of climatic and logistic conditions. This dataset provides the first published data for the HYPERNETS site in Lake Garda in Italy (GAIT). It is a subset of the complete data record which consists of the best quality GAIT measurements which could be used for satellite validation. The provided NetCDF files are the L2A hypernets products with water leaving radiance and reflectances, with and without NIR Similarity Correction (see Ruddick et al., 2006, DOI:<a href="http://dx.doi.org/10.2307/3841124">10.2307/3841124</a>). The reflectance in the L2A products is the Water Reflectance without NIR Similarity Correction (referred to as reflectance_nosc in the file) defined as:\(\rho_wnosc=\pi (Lu-\rho_FLd)/E_d\)where Lu is the upwelling radiance (at 40° zenith angle, and, 90° or 135° azimuth angle relative to the sun), Ld is the downwelling radiance (at 140° zenith angle, and, 90° or 135° azimuth angle relative to the sun). Ed is the (hemispherical) downwelling irradiance (i.e. including both direct solar and diffuse sky irradiance).For the GAIT site, the reflectance corrected for the NIR Similarity correction (epsilon, see Ruddick et al., 2006) is also provided:\(\rho_w=\pi (Lu-\rho_FLd)/E_d-\epsilon\)These reflectances have dimensions of wavelength and series, where each series is a set of measurements for the computation of a water reflectance measurement. In addition to variables for wavelength and bandwidth, the files also contain variables that provide for each series the acquisition time, viewing and solar angles, and quality flags (typically no flags are set in the data provided in this dataset). These NetCDF files also contain further relevant metadata as attributes. See https://hypernets-processor.readthedocs.io/ for further info.The HYPSTAR®-SR (Standard Range) instruments deployed at each land HYPERNETS site consist of a VNIR sensor and autonomously collect data between 380-1000 nm at various viewing geometries and send it to a central server for quality control and processing. The VNIR sensor spans 1330 channels between 380 and 1000 nm with a FWHM of 3 nm. The hypernets_processor (Goyens et al. 2021, DOI: <a href="https://doi.org/10.1109/IGARSS47720.2021.9553738">10.1109/IGARSS47720.2021.9553738</a>; De Vis et al. in prep.) automatically processes all this data into various products, including the L2A surface reflectance product provided here. The current dataset is limited to the 400-900 nm range. Uncertainties are not yet included.To obtain this dataset, we start from the full GAIT data record and omit all the data that do not pass all the quality checks performed as part of the hypernets_processor. In addition, an additional screening procedure was developed to supply the best quality data suitable for satellite validation:1. The coefficient of variation in water reflectance is below 10% in the 580-600 nm range2. The water reflectance (after correction for the NIR similarity) at 500 nm is below 0.1

opencc-by-4.0Jun 2023View details →

Initial Sample of HYPERNETS Hyperspectral Water Reflectance Measurements for Satellite Validation from the VEIT site (Italy)

The HYPERNETS project (www.hypernets.eu) has the overall aim to ensure that high quality in situ measurements are available to support the (VNIR/SWIR) optical Copernicus products. Therefore, it established a new autonomous hyperspectral spectroradiometer (HYPSTAR® - www.hypstar.eu) dedicated to land and water surface reflectance validation with instrument pointing capabilities. In the prototype phase, the instrument is being deployed at 24 sites covering a range of water and land types and a range of climatic and logistic conditions. This dataset provides the first published data for the HYPERNETS site at Aqua Alta, Venice in Italy (VEIT). It is a subset of the complete data record which consists of the best quality VEIT measurements which could be used for satellite validation.  The provided NetCDF files are the L2A hypernets products with water leaving radiance and reflectances, with and without NIR Similarity Correction (see Ruddick et al., 2006, DOI:<a href="http://dx.doi.org/10.2307/3841124">10.2307/3841124</a>). The reflectance in the L2A products is the Water Reflectance without NIR Similarity Correction (referred to as reflectance_nosc in the file) defined as: \(\rho_wnosc=\pi (Lu-\rho_FLd)/E_d\) where Lu is the upwelling radiance (at 40° zenith angle, and, 90° or 135° azimuth angle relative to the sun), Ld is the downwelling radiance (at 140° zenith angle, and, 90° or 135° azimuth angle relative to the sun). Ed is the (hemispherical) downwelling irradiance (i.e. including both direct solar and diffuse sky irradiance). For the VEIT site, the reflectance corrected for the NIR Similarity correction (epsilon, see Ruddick et al., 2006) is also provided: \(\rho_w=\pi (Lu-\rho_FLd)/E_d-\epsilon\) These reflectances have dimensions of wavelength and series, where each series is a set of measurements for the computation of a water reflectance measurement. In addition to variables for wavelength and bandwidth, the files also contain variables that provide for each series the acquisition time, viewing and solar angles, and quality flags (typically no flags are set in the data provided in this dataset). These NetCDF files also contain further relevant metadata as attributes. See https://hypernets-processor.readthedocs.io/ for further info. The HYPSTAR®-SR (Standard Range) instruments deployed at each land HYPERNETS site consist of a VNIR sensor and autonomously collect data between 380-1000 nm at various viewing geometries and send it to a central server for quality control and processing. The VNIR sensor spans 1330 channels between 380 and 1000 nm with a FWHM of 3 nm. The hypernets_processor (Goyens et al. 2021, DOI: <a href="https://doi.org/10.1109/IGARSS47720.2021.9553738">10.1109/IGARSS47720.2021.9553738</a>; De Vis et al. in prep.) automatically processes all this data into various products, including the L2A surface reflectance product provided here. The current dataset is limited to the 400-900 nm range. Uncertainties are not yet included. To obtain this dataset, we start from the full VEIT data record and omit all the data that do not pass all of the quality checks performed as part of the hypernets_processor. In addition, an additional screening procedure was developed to supply the best quality data suitable for satellite validation: 1. The coefficient of variation in water reflectance is below 10% in the 580-600 nm range 2. The water reflectance (after correction for the NIR similarity) above 800 nm is below 0.01

opencc-by-4.0Oct 2021View details →

Salt-Affected Soils in Italy

Soil salinization and sodification risks are two of the main threats in agricultural soils of Italy (Dazzi, 2008). In Italy they are mainly due to irrigation with saline waters (Dazzi and Lo Papa, 2013), to seawater intrusion (Castrignanò et al., 2008, Dazzi and Lo Papa, 2013, Selvaggi et al., 2010), and to saline parent materials (Dazzi and Fierotti, 1994). The water level is strictly regulated by channels and pumping stations (Vittori Antisari et al., 2020; Buscaroli and Zannoni, 2010; Teatini et al., 2007), and seawater intrusion along rivers, canals and in the groundwater aquifer is exacerbated by subsidence (Teatini et al., 2005). The salt-rich parent material can be exposed due to soil erosion (Piccarreta et al., 2006; Cocco et al., 2015). In the last decades, several Italian regional authorities for soil data produced soil salinity (risk) maps, resorting to different mapping approaches. Previous examples of salinity risk maps of Italy have been also attempted (Dazzi, 2008, Costantini et al. 2009). This works presents the maps of salt-affected soils of Italy, as part of the 1k grid GSSmap, realized adopting the procedure proposed by the Global Soil Partnership (GSP), and involving the Italian regional authorities, which are part of the Italian Soil Partnership.

opencc-by-4.0Aug 2023View details →

Water quality in a basin for drinking water in the North-West of Italy (2022-2023)

Information about water quality in La Loggia basin was collected in different seasons in 2022 and 2023, both on the basin surface and at different depths. Samples were collected and analysed in lab, for the following parameters: <ul> <li>Total chlorophyll</li> <li>Blue-green algae</li> <li>Diatoms</li> <li>Green algae</li> <li>Planktothrix</li> <li>Transparency</li> <li>Temperature</li> <li>Dissolved oxygen</li> <li>pH</li> <li>Conductivity</li> <li>Turbidity</li> <li>Bromide</li> <li>Bromate</li> <li>Chloride</li> <li>Chlorite</li> <li>Chlorate</li> <li>Fluoride</li> <li>Nitrite</li> <li>Nitrate</li> <li>Orthophosphate</li> <li>Sulfates</li> </ul> Samples were collected in the same dates of Sentinel-2 passages, in order to be used for the of satellite derived water quality products. The shared data are not representative of drinking water distributed to users, since a multi-step treatment is performed on raw water in order to assure water safety and law-compliant quality standards. The coordinates of the sampling points are also available in the dataset.

opencc-by-4.0Sep 2023View details →

Ensemble monthly evapotranspiration over italy 1991-2020

Six open access actual ET datasets are merged using an expert-based multiple collocation (MC) approach, with the aim of reconstructing a spatiotemporal consistent monthly dataset for the climatological period 1991-2020 over Italy at a spatial resolution of 1-km. The merged products include: three water balance datasets (BIG BANG, LSA SAF, and LISFLOOD), two residual surface energy balance models (SSEBop, and ALEXI) and the MODIS standard product. More details can be found in Cammalleri et al. (2023, under review)

opencc-by-4.0Oct 2023View details →

Database of pyroclastic cover deposit thickness measurements (PT-Cam) in peri-volcanic areas of Campania (Italy)

In an eruptive event, tephra deposits (i.e. ash and pumice) disperse in the atmosphere and deposit on the ground surface according to the speed and direction of the wind. Because the geotechnical and hydraulic properties of the unconsolidated pyroclastic fall deposits usually differ from the bedrock, their spatial thickness significantly influences geomorphological and hydrogeological processes such as landscape evolution, erosion, landslide, and hillslope hydrogeology. The PT-Cam database presents the thickness of tephra deposits (i.e. the unconsolidated materials over the bedrock) in Campania region (Italy), measured through in-situ investigations of some territories around the Somma-Vesuvius, Campi Flegrei, Roccamonfina, and Ischia volcanoes during the last decades. The measurements were conducted with probing tests, dynamic penetration tests, trenches, man-made pits, seismic surveys, and outcrops. Explanation for database attribute: <ul> <li>CODE: identification code of the measurement;</li> <li>z: measured thickness expressed in cm;</li> <li>type_z: thickness type (i.e. if investigation has reached to the bedrock the type is “total” otherwise it is “partial”);</li> <li>type_investigation: method of in-situ investigation;</li> <li>locality: municipality to which the measurement point belongs;</li> <li>Longitude, Latitude: km coordinates in UTM WGS 84 system.</li> </ul>

opencc-by-4.0Jan 2020View details →

Italy Southern Regions organic waste stream, Agricultural, Forest and Municipal Solid Waste, years 2018 and 2030

Southern Italy regions agricultural residues (straw, pruning)  quantification, years 2018 and 2030 Souther Italy regions above ground annual forest increment, 2018 and 2030 technical and environmental contraints Souther Italy regions Municipal Solid Waste separation 2018,  and 2030 minimum target EU waste Directive 2018/851

opencc-by-4.0Mar 2020View details →

LTER-Italy site Lago Maggiore figure

Geographical representation of the LTER-Italy site Lago Maggiore - DEIMS-ID <a href="https://deims.org/f30007c4-8a6e-4f11-ab87-569db54638fe">https://deims.org/f30007c4-8a6e-4f11-ab87-569db54638fe</a>

opencc-by-4.0May 2020View details →

Dataset: Effects of high altitude reservoirs on the structure and function of lotic ecosystems: a case study in Italy

Supporting data for "Effects of high altitude reservoirs on the structure and function of lotic ecosystems: a case study in Italy" Macroinvertebrate community composition Water chemical characteristics Daily mean water temperature and daily temperature variations Results of the leaf bags experiments

Annotated checklist of the beetles of Abeti Soprani, a silver fir forest of Central Italy

The checklist contains 179 species of beetles which belong to 48 families. The species were collected during a field study carried out in the years 2012 and 2013 and aimed at describing the beetles of the area. The collection methods consisted in window flight traps and emergence traps. The study area, named Abeti Soprani, is a silver fir (Abies alba) forest located in the Central Apennines. The checklist is annotated with information on the taxonomy of the species (order and family), number of individuals, geographic position, habitat type (following EUNIS habitat classification 2017), sampling protocol, collector name, specialist name, IUCN Red List categories of the saproxylic species (Carpaneto et al. 2015).  The terms used for the dataset fields follows the Darwin Core Maintenance Group. 2020. List of Darwin Core terms. Biodiversity Information Standards (TDWG). <a href="https://dwc.tdwg.org/list/">https://dwc.tdwg.org/list/</a> Investigations on spatial patterns and diversity have been based on this dataset and published (Parisi et al. 2016, 2020). The harmonization of the dataset to the point of view of taxa, authorship, LSID and the massive upgrading of the related identifiers in Zenodo record was performed by the use of R script using respectively dplyr, taxize (Chamberlain and Szöcs, 2013) and zen4r (Blondel and Barde, 2020) packages.

Annotated checklist of the beetles of chestnut agroforestry systems in Aspromonte, Southern Italy

The checklist contains 255 species of beetles which belong to 49 families. The species were collected during a field study carried out in the years 2017 and aimed at describing the community of beetles. The collection methods consisted of window flight traps. The study area included 3 sites, two coppice stands, young and mature (38.180221 N, 15.784308 E), and a traditional fruit orchard (38.06018 N, 15.781616 E), located in the Italian Southern Apennines on the borders of the Aspromonte National Park. The checklist is annotated with information on the taxonomy of the species (order and family), number of individuals, locality, habitat type (following EUNIS habitat classification 2017), sampling protocol, collector name, specialist name, IUCN Red List categories of the saproxylic species (Carpaneto et al. 2015).  The terms used for the dataset fields follows the Darwin Core Maintenance Group. 2020. List of Darwin Core terms. Biodiversity Information Standards (TDWG). <a href="https://dwc.tdwg.org/list/">https://dwc.tdwg.org/list/</a> The Diversity of saproxylic beetle communities have been analysed and published (Parisi et al. 2020). The harmonization of the dataset to the point of view of taxa, authorship, LSID and the massive upgrading of the related identifiers in Zenodo record was performed by the use of R script using respectively dplyr, taxize (Chamberlain and Szöcs, 2013) and zen4r (Blondel and Barde, 2020) packages.

Annotated checklist of the beetles of beech forests in Matese National Park, Central Italy

The checklist contains 165 species of beetles which belong to 37 families. The species were collected during a field study carried out in the year 2018 and aimed at describing the community of beetles. The collection methods consisted of window flight traps. The study activities were carried out in four distinct beech forest stands based on their altitude (High and Low) and exposure (South and North) and located in the Italian Central Apennines. The sites are included in the Natura 2000 site IT 7222287 “La Gallinola - Monte Miletto - Monti del Matese” and Matese National Park. The checklist is annotated with information on the taxonomy of the species (order and family), number of individuals, geographic position, habitat type (following EUNIS habitat classification 2017), sampling protocol, collector name, specialist name, IUCN Red List categories of the saproxylic species (Carpaneto et al. 2015).  The terms used for the dataset fields follows the Darwin Core Maintenance Group. 2020. List of Darwin Core terms. Biodiversity Information Standards (TDWG). <a href="https://dwc.tdwg.org/list/">https://dwc.tdwg.org/list/</a> The discovery of a new species of beetle (Elateridae) for the Italian fauna was based on this dataset (Parisi et al., 2020). The harmonization of the dataset to the point of view of taxa, authorship, LSID and the massive upgrading of the related identifiers in Zenodo record was performed by the use of R script using respectively dplyr, taxize (Chamberlain and Szöcs, 2013) and zen4r (Blondel and Barde, 2020) packages.

Annotated checklist of the beetles of three beech forests in Gran Sasso National Park, Central Italy

The checklist contains 163 species of beetles which belong to 36 families. The species were collected during a field study carried out in the years 2013 and 2016 and aimed at describing the community of beetles. The collection methods consisted of window flight traps and emergence traps. The study area included 3 beech forest sites, named Prati di Tivo (42.5096 N, 13.5679 E), Venacquaro (42.4988 N, 13.5139 E) and Incodara (42.5123 N, 13.4735 E) located in the Italian Central Apennines. The sites are included in the Natura 2000 site IT7110202 “Gran Sasso”. The checklist is annotated with information on the taxonomy of the species (order and family), number of individuals, locality, habitat type (following EUNIS habitat classification 2017), sampling protocol, collector name, specialist name, IUCN Red List categories of the saproxylic species (Carpaneto et al. 2015).  The terms used for the dataset fields follows the Darwin Core Maintenance Group. 2020. List of Darwin Core terms. Biodiversity Information Standards (TDWG). <a href="https://dwc.tdwg.org/list/">https://dwc.tdwg.org/list/</a> Investigations on stand structure and forest biodiversity (Sabatini et al. 2016) and faunistic analysis (Zanetti and Parisi 2019) have been based on this dataset. The harmonization of the dataset to the point of view of taxa, authorship, LSID and the massive upgrading of the related identifiers in Zenodo record was performed by the use of R script using respectively dplyr, taxize (Chamberlain and Szöcs, 2013) and zen4r (Blondel and Barde, 2020) packages.

opencc-by-4.0Dec 2020View details →

Dataset of Sentinel-1 surface soil moisture time series at 1 km resolution over Southern Italy

The dataset consists of a time series of the Sentinel-1 (S-1) surface soil moisture (SSM) product at 1 km spatial resolution validated in Balenzano et al. (2021 a) over the Southern Italy. The specifications of the S-1 SSM product are provided in Balenzano et al. (2021 b). The SSM time series was obtained in correspondence of the ascending (RON A146) S-1 Interferometric Wide swath (IW) acquisition dates from January 2015 to December 2018 with a temporal gap between consecutive of 6 days (when both S-1A and S-1B data are available) or 12 days. On each date (183 in total), two co-registered layers are provided: mean SSM [m3/m3] and its standard deviation [m3/m3], which provides the SSM uncertainty. The retrieval algorithm is a time series short term change detection (STCD) that is implemented in the “Soil MOisture retrieval from multi-temporal SAR data” (SMOSAR) code (Balenzano et al. 2013).

opencc-by-4.0Oct 2023View details →

High-resolution earthquake catalog obtained through template-matching in the Southern Apennine (Italy)

This is an enhanced, high-resolution earthquake catalog obtained through template-matching (TM). It covers the area of the Southern Apennines (Italy), for the period 2009-2014 Starting from about 4000 events used as templates, TM allowed to detect the hidden, small-magnitude seismicity in the 0-1 magnitude range, allowing a significant decrease of the magnitude of completeness in the resulting earthquake catalog. The catalog contains: <ul> <li>templates (events catalogued by INGV and used as templates)</li> <li>template-matching detections (i.e. newly detected events by TM)</li> <li>events catalogued by INGV that are also found through template-matching</li> </ul> All events are located with the same 1-D velocity model obtained by averaging several models that have been proposed in the literature, covering different portion of the Southern Apennines.  DATA STRUCTURE id: id of event. Events detected by template-matching start with 'TM', otherwise the id is the same as in the official INGV catalog. lon: longitude (degrees) lat: latitude (degrees) depth: depth in km time: origin time M_l: local magnitude lon_error: error on longitude (degrees) lat_error: error on latitude (degrees) depth_error: error on depth (km) RMS: root-mean-square (sec) az_gap: azimuthal gap n_phases: total number of P and S arrivals  n_stations: total number of station recording the event mag_diff: difference in magnitude between detection and its template dt: difference in origin time between template and detected event (sec) templ_id: id of the template event as_template: =1 if the event was used as template, 0 otherwise matched_TM (for events already catalogued by INGV): =1 if the events matched a detection made by template matching, =0 otherwise matched_BSI: ==id of the corresponding event catalogued by INGV. For newly detected events (thus never catalogued before) this field is 'NA'

opencc-by-nc-4.0Feb 2024View details →

Geodiversity and Geoheritage data from Alagna Valsesia, Sesia Val Grande UGGp (NW Italy)

Geodiversity and geoheritage are concepts that have gained popularity in recent years for managing territories by promoting geoconservation and sustainable development. For example, geoparks, areas recognized by UNESCO and considered among the best examples of promoting informal education, geoconservation and geotourism of an area, are growing in number and importance. However, establishing the role and potential use of the geodiversity map in geoconservation and geoheritage recognition remains a complex task. In fact, there are numerous methodologies proposed to assess geodiversity, which can be summarized in 2 categories: qualitative method and quantitative method. These methods assess different characteristics of geodiversity and, from a geoconservation perspective, could be complementary tools. To explore the potential use of the quantitative geodiversity map and its association with geoheritage, we provide here files of Alagna Valsesia, a mountainous area located at the foot of Monte Rosa Massif, NW Italian Alps, within the Sesia Val Grande UGGp. Specifically, these data have been collected for the following pourposes: <ol> <li>Map geodiversity (shapefiles of geodiversity units and DTM of Alagna Valsesia);</li> <li>Inventory and mapping of geosites (shapefiles of geosites containing, in addition to the location, information on the importance and interests of the geosites, useful for land managers for their promotion and conservation);</li> <li>Statistical calculation of correlation between geodiversity and geoheritage in the field (R language script useful for calculating this correlation, which challenges the potential use of quantitative map for geosite recognition).</li> </ol> The data represent original data for the following publication: Michele Guerini, Alizia Mantovani, Rasool Bux Khoso, Marco Giardino (2024). Exploring the Correlation between Geoheritage and Geodiversity through Comprehensive Mapping: A Study within the Sesia Val Grande UNESCO Global Geopark (NW Italy), Geomorphology, Volume 461, 109298, https://doi.org/10.1016/j.geomorph.2024.109298.

opencc-by-4.0Dec 2023View details →

3D Models of the yellow coffins in the Museo Egizio, Torino (Italy)

3D Models of yellow coffin lids in the <a href="https://www.museoegizio.it/" target="_blank" rel="noopener">Museo Egizio, Torino</a>. The 3D models consider only the external upper part of coffin lids as far down as the lower part of the crossed forearms.   The dataset contains: <ol> <li>zip files with the 3D models generated with the software Agisoft Metashape 1.8.3 (.jpg; .mtl; .obj);</li> <li>.tif files with the orthophtgraphs of the coffins textured and not textured</li> <li>Exported Report of 3D models (.pdf)</li> <li>.pdn file with the overlapped layers (orthophotographs textured and not textured, drawings and points) generated with the open source paint. net</li> </ol> The dataset is part of the results of the  <a href="https://facesrevealed.museoegizio.it/">Faces Revealed Project</a>. The project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 895130 If you publish material based on datasets contained in this archive, then, in your acknowledgements, please cite the original source, referring to it through the following DOI: 10.5281/zenodo.10589491

opencc-by-4.0Dec 2023View details →

Pirro Nord 13 excavation dataset (Apricena, FG, Italy)

Pirro Nord 13 dataset containing the spatial coordinates of archaeological material (bones/teeth and lithics) from the 2012, 2013, 2014, 2015, 2017, 2018, 2019, 2021, 2022 and 2023 excavations.

opencc-by-4.0Nov 2024View details →

Publications supported by ELIXIR and ELIXIR Italy (during the periods 2011-2023 and 2015-2023)

Publications supported by ELIXIR and ELIXIR Italy (during the periods 2011-2023 and 2015-2023), retrieved from EuropePMC (Datasome) and curated by ELIXIR Hub and ELIXIR Italy.