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2023
Report
Open Access
Massaciuccoli Lake Basin - Atlas of agri-environmental spatial data
Vannini G. L., Coro G.
Atlas of agri-environmental spatial data developed in the context of the ITINERIS PNRR project. This is a cartographic collection of geospatial data with resolution lower than 50m for the Massaciuccoli Lake Basin.Source: ISTI Technical Report, ISTI-2023-TR/013, 2023
Vannini G. L., Coro G.
Atlas of agri-environmental spatial data developed in the context of the ITINERIS PNRR project. This is a cartographic collection of geospatial data with resolution lower than 50m for the Massaciuccoli Lake Basin.Source: ISTI Technical Report, ISTI-2023-TR/013, 2023
See at:
data.d4science.net 
| CNR ExploRA
2023
Journal article
Open Access
Missing plant detection in vineyards using UAV angled RGB imagery acquired in dormant period
Di Gennaro S. F., Vannini G. L., Berton A., Dainelli R., Toscano P., Matese A.
Since 2010, more and more farmers have been using remote sensing data from unmanned aerial vehicles, which have a high spatial-temporal resolution, to determine the status of their crops and how their fields change. Imaging sensors, such as multispectral and RGB cameras, are the most widely used tool in vineyards to characterize the vegetative development of the canopy and detect the presence of missing vines along the rows. In this study, the authors propose different approaches to identify and locate each vine within a commercial vineyard using angled RGB images acquired during winter in the dormant period (without canopy leaves), thus minimizing any disturbance to the agronomic practices commonly conducted in the vegetative period. Using a combination of photogrammetric techniques and spatial analysis tools, a workflow was developed to extract each post and vine trunk from a dense point cloud and then assess the number and position of missing vines with high precision. In order to correctly identify the vines and missing vines, the performance of four methods was evaluated, and the best performing one achieved 95.10% precision and 92.72% overall accuracy. The results confirm that the methodology developed represents an effective support in the decision-making processes for the correct management of missing vines, which is essential for preserving a vineyard's productive capacity and, more importantly, to ensure the farmer's economic return.Source: Drones 7 (2023). doi:10.3390/drones7060349
DOI: 10.3390/drones7060349
Metrics:
Di Gennaro S. F., Vannini G. L., Berton A., Dainelli R., Toscano P., Matese A.
Since 2010, more and more farmers have been using remote sensing data from unmanned aerial vehicles, which have a high spatial-temporal resolution, to determine the status of their crops and how their fields change. Imaging sensors, such as multispectral and RGB cameras, are the most widely used tool in vineyards to characterize the vegetative development of the canopy and detect the presence of missing vines along the rows. In this study, the authors propose different approaches to identify and locate each vine within a commercial vineyard using angled RGB images acquired during winter in the dormant period (without canopy leaves), thus minimizing any disturbance to the agronomic practices commonly conducted in the vegetative period. Using a combination of photogrammetric techniques and spatial analysis tools, a workflow was developed to extract each post and vine trunk from a dense point cloud and then assess the number and position of missing vines with high precision. In order to correctly identify the vines and missing vines, the performance of four methods was evaluated, and the best performing one achieved 95.10% precision and 92.72% overall accuracy. The results confirm that the methodology developed represents an effective support in the decision-making processes for the correct management of missing vines, which is essential for preserving a vineyard's productive capacity and, more importantly, to ensure the farmer's economic return.Source: Drones 7 (2023). doi:10.3390/drones7060349
DOI: 10.3390/drones7060349
Metrics:
See at:
ISTI Repository | www.mdpi.com | CNR ExploRA
2023
Report
Unknown
The gCube geoportal platform
Candela L., Cirillo R., Mangiacrapa F., Pagano P., Sinibaldi F., Vannini G. L.
The gCube Geoportal platform is a component of the gCube open source software system conceived to support the creation and publication of georeferenced research objects, i.e. multi-part and multimedia research objects characterised by geospatial and temporal features. The Geoportal platform enables user communities to fully customise the data model characterising their instance by defining the structure, the content and the workflow of the potential research objects to be managed. `this report carefully describes the technology and documents how it was exploited to serve the development of a national catalogue for archaeological artifacts.Source: ISTI Technical Report, ISTI-2023-TR/012, 2023
DOI: 10.32079/isti-tr-2023/012
Project(s): ARIADNEplus
, Blue Cloud
Metrics:
Candela L., Cirillo R., Mangiacrapa F., Pagano P., Sinibaldi F., Vannini G. L.
The gCube Geoportal platform is a component of the gCube open source software system conceived to support the creation and publication of georeferenced research objects, i.e. multi-part and multimedia research objects characterised by geospatial and temporal features. The Geoportal platform enables user communities to fully customise the data model characterising their instance by defining the structure, the content and the workflow of the potential research objects to be managed. `this report carefully describes the technology and documents how it was exploited to serve the development of a national catalogue for archaeological artifacts.Source: ISTI Technical Report, ISTI-2023-TR/012, 2023
DOI: 10.32079/isti-tr-2023/012
Project(s): ARIADNEplus
, Blue Cloud Metrics:
See at: CNR ExploRA
2023
Report
Unknown
InfraScience research activity report 2023
Artini M., Assante M., Atzori C., Baglioni M., Bardi A., Bosio C., Bove P., Calanducci A., Candela L., Casini G., Castelli D., Cirillo R., Coro G., De Bonis M., Debole F., Dell'Amico A., Frosini L., Ibrahim A. S. T., La Bruzzo S., Lelii L., Manghi P., Mangiacrapa F., Mangione D., Mannocci A., Molinaro E., Pagano P., Panichi G., Paratore M. T., Pavone G., Piccioli T., Sinibaldi F., Straccia U., Vannini G. L.
InfraScience is a research group of the National Research Council of Italy - Institute of Information Science and Technologies (CNR - ISTI) based in Pisa, Italy. This report documents the research activity performed by this group in 2023 to highlight the major results. In particular, the InfraScience group engaged in research challenges characterising Data Infrastructures, e-Science, and Intelligent Systems. The group activity is pursued by closely connecting research and development and by promoting and supporting open science. In fact, the group is leading the development of two large scale infrastructures for Open Science, i.e. D4Science and OpenAIRE. During 2023 InfraScience members contributed to the publishing of several papers, to the research and development activities of several research projects (primarily funded by EU), to the organization of conferences and training events, to several working groups and task forces.Source: ISTI Annual Reports, 2023
DOI: 10.32079/isti-ar-2023/002
Project(s): Blue Cloud, EOSC Future , TAILOR
Metrics:
Artini M., Assante M., Atzori C., Baglioni M., Bardi A., Bosio C., Bove P., Calanducci A., Candela L., Casini G., Castelli D., Cirillo R., Coro G., De Bonis M., Debole F., Dell'Amico A., Frosini L., Ibrahim A. S. T., La Bruzzo S., Lelii L., Manghi P., Mangiacrapa F., Mangione D., Mannocci A., Molinaro E., Pagano P., Panichi G., Paratore M. T., Pavone G., Piccioli T., Sinibaldi F., Straccia U., Vannini G. L.
InfraScience is a research group of the National Research Council of Italy - Institute of Information Science and Technologies (CNR - ISTI) based in Pisa, Italy. This report documents the research activity performed by this group in 2023 to highlight the major results. In particular, the InfraScience group engaged in research challenges characterising Data Infrastructures, e-Science, and Intelligent Systems. The group activity is pursued by closely connecting research and development and by promoting and supporting open science. In fact, the group is leading the development of two large scale infrastructures for Open Science, i.e. D4Science and OpenAIRE. During 2023 InfraScience members contributed to the publishing of several papers, to the research and development activities of several research projects (primarily funded by EU), to the organization of conferences and training events, to several working groups and task forces.Source: ISTI Annual Reports, 2023
DOI: 10.32079/isti-ar-2023/002
Project(s): Blue Cloud
, EOSC Future , TAILOR Metrics:
See at: CNR ExploRA