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Finanziamento UE – NextGenerationEU PRIN 2022 PNRR - SVeBio Statistics for vegetation biodiversity: estimation and mapping - PNRR M4C2 investimento 1.1 Avviso 1409/2022

Progetto
The biodiversity decline is a primary concern. In Italy, the evidence of the problem is now so widely and urgently perceived that in February 2022 the Parliament approved two articles of its Constitution Chart (9 and 41) to introduce the central role of biodiversity as a constitutional value that deserves specific protection for public interest. Vegetation plays a crucial role in biodiversity, as it influences almost every facet of the biophysical world and is an integral part ofecosystem composition, function, and structure, so that the conservation of biodiversity is, in turn, utterly dependent on the conservation of vegetation biodiversity. Also the Habitats directive (92/43/EEC) requires the EU member states to conserve habitats and species and to assess their conservation status every 6 years. Therefore, the geographical depiction of the spatial pattern of habitats, biodiversity indexes or other attributes of interest is essential for performing effective conservation strategies and halting biodiversity decline. SVeBio perfectly fits in this objective, aiming to develop innovative and efficient methods for estimating totals and construing wall-to-wall maps to assess and monitor vegetation biodiversity. More precisely, SVeBio will provide MODEL-BASED and MODEL-ASSISTED methods for producing SPATIAL MAPS by exploiting data available from probability sampling surveys, purposive field campaigns and remote sensing information. In the model-based framework, mapping is usually performed by using multiple data sources, while, in a model-assisted setting, methodological investigations for producing wall-to-wall maps by integrating purposive data with probability and remote sensing data are completely lacking and will be developped in this project. Furthermore, for the first time, the use of model-based predictions as proxies for the model-assisted interpolation will be investigated. This combined/hybrid strategy should take advantage of the strength of both approaches. Importantly, all the maps will be equipped with an uncertainty evaluation. In addition, the joint exploitation of multiple data sources will be addressed to develop theoretical advances in TOTAL ESTIMATION. Moreover, because the total estimates will invariably differ from those achieved by the produced maps as the sum of estimated/predicted values, SVeBio aims to investigate harmonization procedures able to rescale maps in such a way that the total arising from maps will match the total estimates. Finally, SVeBio will focus on two relevant and vulnerable repositories of biodiversity: FORESTS and COASTAL SAND DUNES. It is worth noting that the statistical tools provided by SVeBio can be exploited in many additional disciplines, such as geology, climatology, sociology and economics. The different expertises of team members and their documented collaborations with environmental researchers and policy makers ensure that SVeBio will have a clear societal impact.
  • Dati Generali
  • Aree Di Ricerca
  • Pubblicazioni

Dati Generali

Partecipanti (3)

GOLINI Natalia   Responsabile scientifico  
IGNACCOLO Rosaria   Partecipante  
LO PRESTI Anna   Partecipante  

Referenti

ROGINA Gabriele   Amministrativo  

Dipartimenti coinvolti

ECONOMIA E STATISTICA "COGNETTI DE MARTIIS"   Principale  

Tipo

Progetti PNRR M4C2 Investimento 1.1 - Fondo per il Programma Nazionale di Ricerca e Progetti di Rilevante Interesse Nazionale (PRIN) - Bando 2022

Finanziatore

MINISTERO DELL'UNIVERSITA' E DELLA RICERCA
Ente Finanziatore

Partner

Università degli Studi di TORINO

Contributo Totale Ottenuto (EURO)

109.555€

Periodo di attività

Novembre 30, 2023 - Novembre 29, 2025

Durata progetto

24 mesi

Aree Di Ricerca

Settori (4)


PE1_15 - Generic statistical methodology and modelling - (2022)

SH7_10 - GIS, spatial analysis; big data in geographical studies - (2022)

SH7_5 - Sustainability sciences, environment and resources - (2022)

Settore SECS-S/01 - Statistica

Parole chiave (6)

  • ascendente
  • decrescente
Data integration
Design-based inference
Forests and coastal sand dunes
Model-assisted inference
Model-based inference
Total estimation
No Results Found
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Pubblicazioni

Pubblicazioni (2)

Functional zoning of biodiversity profiles 
ENVIRONMETRICS
2024
Articolo
Altmetric disabilitato. Abilitalo su "Utilizzo dei cookie"
Improving spatial maps with preferential sampling via hierarchical modeling 
2024- ECOSTAECONOMETRICSANDSTATISTICS
2024
Contributo in Atti di convegno
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