Annalisa Viani

ORCID: 0000-0003-1441-7678
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About
Contact & Profiles
Research Areas
  • Zoonotic diseases and public health
  • Viral Infections and Vectors
  • Remote Sensing in Agriculture
  • Animal Disease Management and Epidemiology
  • Species Distribution and Climate Change
  • Urban Heat Island Mitigation
  • Land Use and Ecosystem Services
  • Remote Sensing and Land Use
  • Insect and Arachnid Ecology and Behavior
  • Salmonella and Campylobacter epidemiology
  • Remote Sensing and LiDAR Applications
  • Digital Imaging for Blood Diseases
  • Leptospirosis research and findings
  • Yersinia bacterium, plague, ectoparasites research
  • Insect Pheromone Research and Control
  • Virology and Viral Diseases
  • Bartonella species infections research
  • Vector-borne infectious diseases
  • Microbial infections and disease research
  • Remote-Sensing Image Classification
  • Dermatological diseases and infestations

Azienda USL della Valle d’Aosta
2024-2025

ASL Roma
2024-2025

Istituto Zooprofilattico Sperimentale del Piemonte Liguria e Valle d'Aosta
2023-2024

University of Turin
2020-2023

Google Earth Engine has deeply changed the way in which observation data are processed, allowing analysis of wide areas a faster and more efficient than ever before. Since its inception, many functions have been implemented by rapidly expanding community, but none so far focused on computation phenological metrics mountain with high-resolution data. This work aimed to fill this gap developing an open-source algorithm map (PMs) such as Start Season, End Length Season detect Peak worldwide...

10.3390/geomatics3010012 article EN cc-by Geomatics 2023-02-21

Changes in land use and cover as well feedback on the climate deeply affect landscape worldwide. This phenomenon has also enlarged human-wildlife interface amplified risk of potential new zoonoses. The expansion human settlement is supposed to spread distribution wildlife diseases such canine distemper virus (CDV), by shaping distribution, density, movements wildlife. Nevertheless, there very little evidence scientific literature how remote sensing GIS tools may help veterinary sector better...

10.3390/ani12081049 article EN cc-by Animals 2022-04-18

Earth observation data have assumed a key role in environmental monitoring, as well risk assessment. Rising temperatures and consequently heat waves due to ongoing climate change represent an important considering the population, animals, exposed. This study was focused on Aosta Valley Region NW Italy. To assess population exposure these patterns, following datasets been considered: (1) HDX Meta dataset refined updated order map distribution its features; (2) Landsat collection (missions 4...

10.3390/rs15092348 article EN cc-by Remote Sensing 2023-04-29

The widespread diffusion of the wild boar on Italian territory and its consistent use for hunting have created possibility to conduct multiple studies pathologies afflicting this ungulate. Nevertheless, in last two decades, only some such as classical African Swine Fever, Tuberculosis, Brucellosis from Brucella suis benefited substantial public funding consequent great interest scientific world, while less attention was addressed parasitic diseases including sarcoptic mange. Therefore, fill...

10.3390/life13040987 article EN cc-by Life 2023-04-11

Nowadays, European program Copernicus’ Sentinel missions have allowed the development of several application services. In this regard, to strengthen use free satellite data in ordinary administrative workflows, work aims evaluate feasibility and prototypal a possible service called Sen4MUN for distribution contributions yearly allocated local municipalities scalable all regions. The analysis was focused on Aosta Valley region, North West Italy. A comparison between Ordinary Workflow (OW)...

10.3390/land13010080 article EN cc-by Land 2024-01-10

Bartonella is a genus of bacteria known to cause various rare but potentially dangerous diseases in humans and wildlife. The objective this study was investigate the presence spp. red foxes ( Vulpes vulpes ) from Piedmont Aosta Valley (NW Italy) explore potential association between environmental humidity infection using remote sensing data. A total 114 spleen samples were collected hunted screened for DNA qPCR assay targeting ssrA locus. Samples that tested positive further analyzed...

10.3389/fvets.2024.1388440 article EN cc-by Frontiers in Veterinary Science 2025-01-21

Geomatics and satellite remote sensing offer useful analysis tools for several technical-scientific fields. This work, with reference to a regional case of study, investigates potentialities describing relationships between environment diseases affecting wildlife at landscape level in the light climate change effects onto vegetation. Specifically, infectious keratoconjunctivitis (IKC) chamois (Rupicapra rupicapra L.) Aosta Valley (NW Italy) was investigated level. IKC (Mycoplasma...

10.3390/rs12213542 article EN cc-by Remote Sensing 2020-10-29

Wildlife can represent a reservoir of zoonotic pathogens and public health problem. In the present study, we investigated spread (

10.3390/ani14040562 article EN cc-by Animals 2024-02-07

Recently, the Italian government has announced IRIDE, a new Earth observation program. IRIDE will likely be completed by 2026 under management of European Space Agency (ESA) and with support (ASI). is an end-to-end system made up set sub-constellations (with radar optical sensors) services intended for Public Administration. The aims this work are twofold: firstly, to disseminate information within scientific community regarding program highlighting key constellation characteristics as...

10.3390/ecrs2023-16839 article EN cc-by 2024-01-25

Ticks represent a reservoir of zoonotic pathogens, and their numbers are increasing largely in wildlife. This work is aimed at producing maps suitable habitats for ticks Aosta Valley, Italy based on multitemporal EO data veterinary datasets (tick species distribution wild hosts). were processed Google Earth Engine considering the following inputs: A) Growing Degree (GDT), B) NDVI from MOD09GA, C) entropy, D) distance water bodies, E) topography, F) rainfalls CHIRPS as monthly composites...

10.12834/vetit.3481.24368.2 article EN PubMed 2024-11-05
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