Author Archives: Giovanna Venuti

5. Analysis of global distribution of Level 2A Sentinel-2 products

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Docente

Giovanna Venuti (mail)

Referente del progetto

dott.ssa Daniela Stroppiana ( mail)

Area di ricerca

Geoinformatica

Keyword (max 3 separate da virgola)

Earth Observations, Multispectral imagery, Sentinel 2

Tecnologie da utilizzare

Google Earth Engine

Descrizione (max 500 caratteri)

This project will be carried out in GEE with the objective of analysing the availability of Level 2A Sentinel-2 images at global scale in the GEE catalogue. The project will be carried out by developing GEE code for accessing the archive and metadata to depict the spatio-temporal distribution of image data and eventually their characteristics (from metadata).

Comparison of spatio-temporal burned area distribution

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Docente

Giovanna Venuti (mail)

Referente del progetto

Dott.ssa Daniela Stroppiana ( mail)

Area di ricerca

Geoinformatica

Keyword (max 3 separate da virgola)

Burned areas, Earth Observations, Time series

Tecnologie da utilizzare

Python, R

Descrizione (max 500 caratteri)

This project aims at comparing the spatio-temporal distribution of burned area estimates derived from multi-annual BA products available at global scale and derived from satellite data. The comparison will be carried out by year, country, biome, and taking into account other factors that could influence fires. Ad hoc code must be developed for the comparison of raster grid products.

Analysis of factors affecting wildfire distribution

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Docente

Giovanna Venuti (mail)

Referente del progetto

Dott.ssa Daniela Stroppiana ( mail)

Area di ricerca

Geoinformatica

Keyword (max 3 separate da virgola)

Burned areas, Earth Observation, Google Earth Engine

Tecnologie da utilizzare

Google Earth Engine

Descrizione (max 500 caratteri)

This project has the objective of using the Google Earth (GEE) catalogue (burned areas, land cover, and other ancillary datasets) for analysing the relative importance of factors affecting burned areas globally. The approach will be based on machine learning algorithms (e.g. Random forest) to be implemented in GEE.

Analysis of satellite SAR data over burned areas in African ecosystems

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Docente

Giovanna Venuti (mail)

Referente del progetto

Dott.ssa Daniela Stroppiana ( mail)

Area di ricerca

Geoinformatica

Keyword (max 3 separate da virgola)

Burned Areas, SAR, Earth Observation

Tecnologie da utilizzare

Google Earth Engine

Descrizione (max 500 caratteri)

This project aims at analysing the burned area signal with SAR Sentinel-1 data over areas affected by fires in African biomes (forest and savanna). The project foresees the integration of information on fire perimeters derived from Sentinel-2 multi-spectral images and backscatter signal in SAR Sentinel-1 data. The analysis will be carried out in Google Earth Engine.

Semi-automatic fitting of covariance functions in 1D and 2D

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Docente

Giovanna Venuti (mail)

Referente del progetto

Mirko Reguzzoni ( mail)

Area di ricerca

Metodologie e architetture software avanzate

Keyword (max 3 separate da virgola)

Covariance-functions, Least-squares, Stochastic-modeling

Descrizione (max 500 caratteri)

The goal is to write a graphical user interface that supports the covariance modelling in 1D and 2D (in both planar and spherical domain) for stochastic interpolation methods. The software has to read the available data, compute the empirical covariance function, show a set of possible positive definite models and, for each of them, allow the manual setting of their parameters. When changing these parameters the corresponding covariance function has to be visualized and, when the user is satisfied by the manual fitting, an automatic least-squares adjustment has to be performed.