Sentinel-2 and PRISMA satellite data for urban land classification in Tuscany region (TUS:CAN PROJECT)

The TUS:CAN project, part of the ASI program "Innovation for Downstream Preparation - Public Administrations," focuses on sustainable urban planning through the classification of man-made materials using multispectral and hyperspectral satellite data. The project aims at mapping the land cover of natural and artificial materials in urban and suburban areas using 10m-hypersharpened Sentinel-2 data with a Random Forest classifier. PRISMA hyperspectral data further categorize artificial materials, with ground truth spectral signatures collected for accuracy. The classification accuracy is finally validated using aerial hyperspectral data from Itres CASI-1500 and SASI-600 sensors.

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Publication Details

Published
2024-11-13
DOI
https://doi.org/10.1117/12.3030965
Primary Topic
Remote Sensing and Land Use
Type
article
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article

Sentinel-2 and PRISMA satellite data for urban land classification in Tuscany region (TUS:CAN PROJECT)

Luisa Beltramone, Riccardo Salvini, Andrea Garzelli, Andrea Rindinella et al.
Remote Sensing and Land Use
article

Sentinel-2 and PRISMA satellite data for urban land classification in Tuscany region (TUS:CAN PROJECT)

Luisa Beltramone, Riccardo Salvini, Andrea Garzelli, Andrea Rindinella, Claudio Vanneschi, Luigi D'Amato, Laura Candela, Ilaria Tabarrani
article en

Abstract

The TUS:CAN project, part of the ASI program "Innovation for Downstream Preparation - Public Administrations," focuses on sustainable urban planning through the classification of man-made materials using multispectral and hyperspectral satellite data. The project aims at mapping the land cover of natural and artificial materials in urban and suburban areas using 10m-hypersharpened Sentinel-2 data with a Random Forest classifier. PRISMA hyperspectral data further categorize artificial materials, with ground truth spectral signatures collected for accuracy. The classification accuracy is finally validated using aerial hyperspectral data from Itres CASI-1500 and SASI-600 sensors.

University of Siena (IT), Agenzia Spaziale Italiana (IT), Regione Toscana
Sustainable cities and communities
Openalex Percentile: Top 76%
Remote Sensing and Land Use
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Sentinel-2 and PRISMA satellite data for urban land classification in Tuscany region (TUS:CAN PROJECT) — Luisa Beltramone, Riccardo Salvini, et al. · (2024) | TGRS Research Map | TGRS