Alvar Aalto is a cloud-based application for the reconnaissance and mapping of Ailanthus altissima. The system combines a GIS-prepared training and control dataset (Aalto) with the Google Earth Engine processing script (Alvar), which retrieves multispectral and thermal satellite imagery, extracts key spectral and topographic features, and performs large-scale classification over an area of interest using established machine-learning methods. The output consists of a classified raster map and vectorized polygons of potential A. altissima presence, supporting the assessment of tree invasion patterns. The Alvar algorithm is based on the assumption that Sentinel-2 imagery, although only barely sufficient in resolution, can still be exploited to detect the presence of such trees.

AlvarAalto 1.0 beta

MARCO CIOLFI
Primo
Software
;
FRANCESCA CHIOCCHINI
Membro del Collaboration Group
;
MARCO LAUTERI
Membro del Collaboration Group
;
PAOLA POLLEGIONI
Membro del Collaboration Group
2025

Abstract

Alvar Aalto is a cloud-based application for the reconnaissance and mapping of Ailanthus altissima. The system combines a GIS-prepared training and control dataset (Aalto) with the Google Earth Engine processing script (Alvar), which retrieves multispectral and thermal satellite imagery, extracts key spectral and topographic features, and performs large-scale classification over an area of interest using established machine-learning methods. The output consists of a classified raster map and vectorized polygons of potential A. altissima presence, supporting the assessment of tree invasion patterns. The Alvar algorithm is based on the assumption that Sentinel-2 imagery, although only barely sufficient in resolution, can still be exploited to detect the presence of such trees.
2025
Istituto di Ricerca sugli Ecosistemi Terrestri - IRET
Ailanthus altissima, Copernicus Sentinel-2, Distribution Modeling
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/557749
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