Work

High order singular value decomposition for plant diversity estimation

Year: 2021

Type: article

Abstract: We propose a new method to estimate plant diversity with Rényi and Rao indexes through the so called High Order Singular Value Decomposition (HOSVD) of tensors. Starting from NASA multi-spectral images we evaluate diversity and we compare original diversity estimates with those realized via the HOSVD compression methods for big data. Our strategy turns out to be extremely powerful in terms of memory storage and precision of the outcome. The obtained results are so promising that we can support the efficiency of our method in the ecological framework.

Source: Bollettino Della Unione Matematica Italiana

DOI: 10.1007/s40574-021-00300-w

Authors: Alessandra Bernardi, Martina Iannacito, Duccio Rocchini

Institutions: University of Trento, Centre Inria de l'université de Bordeaux, Czech University of Life Sciences Prague, University of Bologna

Language: English

Topic: Tensor decomposition and applications

Subfield: Computational Mathematics

Field: Mathematics

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $2,780

Funders: Istituto Nazionale di Alta Matematica "Francesco Severi", Università degli Studi di Trento