High order singular value decomposition for plant diversity estimation

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 compare original estimates those realized via HOSVD compression methods for big data. Our strategy turns out be extremely powerful in terms memory storage precision outcome. The obtained results are promising that can support efficiency our ecological framework.