Shrub clearing and extensive livestock as a strategy for enhancing ecosystem services in degraded Mediterranean mid-mountain areas.

Land abandonment in the Mediterranean mountains since the 20th century has led to a reduction of ecosystem services, due to revegetation and homogenization of the landscape. To counteract these effects, the regional administration of La Rioja in Spain initiated a Plan for Shrub Clearing (PSC) combined with extensive livestock grazing in 1986, which is still in action today. This study analyses the effects of pairing clearing with grazing in an experimental area of the Leza valley (Iberian System) on: (i) the landscape structure and structural diversity; (ii) the production of pasture; (iii) fire control; (iv) soil organic carbon sequestration (also considering soil environmental types); (v) surface water resources.

SpaSSA: Superpixelwise Adaptive SSA for Unsupervised Spatial-Spectral Feature Extraction in Hyperspectral Image.

Singular spectral analysis (SSA) has recently been successfully applied to feature extraction in hyperspectral image (HSI), including conventional (1-D) SSA in spectral domain and 2-D SSA in spatial domain. However, there are some drawbacks, such as sensitivity to the window size, high computational complexity under a large window, and failing to extract joint spectral-spatial features. To tackle these issues, in this article, we propose superpixelwise adaptive SSA (SpaSSA), that is superpixelwise adaptive SSA for exploiting local spatial information of HSI.

Embedded product authentication codes in additive manufactured parts: Imaging and image processing for improved scan ability.

The layer-by-layer printing process of additive manufacturing methods provides new opportunities to embed identification codes inside parts during manufacture. These embedded codes can be used for product authentication and identification of counterfeits. The availability of reverse engineering tools has increased the risk of counterfeit part production and new authentication technologies such as the one proposed in this paper are required for many applications including aerospace components and medical implants and devices.

A Novel Intelligent Computational Approach to Model Epidemiological Trends and Assess the Impact of Non-Pharmacological Interventions for COVID-19.

The novel coronavirus disease 2019 (COVID-19) pandemic has led to a worldwide crisis in public health. It is crucial we understand the epidemiological trends and impact of non-pharmacological interventions (NPIs), such as lockdowns for effective management of the disease and control of its spread. We develop and validate a novel intelligent computational model to predict epidemiological trends of COVID-19, with the model parameters enabling an evaluation of the impact of NPIs.

Adaptive Distance-Based Band Hierarchy (ADBH) for Effective Hyperspectral Band Selection.

Band selection has become a significant issue for the efficiency of the hyperspectral image (HSI) processing. Although many unsupervised band selection (UBS) approaches have been developed in the last decades, a flexible and robust method is still lacking. The lack of proper understanding of the HSI data structure has resulted in the inconsistency in the outcome of UBS.