Monitoring post-fire forest recovery using multi-temporal Digital Surface Models generated from different platforms

Wildfires can greatly affect forest dynamics. Given the alteration of fire regimes foreseen globally due to climate and land use changes, greater attention should be devoted to prevention and restoration activities. Concerning in particular post-fire restoration actions, it is fundamental, together with a better understanding of ecological processes resulting from the disturbance, to define techniques and protocols for long-term monitoring of burned areas. This paper presents the results of a study conducted within an area affected by a stand-replacing crown fire (Verrayes, Aosta (AO), Italy) in 2005, which is part of a long-term monitoring research on post-fire restoration dynamics. We performed a change detection analysis through a time sequence (2008-2015) of DSMs (Digital Surface Models) obtained from LiDAR (ALS - Airborne Laser Scanner) and digital images (UAV - Unmanned Aerial Vehicle flight) to test the ability of the systems (platform + sensor) to identify the ongoing processes. New technologies providing high-resolution information and new devices (i.e. UAV) able to acquire geographic data “on demand” demonstrated great potential for monitoring post disturbance recovery dynamics of vegetation

A collaborative, semantic and context-aware search engine

Search engines help people to find information in the largest public knowledge system of the world: the Web. Unfortunately its size makes very complex to discover the right information. The users are faced lots of useless results forcing them to select one by one the most suitable. The new generation of search engines evolve from keyword-based indexing and classification to more sophisticated techniques considering the meaning, the context and the usage of information. We argue about the three key aspects: collaboration, geo-referencing and semantics. Collaboration distributes storage, processing and trust on a world-wide network of nodes running on users’ computers, getting rid of bottlenecks and central points of failures. The geo-referencing of catalogued resources allows contextualisation based on user position. Semantic analysis lets to increase the results relevance. In this paper, we expose the studies, the concepts and the solutions of a research project to introduce these three key features in a novel search engine architecture.213-21

UAV per la generazione di DSM multi-temporali per il monitoraggio delle dinamiche di ricostituzione post-incendio di aree boschive

Gli incendi boschivi sono uno dei principali disturbi naturali che influenzano le dinamiche degli ecosistemi forestali. Gli effetti degli incendi boschivi possono variare a seconda dell'intensità dell'evento, fino a raggiungere severità tali da determinare la morte dell'intero soprassuolo forestale. L’alterazione del regime degli incendi boschivi prevista a livello globale in relazione ai cambiamenti climatici e di uso del suolo, comporta una sempre maggiore attenzione agli aspetti di prevenzione e ricostituzione delle aree interessate. Nell’ambito, in particolare, della ricostituzione post-incendio, appare fondamentale, oltre all’approfondimento delle conoscenze sui processi ecologici in risposta al disturbo, definire tecniche e protocolli di monitoraggio di lungo periodo. In questo contesto, l’utilizzo di Unmanned Aerial Vehicle (UAV) può essere uno strumento utile allo svolgimento di indagini a media scala in aree interessate da incendi boschivi. Infatti questi strumenti, che offrono la possibilità di installare a bordo sensori di natura diversa, quali camere multispettrali o sensori termici, consentono di effettuare rilievi speditivi e ripetibili nel tempo, fondamentali per analisi multi-temporali delle aree di interesse. In questo articolo vengono presentati i risultati preliminari relativi ad un’indagine condotta all’interno di un’area interessata nel 2005 da un incendio di chioma (Verrayes, AO) nell’ambito di un progetto di monitoraggio di lungo periodo delle dinamiche di ricostituzione post-incendio. E’ stato pertanto realizzato un rilievo speditivo con UAV con camere visibili e multispettrali al fine di generare un modello della superficie (Digital Surface Model – DSM) da confrontare con un precedente modello ottenuto tramite rilievo lidar

Natural Disturbances and Protection Forests: At the Cutting Edge of Remote Sensing Technologies for the Rapid Assessment of Protective Effects against Rockfall

Protection forests can be severely affected by natural disturbances, whose consequences could greatly alter the fundamental ecosystem services they are providing. Assessing and monitoring the status of the protective effects, particularly within disturbed stands, is therefore of vital importance, with timing being a critical issue. Remote sensing technologies (e.g., satellite imagery, LiDAR, UAV) are widely available nowadays and can be effectively applied to quantify and monitor the protective effects of Alpine forests. This is especially important after abrupt changes in forest cover and structure following the occurrence of a disturbance event. In this contribution, we present a brief introduction on remote sensing technologies and their potential contribution to protection forest management, followed by two case studies. In particular, we focus on research areas within protection forests against rockfall affected by windthrow (i.e., the 2018 storm Vaia in the Eastern Italian Alps, where LiDAR and UAV data were used), and forest fires (i.e., the 2017 fall fires in the Western Italian Alps, involving Sentinel-2 image analyses)

Prolongation of survival of dogs with oral malignant melanoma treated by en bloc surgical resection and adjuvant CSPG4-antigen electrovaccination

Reported post-surgery 1-year survival rate for oral canine malignant melanoma (cMM) is around 30%; novel treatments are needed as the role of adjuvant chemotherapy is unclear. This prospective study regards adjuvant electrovaccination with human-CSPG4-encoded plasmid in 23 dogs with resected II/III-staged CSPG4-positive oral cMM compared with 19 dogs with resected only II/III-staged CSPG4-positive oral cMM. Vaccination resulted in 6/12/18/24-month survival rate of respectively 95.6/73.9/47.8/30.4% (MST 684 days, range 78-1694, 8/23 dogs alive) and 6/12/18/24-month DFI rate of respectively 82.6/47.8/26.1/17.4% (DFI 477 days, range 50-1694). Non-vaccinated dogs showed 6/12/18/24-month survival rate of respectively 63.2/26.3/15.8/5.3% (MST 200 days, range 75-1507, 1/19 dogs alive) and 6/12/18/24-month DFI rate of respectively 52.6/26.3/10.5/5.3% (DFI 180 days, range 38-1250). Overall survival and DFI of vaccinated dogs was longer in those <20 Kg. In vaccinated and non-vaccinated dogs local recurrence rate was respectively 34.8% and 42% while lung metastatic rate was respectively 39% and 79%

Genome-wide Analyses Identify KIF5A as a Novel ALS Gene

To identify novel genes associated with ALS, we undertook two lines of investigation. We carried out a genome-wide association study comparing 20,806 ALS cases and 59,804 controls. Independently, we performed a rare variant burden analysis comparing 1,138 index familial ALS cases and 19,494 controls. Through both approaches, we identified kinesin family member 5A (KIF5A) as a novel gene associated with ALS. Interestingly, mutations predominantly in the N-terminal motor domain of KIF5A are causative for two neurodegenerative diseases: hereditary spastic paraplegia (SPG10) and Charcot-Marie-Tooth type 2 (CMT2). In contrast, ALS-associated mutations are primarily located at the C-terminal cargo-binding tail domain and patients harboring loss-of-function mutations displayed an extended survival relative to typical ALS cases. Taken together, these results broaden the phenotype spectrum resulting from mutations in KIF5A and strengthen the role of cytoskeletal defects in the pathogenesis of ALS.Peer reviewe