Self-taught Object Localization with Deep Networks

This paper introduces self-taught object localization, a novel approach that leverages deep convolutional networks trained for whole-image recognition to localize objects in images without additional human supervision, i.e., without using any ground-truth bounding boxes for training. The key idea is to analyze the change in the recognition scores when artificially masking out different regions of the image. The masking out of a region that includes the object typically causes a significant drop in recognition score. This idea is embedded into an agglomerative clustering technique that generates self-taught localization hypotheses. Our object localization scheme outperforms existing proposal methods in both precision and recall for small number of subwindow proposals (e.g., on ILSVRC-2012 it produces a relative gain of 23.4% over the state-of-the-art for top-1 hypothesis). Furthermore, our experiments show that the annotations automatically-generated by our method can be used to train object detectors yielding recognition results remarkably close to those obtained by training on manually-annotated bounding boxes.Comment: WACV 201

Estimating soil degradation in montane grasslands of North-eastern Italian Alps (Italy)

Grasslands cover a large portion of the terrestrial ecosystems, and are vital for biodiversity conservation, environmental protection and livestock husbandry. However, grasslands are degraded due to unreasonable management worldwide, i.e., soil erosion indirectly due to the damage of overgrazing on vegetation coverage and soil texture. An in-depth investigation is necessary to quantify soil erosion in alpine pastures, in order to manage grasslands more sustainably. In this work, we collected freely available satellite images and carried out intensive field surveys for the whole Autonomous Province of Trento (Northeastern Italian Alps) in 2016. The area (and volume) of soil erosions were then estimated and shown in maps. The average of the depths of soil erosion measured in field was used as a reference for estimating soil erosion of the entire study area. High-resolution DEMs difference in soil surface conditions was also computed in two representative areas between pre- and post-degradation to estimate the volume and the average depth of eroded soils. The degradation of soil in the study areas has been estimated in 144063 m2 and an estimated volume of 33610 ± 1800 m3. Results indicate that our procedure can serve as a low-cost approach for a rapid estimation of soil erosion in mountain areas. Mapping soil erosion can improve the sustainability of grazing management system and reduce the risk of pastureland degradation at large spatial scales

Development of a novel approach for sediment connectivity analysis in debris-flow prone catchments under managed and unmanaged conditions

I processi torrentizi sono tra i principali attori nella produzione e mobilitazione del sedimento in un bacino idrografico montano. Diventa quindi importante, nelle fasi di pianificazione delle strategie di mitigazione del rischio idrogeologico, approfondire e valutare la quantit\ue0 di sedimento disponibile e le potenziali dinamiche di mobilitazione. Negli ultimi decenni sono stati sviluppati numerose metodologie e modelli numerici per valutare la dinamica di produzione e mobilitazione del sedimento in bacini idrografici alpini. In questo contesto, l\u2019Indice di Connettivit\ue0 del sedimento (IC) consente di analizzare il collegamento esistente tra le aree sorgente di sedimento e il reticolo idrografico (oppure direttamente con le sezioni di chiusura). L\u2019indice di connettivit\ue0 \ue8 un indice basato sull\u2019analisi di dati raster che permette un\u2019applicazione rapida, richiedendo solamente un DTM come dato di input. Il risultato \ue8 una mappa della connettivit\ue0 che evidenzia le canalizzazioni preferenziali lungo l\u2019intera area di studio. L\u2019interpretazione dell\u2019indice di connettivit\ue0 \ue8 basata soprattutto sull\u2019analisi e interpretazione del dato cartografico. Per espandere le potenzialit\ue0 di questo indice, questa tesi propone una nuova metodologia per analizzare e interpretare l\u2019 indice di connettivit\ue0 del sedimento. Questo nuovo metodo \ue8 basato sull\u2019analisi dell\u2019IC, e delle variabili che lo compongono, lungo profili longitudinali selezionati. La metodologia presentata in questa tesi, \ue8 stata applicata per valutare la connettivit\ue0 su due bacini idrografici, di cui uno caratterizzato dalla presenza di opere di mitigazione (Saint Antoine \u2013 Dipartimento della Savoia - Francia) e uno privo di opere ( Rio Soial \u2013 Provincia Autonoma di Trento - Italia). L\u2019analisi integrata effettuata sul bacino idrografico privo di opere (Rio Soial), ha lo scopo di comprendere come l\u2019evoluzione geomorfologica dell\u2019area influenzi la computazione dell\u2019indice di connettivit\ue0 e se quest\u2019ultimo poss\ue0 aiutare a predirre future tendenze geomorfologiche. I risultati fanno emergere una capacit\ue0 dell\u2019indice di connettivit\ue0 di catturare l\u2019evoluzione del bacino a seguito di sei eventi di colata detritica avvenuti nel periodo analizzato. Inoltre, l\u2019analisi longitudinale ha permesso di confermare la potenzialit\ue0 dell\u2019 IC nel predirre potenziali dinamiche di deposizione in una specifica area del bacino analizzato. L\u2019analisi operata sul bacino sistemato con opere, ha l\u2019obiettivo di comprendere e analizzare l\u2019interazione dell\u2019indice di connettivit\ue0 con la presenza (e assenza) di opere di sistemazione idraulica. In questo caso studio, l\u2019indice evidenzia differenze sostanziali tra i segmenti sistemati con opere e quelli privi di opere. Differenza che \ue8 stata rilevata anche analizando gli effetti di una colata detirtica avvenuta durante l\u2019arco temporale analizzato. Concludendo, dalle analisi eseguite si pu\uf2 affermare come l\u2019introduzione di un\u2019analisi longitudinale dell\u2019indice possa consentire nuove opportunit\ue0 di utilizzo, in particolare durante le fasi di analisi e pianificazione delle strategie di mitigazione del rischio idrogeologico

Debris-flow channel evolution at the triggering and transport zone: learning from a very active case study in the Dolomites

Understanding morphology changes and sediment spreading along a debris-flow channel is a key step in hazard mitigation planning. This research analyses a 10 years evolution of erosion/deposition patterns in an active debris-flow upper channel located on the Dolomites (rio Soial, Val di Fassa, Trento, Italy). The morphologic evolution of the channel has been analysed performing a Difference of DEM (DoD) (Cavalli et al., 2015; Wheaton et al., 2010). DEM differencing enables quantitative and spatially-distributed representation of erosion and deposition within the analysed time window, at both channel reach and the catchment scale. In this study, the analysis were performed using two high-resolution Digital Terrain Models (DTMs). The 2008 LiDAR-derived DTM of the Autonomous Province of Trento with a DTM created from a UAV-based point cloud from July 2018 were compared. This data set was also used to determine the changes in the sediment Connectivity Index (CI), which explains the existing degree of linkage between sediment sources and channel network (Cavalli et al., 2013). During the period 2008-2018 five debris flow events have occurred. Each associated rainstorm was analysed in order to assess the evolution of the threshold rain intensities in relation to the evolution of the channel-valley morphology. The results on the CI analysis show a general decrease in CI values, meaning an increased disconnection between the head basin areas and the outlet at the end of the transport reach. Also, the rain thresholds show a slight increase after the lasts event, indicating a gradual stabilization of the basin and a possible reduction of the expected frequency of debris flow events

Décryptage de l'indice de connectivité sédimentaire et des faciès d'érosion dans un bassin versant à lave torrentielle

International audienceUnderstanding sediment connectivity and erosion pattern are fundamental in order to assess in a proper way actual and potential future hazard in debris flow prone areas. In this work, we propose a novel way to analyse and decipher the Connectivity Index (CI) applied in the Saint Antoine catchment, located in the French Alps. We conceptualised a procedure for the extraction of each variable involved in the CI computation along the thalweg profile. This new way to analyse CI helps to understand how this index is affected by past debris flow events and presence or absence of protection measures, also comparing protected reaches against non-protected reaches. This method opens new opportunity to use the Connectivity Index as an effective instrument to catch present or future hazard and support the planning of hazard mitigation measures

Décryptage de l'indice de connectivité sédimentaire et des faciès d'érosion dans un bassin versant à lave torrentielle

International audienceUnderstanding sediment connectivity and erosion pattern are fundamental in order to assess in a proper way actual and potential future hazard in debris flow prone areas. In this work, we propose a novel way to analyse and decipher the Connectivity Index (CI) applied in the Saint Antoine catchment, located in the French Alps. We conceptualised a procedure for the extraction of each variable involved in the CI computation along the thalweg profile. This new way to analyse CI helps to understand how this index is affected by past debris flow events and presence or absence of protection measures, also comparing protected reaches against non-protected reaches. This method opens new opportunity to use the Connectivity Index as an effective instrument to catch present or future hazard and support the planning of hazard mitigation measures

Morphodynamics and sediment connectivity index in an unmanaged, debris-flow prone catchment: a through time perspective

International audienceTorrential processes are among the main actors responsible for sediment production and mobility in mountain catchments. For this reason, the understanding of preferential pathways for sediment routing has become a priority in hazard assessment and mitigation. In this context, the sediment Connectivity Index (IC) enables to analyse the existing linkage between sediment sources and the selected target (channel network or catchment outlet). The IC is a grid-based index that allows fast computation of sediment connectivity based on landscape information derived from a single Digital Terrain Model (DTM). The index computation is based on the log-ratio between an upslope and a downslope component, including information about drainage area, slope, terrain roughness, and distance to the analysis target (e.g. outlet). The output is a map that highlights the degree of structural connectivity of sediment pathways over analysed catchments. Until now, these maps are however rarely used to help defining debris-flow hazard maps, notably due to a lack of guidelines to interpret the IC spatial distribution. This paper proposes an exploitation procedure along profiles to extract more information from the analysis of mapped IC values. The methodology relies on the analysis of the IC and its component variables along the main channel profile, integrated with information about sediment budgeting derived from Difference of DEMs (DoD). The study of connectivity was applied in the unmanaged sub-catchment (without torrent control works) of the Rio Soial (Autonomous Province of Trento-NE Italy) to understanding the geomorphic evolution of the area after five debris flows (in ten years) and the related changes of sediment connectivity. Using a recent DTM as validation, we demonstrated how an IC analysis over the older DTM can help predicting geomorphic changes and associated hazards. The results show an IC aptitude to capture geomorphic trajectories, anticipate debris flow deposits in a specific channel location, and depict preferential routing pathways.

Deciphering sediment Connectivity Index and erosion pattern in a debris flow catchment

Understanding sediment connectivity and erosion pattern are fundamental in order to assess in a proper way actual and potential future hazard in debris flow prone areas. In this work, we propose a novel way to analyse and decipher the Connectivity Index (CI) applied in the Saint Antoine catchment, located in the French Alps. We conceptualised a procedure for the extraction of each variable involved in the CI computation along the thalweg profile. This new way to analyse CI helps to understand how this index is affected by past debris flow events and presence or absence of protection measures, also comparing protected reaches against non-protected reaches. This method opens new opportunity to use the Connectivity Index as an effective instrument to catch present or future hazard and support the planning of hazard mitigation measures