Good afternoon, my name is Vanina Fisore, I'm a researcher at ITACHA, a center of applied research devoted to support humanitarian activities in response to natural disasters by means of remote sensing techniques. ITACHA is based in Italy. The work I'm going to present today regards the possible

improvements offered by aerial LiDAR technology in the knowledge of avalanche phenomena. This last can in fact provide high resolution information about topography, which is one of the main factors influencing avalanche formation and behavior through the identification and characterization of more impervious zones.

So in this context the present work describes an operative application of the use of a high point density aerial LiDAR data in support to avalanche events prevention and risk mitigation.

This study area is located at the Italian-French state border along an important cross-border communication route. The name of the locality is Colle de la Matalena, nearby the village of Argenteira. As you can see from the pictures, the area has a very complex geomorphology with very high slope values. Due to the extreme environmental conditions,

no tree vegetation cover is present for majority of the area. Here in the winter season and during heavy snowfalls, a big part of the road is involved in intense avalanche events that negatively impact on local and border traffic. At present, in order to maintain the safety

conditions of the road, regular closure periods occur quite often and can be very long, with consequent negative effects on socio-economic activities. So for this reason regional administration decided to adopt a control activity on priority areas

together with artificial detachment methods. The artificial detachment of the snowpack at a time will in fact reduce the road closing time span and of course minimize the risk related to people and road safety. For this reason regional administrations have

activated the avalanche artificial detachment intervention plan in order to prevent and manage the avalanche risk in the study area. The plan provides a detailed description of the area with specific focus on avalanche sites, identifying 14 of these last as actually affecting the cross

border route annually. Moreover, the plan describes artificial detachment systems to be used and the methodology followed during artificial snowpack detachment. Specifically, detachment procedures within identified avalanche sites will be activated at a certain threshold

of snowpack depth corresponding to 30 centimeters. This will guarantee to generate smaller and controlled snowmass movements and consequently to avoid the formation of excessive snow thickness from which greater avalanche could generate. The threshold will be observed directly from the

road by remote observation on ad-hoc snowpulse markers positioned within the highest parts of detachment areas of avalanche sites. When this threshold is observed then detachment procedures

are activated with simultaneous closure of the road so as to avoid the danger and risk of larger proportions avalanche formation. With this premises main aim of the present work was first to provide a high quality geomorphological characterization of the area necessary

for involved authorities to activate the artificial detachment intervention plan and second to investigate capabilities and limits of the LiDAR technology in the identification of avalanche sites only relying on geomorphological information directly derived by LiDAR data processing.

Performed analysis regarded first a series of basic cartographic data contained within the intervention plan specifically a geodatabase containing feature classes was adopted. Contained information are relative to general information about the area such as road network

administrative limits land cover and hydrology and to more specific information regarding avalanche sites such as snowpack detachment areas positions avalanche extension identified

by different methods snowball positions artificial detachment systems positions etc. So all these data were used as reference data managed in in a GIS environment and used to validate the other data derived from LiDAR data processing. As regard to LiDAR data acquisition

the aerial LiDAR mission was carried out on the 6th of October 2019 before the beginning of the winter season and before any snowfall event. Raw LiDAR point cloud was pre-processed using terra-scan application for point cloud classification and filtration due to the

morphological and vegetation characterization of the slope a geometrical LiDAR classification was preferred instead of a full waveform data processing. The slope in fact mainly presents exposed rocks with no vegetation with a small isolated spot of bushes and some conifer trees.

For this reason the 80% of the data sets taken can be considered as ground point cloud with small areas that needs more classification algorithms. Digital terrain models and digital

surface model with 0.5 meters pixel sites were then obtained. Figures shows the part of the slope presenting tree cover vegetation so as to appreciate the difference between the two data.

In order to better characterize the area from a geomorphological point of view some terrain analyses were performed with saggages. The Optane DTM was used to compute slope aspect wind exposure and convexity and then some descriptive statistics computed for the avalanche detachment areas contained

within available reference data. As you can see all detachment areas are within the range of 30 and 14 degrees of slope and mainly some southwest oriented. As regard to the convexity

analysis values above zero normally describes convex profiles while values below zero concave profiles. Reported statistics shows that majority of detachment areas have positive values those convex profiles. Obtained wind exposition index values show that all detachment areas

present positive values above one so are exposed to wind whereas no accumulation due to wind action is in fact more likely. Moreover flow accumulation analysis was computed for the area to identify watersheds position in order to show if with the only use of

either derived data identification of position of already known avalanche sites was achievable. So surface depressions within the input DTM were first identified and then filled for the world area by using the field sync module. Subsequently the accumulated flow was obtained

by using the flow accumulation module. Validation of obtained results was then performed through comparison by overlapping with available reference cartographic data. Results show that areas crossed by avalanche events were well identified. Consequently the channel network

generation of the study area was possible as demonstrated by evaluation of reference cartographic data as you can see in the map on the right. The analysis identified all the areas crossed by avalanche events reported in the intervention plan providing information

about the position of the avalanche sites. Instead no information was achievable about the extension of the potential sliding area since this list also depends on snow parameters such as snow depth, snowpack structure and other. Finally in order to understand if

derived data by themselves were sufficient to identify potential avalanche detachment areas only relying on geomorphological parameters a graphical grid covering the whole study area was generated. Statistics about mean values of slope aspect convexity and wind exposure

were then computed within the graticule cells with the aim of identifying potential detachment areas. Results as displayed in the map shows that almost all detachment areas of the reference data

were identified but also that a great overestimation of this list is present. Again metric parameters about snowpack structure results to be necessary. As requested by regional authorities involved in the avalanche control activities the high

resolution three-dimensional terrain model of the study area was also obtained by using global mapper software. Main conclusion of the work can be that the processing of lighter data permitted to obtain high resolution derived data in particular high resolution terrain models were

generated and geomorphological characterization of the area was obtained. High resolution three-dimensional digital terrain models were also obtained. Then a second kind of analysis was performed to understand capabilities and limits of the LIDAR technology in the identification

of the potential avalanche detachment areas only relying on geomorphological information directly derived by LIDAR data processing. Obtained results showed that position of the avalanche sites were correctly identified while no information could be obtained about the

extension of the sliding areas since this list also depends on snow parameters. The same can be said for detachment areas identification not possible only considering geomorphological parameters. Potentialities of the adopted approach can be identified in the following. A further area

LIDAR acquisition during the winter season and with snow presence on the ground would allow to know snowpack elevation value and the knowledge of such value would permit consequently to derive snow depth information at detachment areas and then better identified together with

already computed geomorphological parameters potential detachment areas. Then area LIDAR acquisitions done before and after an avalanche events would permit to apply a change detection analysis

allowing the measurement of the extension of detachment and sliding areas. Thank you for your attention.