Economic Impacts of Forest Storms—Taking Stock of After-Vaia Situation of Local Roundwood Markets in Northeastern Italy

Udali, Alberto; Andrighetto, N.; Grigolato, Stefano; Gatto, Paola

doi:10.3390/f12040414

Cited by 18 publications

(13 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The study area coincides with the Italian area hits by the VAIA windstorm as reported by Chirici et al (2018) [47] in the following Regions of Italy: Trentino Alto Adige, Veneto, Friuli Venezia Giulia, Lombardia, Piemonte, and Valle d'Aosta (Figure 1), for a total of 67,000 km 2 covered by forest for 144,651.1 ha following the FAO forest definition [48,49]. The VAIA storm hit the area in the night between 28 and 29 October 2018 with winds up to 200 km/h [45].…”

Section: Study Area and Vaia Windstormsupporting

confidence: 71%

See 1 more Smart Citation

Estimating VAIA Windstorm Damaged Forest Area in Italy Using Time Series Sentinel-2 Imagery and Continuous Change Detection Algorithms

Giannetti

Pecchi

Travaglini

et al. 2021

Forests

View full text Add to dashboard Cite

Mapping forest disturbances is an essential component of forest monitoring systems both to support local decisions and for international reporting. Between the 28 and 29 October 2018, the VAIA storm hit the Northeast regions of Italy with wind gusts exceeding 200 km h−1. The forests in these regions have been seriously damaged. Over 490 Municipalities in six administrative Regions in Northern Italy registered forest damages caused by VAIA, that destroyed or intensely damaged forest stands spread over an area of 67,000 km2. The present work tested the use of two continuous change detection algorithms, i.e., the Bayesian estimator of abrupt change, seasonal change, and trend (BEAST) and the continuous change detection and classification (CCDC) to map and estimate forest windstorm damage area using a normalized burned ration (NBR) time series calculated on three years Sentinel-2 (S2) images collection (i.e., January 2017–October 2019). We analyzed the accuracy of the maps and the damaged forest area using a probability-based stratified estimation within 12 months after the storm with an independent validation dataset. The results showed that close to the storm (i.e., 1 to 6 months November 2018–March 2019) it is not possible to obtain accurate results independently of the algorithm used, while accurate results were observed between 7 and 12 months from the storm (i.e., May 2019 – October 2019) in terms of Standard Error (SE), percentage SE (SE%), overall accuracy (OA), producer accuracy (PA), user accuracy (UA), and gmean for both BEAST and CCDC (SE< 3725.3 ha , SE% < 9.69 , OA > 89.7, PA and UA > 0.87, gmean > 0.83).

show abstract

Section: Study Area and Vaia Windstormsupporting

confidence: 71%

“…), and Pinus (Pinus spp. ), however some damages were reported also in broadleaves forests such as in beech stands (Fagus sylvatica L.) [48]. Preliminary field recognition and manual photointerpretation of satellite data showed that a total of 42.525 ha of forests were damaged by the storm [47,49].…”

Section: Study Area and Vaia Windstormmentioning

confidence: 99%

Estimating VAIA Windstorm Damaged Forest Area in Italy Using Time Series Sentinel-2 Imagery and Continuous Change Detection Algorithms

Giannetti

Pecchi

Travaglini

et al. 2021

Forests

View full text Add to dashboard Cite

show abstract

“…The Vaia storm, which occurred in Northeastern Italy at the end of October 2018, felled large volumes of timber causing serious ecological and financial losses, with unexpected challenges for forest managers. The wind gusts exceeded 200 km h −1 ; over 490 Municipalities in six administrative Regions registered forest damages over an area of 67,000 km 2 [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

Estimated Biomass Loss Caused by the Vaia Windthrow in Northern Italy: Evaluation of Active and Passive Remote Sensing Options

Laurin

Puletti²,

Tattoni

et al. 2021

Remote Sensing

View full text Add to dashboard Cite

Windstorms are a major disturbance factor for European forests. The 2018 Vaia storm, felled large volumes of timber in Italy causing serious ecological and financial losses. Remote sensing is fundamental for primary assessment of damages and post-emergency phase. An explicit estimation of the timber loss caused by Vaia using satellite remote sensing was not yet undertaken. In this investigation, three different estimates of timber loss were compared in two study sites in the Alpine area: pre-existing local growing stock volume maps based on lidar data, a recent national-level forest volume map, and an novel estimation of AGB values based on active and passive remote sensing. The compared datasets resemble the type of information that a forest manager might potentially find or produce. The results show a significant disagreement in the different biomass estimates, related to the methods used to produce them, the study areas characteristics, and the size of the damaged areas. These sources of uncertainty highlight the difficulty of estimating timber loss, unless a unified national or regional European strategy to improve preparedness to forest hazards is defined. Considering the frequent impacts on forest resources that occurred in the last years in the European Union, remote sensing-based surveys targeting forests is urgent, particularly for the many European countries that still lack reliable forest stocks data.

show abstract

“…Considering the aforementioned issues, the post-windthrow management should provide for rapid and efficient salvage logging operations, in order to quickly remove timber from damaged stands and limit the economic loss [7]. Salvage logging implementation is still a matter of debate, since it was reported that it may cause negative impacts on forest communities [8].…”

Section: Introductionmentioning

confidence: 99%

Standardized wooden system for timber internal tension simulation

Sforza

Marchi

Grigolato

et al. 2021

20th International Scientific Conference Engineering for Rural Development Proceedings

Self Cite

View full text Add to dashboard Cite

Forest operations performed after natural disturbances occurrence can be highly dangerous due to the critical environmental conditions. Only specialised operators can address such challenging situations. However, the high-quality training activities needed to train forestry operators are not easily feasible in real conditions. The implementation of an engineering system that simulates the complex context of salvage tasks can be a valid solution to prepare operators in a controlled environment. The simulation of critical issues in the use of damaged forest areas, typically represented by logs subjected to a typical stress situation, such as tensile or compressive stress levels, will be carried out through the design of a mobile system for simulation of tensions in timber. The proposed solution aims to define a modular wooden structure to be realized with standard logs available at the logging site to be versatile and safe. The structure will be provided with sensors and load cells that will show the exact level of the stress applied to the logs during the cutting simulation. To this aim, computer analyses with finite element models have been conducted to design a solution that considers multiple parameters, such as log dimensions, tree species, maximum load bearing capacity of the structure and defines an optimal range of design solutions. The numerical procedure recreates the actual stress level developed in collapsed trees, or other unfavourable situations, which might lead to unexpected hazardous condition for the forest operator. The obtained structure must fulfil different requirements: low weight structure, in order to keep the realization, fast assembly/disassembly operations and assure a sufficient safety level according to typical design provisions of real structures. The results provided in this work show that the proposed technique has been accomplished and a first full-scale prototype has been realized and tested.

show abstract

Economic Impacts of Forest Storms—Taking Stock of After-Vaia Situation of Local Roundwood Markets in Northeastern Italy

Cited by 18 publications

References 15 publications

Estimating VAIA Windstorm Damaged Forest Area in Italy Using Time Series Sentinel-2 Imagery and Continuous Change Detection Algorithms

Estimating VAIA Windstorm Damaged Forest Area in Italy Using Time Series Sentinel-2 Imagery and Continuous Change Detection Algorithms

Estimated Biomass Loss Caused by the Vaia Windthrow in Northern Italy: Evaluation of Active and Passive Remote Sensing Options

Standardized wooden system for timber internal tension simulation

Contact Info

Product

Resources

About