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Analysis of hail events in agricultural areas using ground information and satellite-based images.

Nina Valsania

Analysis of hail events in agricultural areas using ground information and satellite-based images.

Rel. Stefania Tamea, Matteo Rolle. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Per L'Ambiente E Il Territorio, 2023

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Hailstorms are becoming more intense, resulting in significant losses in the agricultural sector and subsequent economic damages. This happens particularly in Northern Italy, which is a hailstorm prone region due to its morphological structure. However, hailstorms are unpredictable, localized events, making it challenging to quickly determine the extent of the damages they cause. This study aims to explore the feasibility of detecting hail damage in maize crops in Piedmont, Italy, using RADAR Sentinel-1 satellite images. This approach ensures that the results are not influenced by cloud cover, atmospheric events, or diurnal variations. The SAR C-band instrument, capable of detecting vegetation canopy structures, is employed for the purpose of analysing crop fields. By examining meteorological reports between 2016 and 2022, which include ground hail probability maps, potential hailstorm’s locations are identified. Hailstorms are typically characterized by intense precipitation and rapid temperature fluctuations within a short time frame. Thus, the hail events under consideration are selected by comparing temperature and precipitation data from ARPA's meteorological stations, focusing on events with significant temperature differences and high precipitation occurring within a short time window. Confirmation is obtained by cross-referencing newspaper articles. As a result, several hail events affecting maize-growing areas are chosen for analysis. Once the events and locations are determined, the backscatter responses of the area covered by maize crops surrounding the meteorological station is analysed. Additionally, the VH/VV spectral index, which is particularly sensitive to biomass presence, is utilized to assess potential vegetation loss in the analysed region. By comparing different municipal administrative areas, it is possible to determine if certain areas are more severely affected than others. One distinction from previous studies on this topic is the uncertainty regarding whether the hail actually fell in close proximity to the meteorological station, resulting in uncertainty of the location of the hail occurrence. Furthermore, it is essential to consider that the backscatter response depends on various factors, including biomass presence, vegetative phase, vegetation structure, soil moisture conditions, canopy structure, surface roughness, dielectric properties, and water presence. Thus, the backscatter response to hail is not unequivocal since, after the hail event, in some areas an increase in backscatter is found and in other there is a decrease. The response varies based on the maize's growth stage, the presence of residual water from the rainfall event, and environmental conditions such as the drought that severely impacted Piedmont in 2022. A crucial aspect of this analysis involves the satellite coverage over the study area, therefore events with different satellite passage frequencies are compared to mitigate this challenge. When the satellite passes at significantly longer intervals (several days apart), the effects of the hailstorm become less visible, making it more challenging to determine the presence and extent of damages. Overall, the obtained results can be used as a basis for future and more in-depth studies of hail risk factors applicable in agricultural insurance.

Relators: Stefania Tamea, Matteo Rolle
Academic year: 2022/23
Publication type: Electronic
Number of Pages: 147
Corso di laurea: Corso di laurea magistrale in Ingegneria Per L'Ambiente E Il Territorio
Classe di laurea: New organization > Master science > LM-35 - ENVIRONMENTAL ENGINEERING
Aziende collaboratrici: UNSPECIFIED
URI: http://webthesis.biblio.polito.it/id/eprint/27256
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