Soil moisture is an important parameter in many fields, including agriculture, climatology, hydrology, and geohazards. Accurate and high spatial resolution soil moisture estimation can improve our understanding of hydrological processes, and climatic interaction, and a more complete view of the domain. Soil moisture estimation can enhance our understanding of preparedness for natural hazards such as landslides, sinkholes, and subsidence. Single-dual polarimetric data is widely used for assessing and monitoring soil moisture due to the availability of datasets. This research proposes a synergized approach using the change detection method based on backscatter information using SAOCOM L-Band Synthetic Aperture Radar (SAR) datasets from 2021 to 2023 to estimate soil moisture and ground deformation using Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) using CosmoSkyMED X-Band datasets from 2011 to 2022. We present a case study of the Petacciato landslide, Molise Region, Italy. The Petacciato landslide is a coastal area in Europe highly prone to mass movements. It is in the northwestern sector of the Molise region (central Italy) in the outermost portion of the central-southern Apennine chain. Timeseries soil moisture results were further compared with the historical open-source meteorological datasets. Precipitation events lead to the most soil moisture that is observed between November to February months. The average ground deformation (LOS velocity) observed on unstable slopes ranged from -1 mm/year to -20 mm/year in the study area.
Assessing the correlation of Time-Series Soil Moisture and Ground Deformation At Petacciato Landslide, Italy / Rana, Divyeshkumar; Mazzanti, Paolo; Bozzano, Francesca. - (2024). (Intervento presentato al convegno The European Geosciences Union (EGU) 2024 tenutosi a Vienna, Austria) [10.5194/egusphere-egu24-912].
Assessing the correlation of Time-Series Soil Moisture and Ground Deformation At Petacciato Landslide, Italy
Divyeshkumar Rana
Primo
Conceptualization
;Paolo MazzantiSecondo
Writing – Review & Editing
;Francesca BozzanoUltimo
Writing – Review & Editing
2024
Abstract
Soil moisture is an important parameter in many fields, including agriculture, climatology, hydrology, and geohazards. Accurate and high spatial resolution soil moisture estimation can improve our understanding of hydrological processes, and climatic interaction, and a more complete view of the domain. Soil moisture estimation can enhance our understanding of preparedness for natural hazards such as landslides, sinkholes, and subsidence. Single-dual polarimetric data is widely used for assessing and monitoring soil moisture due to the availability of datasets. This research proposes a synergized approach using the change detection method based on backscatter information using SAOCOM L-Band Synthetic Aperture Radar (SAR) datasets from 2021 to 2023 to estimate soil moisture and ground deformation using Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) using CosmoSkyMED X-Band datasets from 2011 to 2022. We present a case study of the Petacciato landslide, Molise Region, Italy. The Petacciato landslide is a coastal area in Europe highly prone to mass movements. It is in the northwestern sector of the Molise region (central Italy) in the outermost portion of the central-southern Apennine chain. Timeseries soil moisture results were further compared with the historical open-source meteorological datasets. Precipitation events lead to the most soil moisture that is observed between November to February months. The average ground deformation (LOS velocity) observed on unstable slopes ranged from -1 mm/year to -20 mm/year in the study area.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.