Zobrazeno 1 - 10
of 16
pro vyhledávání: '"Aleksandra Wrzesniak"'
Autor:
Aleksandra Wrzesniak, Daniele Giordan
Publikováno v:
Geomatics, Natural Hazards & Risk, Vol 8, Iss 2, Pp 1898-1913 (2017)
Despite the support of technological improvements in hazard monitoring and management, the aspect of dissemination of scientific data is still underestimated. Hazard monitoring systems are usually organized in complex networks, composed of automatize
Externí odkaz:
https://doaj.org/article/257931d086154679b02e48f05b915325
Publikováno v:
Remote Sensing, Vol 13, Iss 15, p 3005 (2021)
In the Ferret Valley (NW Italy), anthropic activities coexist close to the Grandes Jorasses massif’s glaciological complex. In the past, break-off events have caused damage to people and infrastructure. These events concerned two specific sectors:
Externí odkaz:
https://doaj.org/article/65f19b21512546978bbf29689199a010
Publikováno v:
Sensors, Vol 19, Iss 10, p 2364 (2019)
Structure from Motion (SfM) is a powerful tool to provide 3D point clouds from a sequence of images taken from different remote sensing technologies. The use of this approach for processing images captured from both Remotely Piloted Aerial Vehicles (
Externí odkaz:
https://doaj.org/article/85f1e2299acd4d7faa443f8cd18576f0
Publikováno v:
Geosciences, Vol 8, Iss 12, p 485 (2018)
Active landslide risk assessment and management are primarily based on the availability of dedicated studies and monitoring activities. The establishment of decision support for the efficient management of active landslides threatening urban areas is
Externí odkaz:
https://doaj.org/article/ba4a99c05d5f434f9aa8e70eaa866d21
Autor:
Aleksandra Wrzesniak, Davide Notti, Daniele Giordan, Niccolo Dematteis, Piernicola Lollino, Francesco Zucca, Nunzio Luciano Fazio
Publikováno v:
Landslides (Berl., Internet) (2021). doi:10.1007/s10346-021-01651-3
info:cnr-pdr/source/autori:Davide Notti, Aleksandra Wrzesniak, Niccolò Dematteis, Piernicola Lollino, Nunzio Luciano Fazio, Francesco Zucca & Daniele Giordan/titolo:A multidisciplinary investigation of deep-seated landslide reactivation triggered by an extreme rainfall event: a case study of the Monesi di Mendatica landslide, Ligurian Alps/doi:10.1007%2Fs10346-021-01651-3/rivista:Landslides (Berl., Internet)/anno:2021/pagina_da:/pagina_a:/intervallo_pagine:/volume
info:cnr-pdr/source/autori:Davide Notti, Aleksandra Wrzesniak, Niccolò Dematteis, Piernicola Lollino, Nunzio Luciano Fazio, Francesco Zucca & Daniele Giordan/titolo:A multidisciplinary investigation of deep-seated landslide reactivation triggered by an extreme rainfall event: a case study of the Monesi di Mendatica landslide, Ligurian Alps/doi:10.1007%2Fs10346-021-01651-3/rivista:Landslides (Berl., Internet)/anno:2021/pagina_da:/pagina_a:/intervallo_pagine:/volume
In November 2016, an extreme rainfall event affected the Ligurian Alps (NW Italy). Consequently, several landslides and debris flows occurred in the upper Tanarello stream basin. In particular, the village of Monesi di Mendatica was severely damaged
The assessment of the surface spatially-distributed three-dimensional (3D) deformation is crucial in landslide monitoring, as it represents the landslide kinematics. However, there is a lack of technologies that can provide this datum effectively and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c1bbbdc3e8f63e70f46ed7c9ce12d7f0
https://doi.org/10.5194/egusphere-egu22-9919
https://doi.org/10.5194/egusphere-egu22-9919
Publikováno v:
Remote Sensing, Vol 13, Iss 3005, p 3005 (2021)
Remote sensing (Basel) (2021). doi:10.3390/rs13153005
info:cnr-pdr/source/autori:Niccolò Dematteis, Daniele Giordan, Fabrizio Troilo, Aleksandra Wrzesniak, Danilo Godone/titolo:Ten-year monitoring of the Grandes Jorasses glaciers kinematics. Limits, potentialities, and possible applications of different monitoring systems/doi:10.3390%2Frs13153005/rivista:Remote sensing (Basel)/anno:2021/pagina_da:/pagina_a:/intervallo_pagine:/volume
Remote sensing (Basel) (2021). doi:10.3390/rs13153005
info:cnr-pdr/source/autori:Niccolò Dematteis, Daniele Giordan, Fabrizio Troilo, Aleksandra Wrzesniak, Danilo Godone/titolo:Ten-year monitoring of the Grandes Jorasses glaciers kinematics. Limits, potentialities, and possible applications of different monitoring systems/doi:10.3390%2Frs13153005/rivista:Remote sensing (Basel)/anno:2021/pagina_da:/pagina_a:/intervallo_pagine:/volume
In the Ferret Valley (NW Italy), anthropic activities coexist close to the Grandes Jorasses massif’s glaciological complex. In the past, break-off events have caused damage to people and infrastructure. These events concerned two specific sectors:
Publikováno v:
Engineering Geology. 303:106655
Publikováno v:
Understanding and Reducing Landslide Disaster Risk ISBN: 9783030607128
Complex landslides are often monitored by multi-instrumental networks. These networks can be coupled with early warning systems that could reduce human, economic and environmental losses. The large amount of data provided by landslides monitoring net
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b5feb36fa6c072c2f432a6efa6689163
https://doi.org/10.1007/978-3-030-60713-5_25
https://doi.org/10.1007/978-3-030-60713-5_25
Publikováno v:
Sensors (Basel, Switzerland)
Sensors
Volume 19
Issue 10
Sensors (Basel) (2019). doi:10.3390/s19102364
info:cnr-pdr/source/autori:Martina Cignetti, Danilo Godone, Aleksandra Wrzesniak, Daniele Giordan/titolo:Structure from Motion Multisource Application for Landslide Characterization and Monitoring: The Champlas du Col Case Study, Sestriere, North-Western Italy/doi:10.3390%2Fs19102364/rivista:Sensors (Basel)/anno:2019/pagina_da:/pagina_a:/intervallo_pagine:/volume
Sensors, Vol 19, Iss 10, p 2364 (2019)
Sensors
Volume 19
Issue 10
Sensors (Basel) (2019). doi:10.3390/s19102364
info:cnr-pdr/source/autori:Martina Cignetti, Danilo Godone, Aleksandra Wrzesniak, Daniele Giordan/titolo:Structure from Motion Multisource Application for Landslide Characterization and Monitoring: The Champlas du Col Case Study, Sestriere, North-Western Italy/doi:10.3390%2Fs19102364/rivista:Sensors (Basel)/anno:2019/pagina_da:/pagina_a:/intervallo_pagine:/volume
Sensors, Vol 19, Iss 10, p 2364 (2019)
Structure from Motion (SfM) is a powerful tool to provide 3D point clouds from a sequence of images taken from different remote sensing technologies. The use of this approach for processing images captured from both Remotely Piloted Aerial Vehicles (