Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Mehdi Akhoondzadeh"'
Publikováno v:
GIScience & Remote Sensing, Vol 58, Iss 8, Pp 1413-1433 (2021)
InSAR processing is vastly used for land deformation monitoring from the space. Machine learning methods are known as strong tools for data modeling as well as predicting. In this study, we are going to model and predict the future behavior of land s
Externí odkaz:
https://doaj.org/article/7b411387168940398ad980fba9c0947c
Autor:
Mehdi Akhoondzadeh
Publikováno v:
Remote Sensing, Vol 15, Iss 12, p 3061 (2023)
On 6 February 2023, at 1:17:34 UTC, a powerful Mw = 7.8 earthquake shook parts of Turkey and Syria. Investigating the behavior of different earthquake precursors around the time and location of this earthquake can facilitate the creation of an earthq
Externí odkaz:
https://doaj.org/article/d730c9e8ef694c1cb42b4fa3738f5ea8
Autor:
Mehdi Akhoondzadeh, Dedalo Marchetti
Publikováno v:
Remote Sensing, Vol 15, Iss 9, p 2224 (2023)
On 6 February 2023, a powerful earthquake at the border between Turkey and Syria caused catastrophic consequences and was, unfortunately, one of the deadliest earthquakes of the recent decades. The moment magnitude of the earthquake was estimated to
Externí odkaz:
https://doaj.org/article/31456169723342aa90b88d9a51f60c1b
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 7179-7197 (2021)
The soil moisture changes ($\Delta {{\boldsymbol{M}}_{\boldsymbol{v}}}$) have a significant influence on forestry, hydrology, meteorology, agriculture, and climate change. Interferometric synthetic aperture radar (InSAR), as a potential remote sensin
Externí odkaz:
https://doaj.org/article/829ae991e16c4aa089570780d62757b9
Publikováno v:
Frontiers in Earth Science, Vol 10 (2022)
On May 14, 2019, a strong Mw = 7.6 shallow earthquake occurred in Papua New Guinea. This paper explores for the first time the analysis of total electron content (TEC) products measured for 6 months by GPS antenna onboard Swarm satellites, to detect
Externí odkaz:
https://doaj.org/article/f7bc9378cfa24900bb2e6265aed2bed4
Publikováno v:
Mathematics, Vol 10, Iss 19, p 3566 (2022)
The fine particulate matter (PM2.5) concentration has been a vital source of info and an essential indicator for measuring and studying the concentration of other air pollutants. It is crucial to realize more accurate predictions of PM2.5 and establi
Externí odkaz:
https://doaj.org/article/ab2f4128d33d4f91aa29ed657e6a0ecd
Autor:
Mehdi Akhoondzadeh, Angelo De Santis
Publikováno v:
Atmosphere, Vol 13, Iss 7, p 1131 (2022)
So far, many efforts have been made to provide a reliable and robust mechanism for the occurrence of large earthquakes. In recent years, different studies have been conducted on the possible correlation between solar-terrestrial interactions and the
Externí odkaz:
https://doaj.org/article/ba3b3ab081d04cea8f01e8453f544505
Autor:
Mehdi Akhoondzadeh, Dedalo Marchetti
Publikováno v:
Remote Sensing, Vol 14, Iss 13, p 3203 (2022)
Predicting the parameters of upcoming earthquakes has always been one of the most challenging topics in studies related to earthquake precursors. Increasing the number of sensors and satellites and consequently incrementing the number of observable p
Externí odkaz:
https://doaj.org/article/e7b919a48ed844d19d0a835a39ff6845
Publikováno v:
Remote Sensing, Vol 14, Iss 7, p 1582 (2022)
Since the appearance and evolution of earthquake ionospheric precursors are expected to show a nonlinear and complex behaviour, the use of nonlinear predictor models seems more appropriate. This paper proposes a new approach based on deep learning as
Externí odkaz:
https://doaj.org/article/2a236c86ff7c47daaf3f0a7ace4de215
Publikováno v:
Remote Sensing, Vol 13, Iss 2, p 220 (2021)
Wildfires are major natural disasters negatively affecting human safety, natural ecosystems, and wildlife. Timely and accurate estimation of wildfire burn areas is particularly important for post-fire management and decision making. In this regard, R
Externí odkaz:
https://doaj.org/article/0b850bd9cb3b4b89b816b04b88b81798