Zobrazeno 1 - 10
of 22
pro vyhledávání: '"Muzaffer Can İBAN"'
Autor:
Muzaffer Can Iban, Oktay Aksu
Publikováno v:
Remote Sensing, Vol 16, Iss 15, p 2842 (2024)
Wildfire susceptibility maps play a crucial role in preemptively identifying regions at risk of future fires and informing decisions related to wildfire management, thereby aiding in mitigating the risks and potential damage posed by wildfires. This
Externí odkaz:
https://doaj.org/article/56b6cdac5e924798b5b061d3067182d5
Publikováno v:
Frontiers in Environmental Science, Vol 11 (2023)
Extreme heat events are happening more frequently and with greater severity, causing significant negative consequences, especially for vulnerable urban populations around the globe. Heat stress is even more common in cities with dense and irregular p
Externí odkaz:
https://doaj.org/article/1c364910cd184fe8ba1dc8b30bc0d1b8
Publikováno v:
Applied Sciences, Vol 14, Iss 8, p 3484 (2024)
This study delves into the integration of analytic hierarchy process (AHP) and geographic information system (GIS) techniques to identify suitable areas for urban development in six districts within the Mersin Metropolitan Area of Turkey. The specifi
Externí odkaz:
https://doaj.org/article/4ad19e3e997a4e0c834416aba5ca35c9
Autor:
Nicola Amoroso, Roberto Cilli, Davide Oscar Nitti, Raffaele Nutricato, Muzaffer Can Iban, Tommaso Maggipinto, Sabina Tangaro, Alfonso Monaco, Roberto Bellotti
Publikováno v:
Remote Sensing, Vol 15, Iss 10, p 2560 (2023)
PSI data are extremely useful for monitoring on-ground displacements. In many cases, clustering algorithms are adopted to highlight the presence of homogeneous patterns; however, clustering algorithms can fail to consider spatial constraints and be p
Externí odkaz:
https://doaj.org/article/bb330e22b0a245e189cffb6a5818efa1
Publikováno v:
Advances in Space Research. 71:3122-3139
Publikováno v:
Stochastic Environmental Research and Risk Assessment. 37:2243-2270
Autor:
Halit Enes Aydin, Muzaffer Can Iban
Publikováno v:
Natural Hazards. 116:2957-2991
Publikováno v:
Environmental Earth Sciences. 82
Autor:
Muzaffer Can Iban, Erman Şentürk
Publikováno v:
Advances in Space Research. 69:1319-1334
The variation of the ionospheric parameters has a crucial role in space weather, communication, and navigation applications. In this research, we analyze the prediction performance of three machine learning (ML) regression models, decision trees, ran