Webbläsaren som du använder stöds inte av denna webbplats. Alla versioner av Internet Explorer stöds inte längre, av oss eller Microsoft (läs mer här: * https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Var god och använd en modern webbläsare för att ta del av denna webbplats, som t.ex. nyaste versioner av Edge, Chrome, Firefox eller Safari osv.

Default user image.

Babak Mohammadi

Doktorand

Default user image.

Application of Machine Learning and Remote Sensing in Hydrology

Författare

  • Babak Mohammadi

Summary, in English

Water is vital to all life on earth, but its management is becoming more difficult owing to the behavior of water in nature such as water dynamics, water movements, and different forms of water in nature. In addition, population growth, the impact of climate change, and the inappropriate use of water resources add more complexity to water resource management. The integration of natural sciences necessitates creative methods in decision sciences, data processing, and modeling methodologies. The prediction of such occurrences is a highly nonlinear problem that requires the use of modern capable techniques. For handling the abovementioned items, we need to use tools capable of solving water-based issues. Machine learning and remote sensing technologies as recently developed technologies have been considered as tools for these solving water-based issues. Additionally, the “Topic” sought to obtain a collection ofrecent studies on the application of machine learning and remote sensing in hydrology.

Avdelning/ar

  • Institutionen för naturgeografi och ekosystemvetenskap

Publiceringsår

2022-06-22

Språk

Engelska

Publikation/Tidskrift/Serie

Sustainability (Switzerland)

Volym

14

Issue

13

Dokumenttyp

Artikel i tidskrift

Förlag

MDPI AG

Ämne

  • Physical Geography
  • Water Engineering

Nyckelord

  • hydrological modeling
  • machine learning
  • Remote sensing

Status

Published

ISBN/ISSN/Övrigt

  • ISSN: 2071-1050