AI-Empowered Physical Inversion of Water Quality and Benthic Parameters from Multi- and Hyperspectral Images

Niroumand-Jadidi, Milad and Gege, Peter (2024) AI-Empowered Physical Inversion of Water Quality and Benthic Parameters from Multi- and Hyperspectral Images. Ocean Optics XXVI, 2024-10-06 - 2024-10-11, Las Palmas de Gran Canaria, Spain.

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Abstract

A new methodology integrated as a new module within the Water Colour Simulator (WASI) software.

Item URL in elib:

https://elib.dlr.de/207537/

Document Type:

Conference or Workshop Item (Poster)

Title:

AI-Empowered Physical Inversion of Water Quality and Benthic Parameters from Multi- and Hyperspectral Images

Authors:

Authors	Institution or Email of Authors	Author's ORCID iD	ORCID Put Code
Niroumand-Jadidi, Milad	milad.niroumand (at) unibo.it	https://orcid.org/0000-0002-9432-3032	UNSPECIFIED
Gege, Peter	peter.gege (at) dlr.de	https://orcid.org/0000-0003-0939-5267	UNSPECIFIED

Date:

8 October 2024

Refereed publication:

Open Access:

Yes

Gold Open Access:

In SCOPUS:

In ISI Web of Science:

Status:

Published

Keywords:

Water, Remote Sensing, Inverse modelling, Artificial Intelligence, Software, WASI

Event Title:

Ocean Optics XXVI

Event Location:

Las Palmas de Gran Canaria, Spain

Event Type:

international Conference

Event Start Date:

6 October 2024

Event End Date:

11 October 2024

Organizer:

The Oceanography Society (TOS)

HGF - Research field:

Aeronautics, Space and Transport

HGF - Program:

Space

HGF - Program Themes:

Earth Observation

DLR - Research area:

Raumfahrt

DLR - Program:

R EO - Earth Observation

DLR - Research theme (Project):

R - Optical remote sensing

Location:

Oberpfaffenhofen

Institutes and Institutions:

Remote Sensing Technology Institute > Experimental Methods

Deposited By:

Gege, Dr.rer.nat. Peter

Deposited On:

22 Oct 2024 10:42

Last Modified:

22 Oct 2024 10:42

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