Inversion and Data Assimilation in Remote Sensing (Hardcover)

Yajing Yan

ISBN 10: 1789451426 / ISBN 13: 9781789451429

Published by ISTE Ltd, London, 2024

About this Item

Hardcover. Remote sensing data are now the primary sources for observing Earth and the Universe. Data inversion and assimilation techniques are the main tools for estimating and predicting the geophysical parameters that characterize the evolution of our planet and the Universe, using remote sensing data. Inversion and Data Assimilation in Remote Sensing explores recent advances in the inversion and assimilation of remote sensing data. It presents traditional and current neural network methods, as well as a number of topics where these methods have been developed or adapted to suit the specific nature of the field. The assimilation section covers prediction problems in volcanology and glaciology. Lastly, the inversion section covers biomass inversion using SAR images, bio-physio-hydrological inversion in coastal areas using multi- and hyperspectral images, and astrophysical inversion using telescope data. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

Seller Inventory # 9781789451429

Bibliographic Details

• Title: Inversion and Data Assimilation in Remote Sensing (Hardcover)
• Publisher: ISTE Ltd, London
• Publication Date: 2024
• Language: English
• ISBN 10: 1789451426
• ISBN 13: 9781789451429
• Binding: Hardcover
• Condition: new

About this title

Synopsis

Remote sensing data are now the primary sources for observing Earth and the Universe. Data inversion and assimilation techniques are the main tools for estimating and predicting the geophysical parameters that characterize the evolution of our planet and the Universe, using remote sensing data.

Inversion and Data Assimilation in Remote Sensing explores recent advances in the inversion and assimilation of remote sensing data. It presents traditional and current neural network methods, as well as a number of topics where these methods have been developed or adapted to suit the specific nature of the field. The assimilation section covers prediction problems in volcanology and glaciology. Lastly, the inversion section covers biomass inversion using SAR images, bio-physio-hydrological inversion in coastal areas using multi- and hyperspectral images, and astrophysical inversion using telescope data.

About the Author

Yajing Yan is a lecturer at the LISTIC laboratory, Université Savoie Mont Blanc, France. Her research focuses on multi-temporal InSAR analysis, remote sensing data fusion and assimilation, and machine learning.