Uncertainty Management in Remote Sensing of Climate Data

Author Stated, No

ISBN 10: 0309139589 / ISBN 13: 9780309139588

Published by National Academies Press, US, 2009

About this Item

Great advances have been made in our understanding of the climate system over the past few decades, and remotely sensed data have played a key role in supporting many of these advances. Improvements in satellites and in computational and data-handling techniques have yielded high quality, readily accessible data. However, rapid increases in data volume have also led to large and complex datasets that pose significant challenges in data analysis. Uncertainty characterization is needed for every satellite mission and scientists continue to be challenged by the need to reduce the uncertainty in remotely sensed climate records and projections. The approaches currently used to quantify the uncertainty in remotely sensed data lack an overall mathematically based framework. An additional challenge is characterizing uncertainty in ways that are useful to a broad spectrum of end-users. In December 2008, the National Academies held a workshop, summarized in this volume, to survey how statisticians, climate scientists, and remote sensing experts might address the challenges of uncertainty management in remote sensing of climate data.The workshop emphasized raising and discussing issues that could be studied more intently by individual researchers or teams of researchers, and setting the stage for possible future collaborative activities.

Seller Inventory # LU-9780309139588

Bibliographic Details

• Title: Uncertainty Management in Remote Sensing of Climate Data
• Publisher: National Academies Press, US
• Publication Date: 2009
• Language: English
• ISBN 10: 0309139589
• ISBN 13: 9780309139588
• Binding: Paperback
• Condition: New

About this title

Synopsis

Great advances have been made in our understanding of the climate system over the past few decades, and remotely sensed data have played a key role in supporting many of these advances. Improvements in satellites and in computational and data-handling techniques have yielded high quality, readily accessible data. However, rapid increases in data volume have also led to large and complex datasets that pose significant challenges in data analysis. Uncertainty characterization is needed for every satellite mission and scientists continue to be challenged by the need to reduce the uncertainty in remotely sensed climate records and projections. The approaches currently used to quantify the uncertainty in remotely sensed data lack an overall mathematically based framework. An additional challenge is characterizing uncertainty in ways that are useful to a broad spectrum of end-users.

In December 2008, the National Academies held a workshop, summarized in this volume, to survey how statisticians, climate scientists, and remote sensing experts might address the challenges of uncertainty management in remote sensing of climate data. The workshop emphasized raising and discussing issues that could be studied more intently by individual researchers or teams of researchers, and setting the stage for possible future collaborative activities.