Satellite aerosol remote sensing over land

著者

    • Kokhanovsky, Alex A.
    • Leeuw, Gerrit de

書誌事項

Satellite aerosol remote sensing over land

Alexander A. Kokhanovsky and Gerrit de Leeuw (Editors)

(Springer-Praxis books in environmental sciences)

Springer , Praxis, c2009

  • : hbk

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注記

Includes bibliographical references and index

内容説明・目次

内容説明

Aerosols have a significant influence on the Earth's radiation budget, but there is considerable uncertainty about the magnitude of their effect on the Earth's climate. Currently, satellite remote sensing is being increasingly utilized to improve our understanding of the effect of atmospheric aerosols on the climate system. Satellite Aerosol Remote Sensing Over Land is the only book that brings together in one volume the most up-to-date research and advances in this discipline. As well as describing the current academic theory, the book presents practical applications, utilizing state-of-the-art instrumentation, invaluable to the work of environmental scientists. With contributions by an international group of experts and leaders of correspondent aerosol retrieval groups, the book is an essential tool for all those working in the field of climate change.

目次

Introduction, 1. The dark-land MODIS collection 5 aerosol retrieval: algorithm development and product evaluation, 2. The time series technique for aerosol retrievals over land from MODIS, 3. Iterative procedure for retrieval of spectral aerosol optical thickness and surface reflectance from satellite data using fast radiative transfer code and its application to MERIS onboard ENVISAT measurements, 4. Aerosol retrieval over land using the ATSR dual-view algorithm, 5. Aerosol optical depth from dual-view (A)ATSR satellite observations, 6. Oxford-RAL Aerosol and Cloud (ORAC): aerosol retrievals from satellite radiometers, 7. Benefits and limitations of the synergistic aerosol retrieval SYNAER, 8. Retrieval of aerosol properties over land using MISR observations, 9. Polarimetric remote sensing of aerosols over land surfaces, 10. Optimal estimation applied to the joint retrieval of aerosol optical depth and surface BRF using MSG/SEVIRI observations, 11. Remote sensing data combinations: superior global maps for aerosol optical depth

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