The doctoral dissertations of the former Helsinki University of Technology (TKK) and Aalto University Schools of Technology (CHEM, ELEC, ENG, SCI) published in electronic format are available in the electronic publications archive of Aalto University - Aaltodoc.
Aalto

Remote Sensing of Snow-Cover for the Boreal Forest Zone Using Microwave Radar

Kari Luojus

Dissertation for the degree of Doctor of Science in Technology to be presented with due permission of the Faculty of Electronics, Communications and Automation for public examination and debate in Auditorium S4 at Helsinki University of Technology (Espoo, Finland) on the 15th of May, 2009, at 12 noon.

Overview in PDF format (ISBN 978-951-697-690-0)   [2194 KB]
Dissertation is also available in print (ISBN 978-951-697-689-4)

Abstract

This doctoral dissertation describes the development of an operationally feasible snow monitoring methodology utilizing spaceborne synthetic aperture radar (SAR) imagery, intended for hydrological applications on the boreal forest zone. The snow-covered area (SCA) estimation methodology developed is characterized using extensive satellite-based datasets, including SAR-based estimation and optical reference data gathered during the snow-melt seasons of 1997-1998, 2000-2002 and 2004-2006 from northern Finland. The methodology applies satellite-based C-band SAR data for snow monitoring during the spring snow-melt season. The SCA information can be utilized for river discharge forecasting and flood predictions and for the optimization of hydropower production.

The development efforts included 1) demonstration of a forest compensation algorithm, 2) establishing the use of wide-swath SAR data 3) development of a weather station assimilation procedure and 4) creation of an enhanced reference image selection algorithm for the SCA estimation methodology.

The feasibility of a proposed, non-boreal forest specific, SAR-based SCA estimation method was evaluated for the boreal forest zone. The acquired results were compared with the characteristics determined for the boreal-forest specific methodology developed within this dissertation. These results can be used when selecting appropriate SCA estimation approaches for future snow monitoring systems whether conducted in different regions or intended for larger i.e. continental or global scale purposes.

An automatic processing system for SCA estimation was developed and demonstrated as part of this work; the system has been delivered to the Finnish Environment Institute for operational use.

This thesis consists of an overview and of the following 6 publications:

  1. Kari P. Luojus, Jouni T. Pulliainen, Sari J. Metsämäki, and Martti T. Hallikainen. 2006. Accuracy assessment of SAR data-based snow-covered area estimation method. IEEE Transactions on Geoscience and Remote Sensing, volume 44, number 2, pages 277-287.
  2. Kari P. Luojus, Jouni T. Pulliainen, Sari J. Metsämäki, and Martti T. Hallikainen. 2007. Snow-covered area estimation using satellite radar wide-swath images. IEEE Transactions on Geoscience and Remote Sensing, volume 45, number 4, pages 978-989.
  3. Kari P. Luojus, Jouni T. Pulliainen, Sari J. Metsämäki, and Martti T. Hallikainen. 2009. Enhanced SAR-based snow-covered area estimation method for boreal forest zone. IEEE Transactions on Geoscience and Remote Sensing, volume 47, number 3, pages 922-935.
  4. Kari P. Luojus, Jouni T. Pulliainen, Alberto Blasco Cutrona, Sari J. Metsämäki, and Martti T. Hallikainen. 2009. Comparison of SAR-based snow-covered area estimation methods for the boreal forest zone. IEEE Geoscience and Remote Sensing Letters, volume 6, number 3, pages 403-407.
  5. Jarkko T. Koskinen, Jouni T. Pulliainen, Kari P. Luojus, and Matias Takala. Monitoring of snow cover properties during the spring melting period in forested areas. IEEE Transactions on Geoscience and Remote Sensing, accepted for publication.
  6. Kari Luojus and Jouni Pulliainen. 2006. Automatic processing chain for SAR data-based snow-covered area estimation method. Espoo, Finland. 33 pages. Helsinki University of Technology, Laboratory of Space Technology, Report 65.

Keywords: remote sensing, snow monitoring, snow-covered area, synthetic aperture radar

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© 2009 Helsinki University of Technology

Last update 2011-05-26