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Record Nr. |
UNINA9910299456403321 |
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Autore |
Ackermann Nicolas |
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Titolo |
Growing Stock Volume Estimation in Temperate Forested Areas Using a Fusion Approach with SAR Satellites Imagery / / by Nicolas Ackermann |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2015 |
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ISBN |
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Edizione |
[1st ed. 2015.] |
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Descrizione fisica |
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1 online resource (323 p.) |
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Collana |
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Springer Theses, Recognizing Outstanding Ph.D. Research, , 2190-5053 |
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Disciplina |
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Soggetti |
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Remote sensing |
Forests and forestry |
Geomorphology |
Remote Sensing/Photogrammetry |
Forestry |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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"Doctoral Thesis accepted by Friedrich-Schiller University of Jena, Germany." |
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Nota di bibliografia |
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Includes bibliographical references at the end of each chapters. |
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Nota di contenuto |
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Introduction -- Literature Review -- Theory and Techniques -- Test Site, Data and Methods -- Results -- Conclusions -- Appendices. |
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Sommario/riassunto |
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"The PhD thesis written by Mr. Ackermann is an outstanding and in-depth scientific study that closes a research gap and paves the way to new developments. Despite the extremely complex issues, his work is very understandable and excellently elaborated." Prof. Dr. Christiane Schmullius "The PhD thesis written by Mr. Ackermann is an excellent and very comprehensive work performed at the highest scientific level. It examines in detail the potential of SAR data with regards to the derivation of forest stem volume in the temperate latitudes. The work belongs to a technically complex field. Nevertheless, Mr. Ackermann has succeeded in presenting the content in a clear and understandable way." Dr. Christian Thiel "The proposed document is overall of very good quality. Mr. Ackermann has done an exhaustive analysis of the in-situ data available on the Thuringian forest and was able to derive Growing Stocking Volume using L- and X-band spaceborne SAR data. The document is very well structured with a good split of information |
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