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Sensing forest structure from lidar

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Remote sensing technology developments increases the possibility of studying the forest structure in detail and suport sustainable forest management goals. The usage of remote sensing data from laser scanning sources has also been remarkbly increased for forestry applications, since conventional field inventories are time consuming and expensive. Furthermore , remote sensing-based methods for obtaining accurate and update forest structure have been under a continuous development. The principal goal of this thesis is to develop methods using remote sensing for obtaining explicit information on forest structure such as regeneration coverage, stem count, segmented and classified tree species. The methods are applied in small test areas and can be extended to large forest areas. The study areas are chosen from small datasets in southeast Germany, and a small forest region in Austria. A set of indicators of forest structure including regeneration converage, stem count by segmentation and tree species are selected. A. wide range of lidar data sources are employed, which could provide a high amount of relevant information for forestry applications.

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Ketersediaan

B20190627311

DS 621.3678 NIN s

(600-)

Tersedia

Informasi Detail

Judul Seri

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No. Panggil

DS 621.3678 NIN s

Penerbit

Netherlands : University of Twente., 2019

Deskripsi Fisik

viii, 142 hlm. : illus. ; 24 cm.

Bahasa

Inggris

ISBN/ISSN

978-90-365-4765-9

Klasifikasi

621.3678

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

Penginderaan Jauh

Info Detail Spesifik

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Pernyataan Tanggungjawab

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Versi lain/terkait

Lampiran Berkas

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