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FOREST CANOPY COVER DETERMINATION USING AN UNMANNED AERIAL VEHICLE AND OBJECT-BASED IMAGE ANALYSIS IN A BEECH AND DURMAST OAK STAND IN THE SOUTH-WEST HILLY AREA OF POIANA-RUSC? MOUNTAINS, ROMANIA

Tiberiu Paul Banu, Gheorghe Florian Borlea, Constantin Banu

First published: 2017-06-20https://doi.org/10.5593/sgem2017/32/s14.108View metrics

Abstract

The forest canopy cover is an important element of forest inventories and it represents the proportion of the ground covered by the vertical projection of the tree crowns. Traditional ground-based methods cannot be efficient in measuring the vertical projection of the tree crowns and in accurately making determinations of forest canopy cover percentage in stands of over a few hectares. The purpose of the current paper is to present the potential of a new approach for forest canopy cover determination that is based on Unmanned Aerial Vehicles (UAV) surveys combined with Object-Based Image Analysis (OBIA). A low-cost commercial UAV was used in order to acquire aerial images over a beech and durmast oak stand in the South-West hilly area of Poiana-Rusc? Mountains. Based on the captured images, an orthomosaic was assembled. OBIA was used in order to segment and classify the orthomosaic and calculate the forest canopy cover percentage. The results present a comparison between the current method determination and the traditional ground-based field estimation. Further, the advantages of the methodology in this study in terms of costs, time-consumption and accuracy are discussed.

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Publication details

Title
FOREST CANOPY COVER DETERMINATION USING AN UNMANNED AERIAL VEHICLE AND OBJECT-BASED IMAGE ANALYSIS IN A BEECH AND DURMAST OAK STAND IN THE SOUTH-WEST HILLY AREA OF POIANA-RUSC? MOUNTAINS, ROMANIA
Authors
Tiberiu Paul Banu, Gheorghe Florian Borlea, Constantin Banu
Proceedings
SGEM International Multidisciplinary Scientific GeoConference EXPO Proceedings; 17th International Multidisciplinary Scientific GeoConference SGEM2017, Water Resources. Forest, Marine and Ocean Ecosystems
Publisher
STEF92 Technology
Year
2017
Pages
837-844
SWS Citekey
Banu201714837844
ISSN
1314-2704
ISBN
978-619-7408-05-8
Language
en
Publication type
Conference Paper
Keywords
References13
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