Drone based Mapping and Identification of Young Spruce Stand for Semiautonomous Cleaning

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http://hdl.handle.net/10138/329307

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Title: Drone based Mapping and Identification of Young Spruce Stand for Semiautonomous Cleaning
Author: Ouattara, Issouf; Hyyti, Heikki; Visala, Arto
Publisher: Elsevier
Date: 2020
Language: en
Belongs to series: IFAC-PapersOnLine, Proceedings of the 21th IFAC World Congress, Berlin, Germany, 12-17 July 2020
ISSN: 2405-8971
2405-8963
URI: http://hdl.handle.net/10138/329307
Abstract: We propose a novel method to locate spruces in a young stand with a low cost unmanned aerial vehicle. The method has three stages: 1) the forest area is mapped and a digital surface model and terrain models are generated, 2) the locations of trees are found from a canopy height model using local maximum and watershed algorithms, and 3) these locations are used in a convolution neural network architecture to detect young spruces. Our result for detecting young spruce trees among other vegetation using only color images from a single RGB camera were promising. The proposed method is able to achieve a detection accuracy of more than 91%. As low cost unmanned aerial vehicles with color cameras are versatile today, the proposed work is enabling low cost forest inventory for automating forest management.
Subject: unmanned aerial vehicle
mapping
individual tree identification
convolutional neural network
autonomous vehicle
forestry


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