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

Tutkimustuotos: LehtiartikkeliConference articleScientificvertaisarvioitu

281 Lataukset (Pure)

Abstrakti

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.
AlkuperäiskieliEnglanti
Sivut15777–15783
Sivumäärä7
JulkaisuIFAC-PapersOnLine
Vuosikerta53
Numero2
DOI - pysyväislinkit
TilaJulkaistu - marrask. 2020
OKM-julkaisutyyppiA4 Artikkeli konferenssijulkaisussa
TapahtumaIFAC World Congress - Virtual, Online
Kesto: 11 heinäk. 202017 heinäk. 2020
Konferenssinumero: 21

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