Use of UAV in inventory of an old orchard - Case study Světlá

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F62156489%3A43410%2F23%3A43923069" target="_blank" >RIV/62156489:43410/23:43923069 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.17660/eJHS.2023/006" target="_blank" >https://doi.org/10.17660/eJHS.2023/006</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.17660/eJHS.2023/006" target="_blank" >10.17660/eJHS.2023/006</a>

Result language

angličtina

Original language name

Use of UAV in inventory of an old orchard - Case study Světlá

Original language description

The conventional inventory is time-consuming and expensive, however the remote sensing method is a useful tool to make orchard inventory faster and cheaper. The aim of this work is to carry out an old orchard inventory using a low-cost system boarded on a drone equipped only with a camera RGB (Red, Green and Blue) with an added NIR (Near-infrared) filter thus providing an automated approach for orchard managers. First, the position measurement of some individual trees was done and then, an Unmanned Aerial Vehicle (UAV) equipped with RGB (visible part of the spectrum) and NIR image camera was used to create the orthophoto images with 5 cm of spatial resolution. The proposed method includes Digital Surface Model (DSM) creation, individual tree location, tree species classification, and field verification of results. In this study, eight different species were identified and RGB, NIR spectral bands and Normalized Difference Vegetation Index (NDVI) were used as input features for classification. Several classification methods were compared in this study such as the Classification and Regression Trees (CART) method, which obtained a 79% of accuracy being Nut and Rose the most predicted species; moreover the producer&apos;s accuracy for eight species is ranging from 0.78-0.91. The results of Boosted Trees method, Random Forest and Supervised Classification technique showed an accuracy of 72%, 66% and 65%, respectively. In this research, the possibility to use drone technology to create an old orchard inventory was analyzed as well as the most accurate methodology to carry out tree species classification.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

20705 - Remote sensing

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

European Journal of Horticultural Science

ISSN

1611-4426

e-ISSN

1611-4434

Volume of the periodical

8

Issue of the periodical within the volume

1

Country of publishing house

DE - GERMANY

Number of pages

9

Pages from-to

"Nestrankovano"

UT code for WoS article

000943190800006

EID of the result in the Scopus database

2-s2.0-85149830790