Application of UAV multispectral imaging for determining the characteristics of maize vegetation
Laen...
Kuupäev
2023
Kättesaadav alates
Ajakirja pealkiri
Ajakirja ISSN
Köite pealkiri
Kirjastaja
Estonian University of Life Sciences
Abstrakt
Interest in forage maize (Zea mays L.) cultivation for livestock feed has grown in
northern conditions. In addition, it is important to develop methods and tools to monitor crop
development and other characteristics of the crop. For these purposes UAVs are very efficient
and versatile tools. UAVs can be equipped with a variety of sensors like lidar or different types
of cameras. Several studies have been conducted where data collected by UAVs are used to
estimate different crop properties like yield and biomass. In this research, a forage maize field
experiment was studied to examine how well the aerial multispectral data correlated with the
different properties of the vegetation. The field test site is located in Helsinki, Finland.
A multispectral camera (MicaSense Rededge 3) was used to take images from five spectral bands
(Red, Green, Blue, Rededge and NIR). All the images were processed with Pix4D software to
generate orthomosaic images. Several vegetation indices were calculated from the five spectral
bands. During the growing season, crop height, chlorophyll content, leaf area index (LAI), fresh
and dry matter biomass were measured from the vegetation. From the five spectral bands,
Rededge had the highest correlation with fresh biomass (R2 = 0.273). The highest correlation for
a vegetation index was found between NDRE and chlorophyll content (R2 = 0.809). A multiple
linear regression (MLR) model using selected spectral bands and vegetation indices as inputs
showed high correlations with the field measurements.
Kirjeldus
Received: February 1st, 2023 ; Accepted: April 25th, 2023 ; Published: May 10th, 2023 ; Correspondence: mikael.anakkala@helsinki.fi
Märksõnad
agriculture, maize, multispectral images, UAV, vegetation index, articles