Evaluation of the Influence of Field Conditions on Aerial Multispectral Images and Vegetation Indices

Remote sensing is a method used for monitoring and measuring agricultural crop fields. Unmanned aerial vehicles (UAV) are used to effectively monitor crops via different camera technologies. Even though aerial imaging can be considered a rather straightforward process, more focus should be given to...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2022-10, Vol.14 (19), p.4792
Main Authors: Änäkkälä, Mikael, Lajunen, Antti, Hakojärvi, Mikko, Alakukku, Laura
Format: Article
Language:English
Subjects:
aerial imaging
Agricultural production
Cameras
Coefficient of variation
Crop fields
drone
Drones
Evaluation
field conditions
Influence
Machine learning
Mathematical analysis
multispectral images
Neural networks
Normalized difference vegetative index
Remote sensing
Satellites
Sensors
Software
Unmanned aerial vehicles
Variation
Vegetation
vegetation index
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Summary:Remote sensing is a method used for monitoring and measuring agricultural crop fields. Unmanned aerial vehicles (UAV) are used to effectively monitor crops via different camera technologies. Even though aerial imaging can be considered a rather straightforward process, more focus should be given to data quality and processing. This research focuses on evaluating the influences of field conditions on raw data quality and commonly used vegetation indices. The aerial images were taken with a custom-built UAV by using a multispectral camera at four different times of the day and during multiple times of the season. Measurements were carried out in the summer seasons of 2019 and 2020. The imaging data were processed with different software to calculate vegetation indices for 10 reference areas inside the fields. The results clearly show that NDVI (normalized difference vegetation index) was the least affected vegetation index by the field conditions. The coefficient of variation (CV) was determined to evaluate the variations in vegetation index values within a day. Vegetation index TVI (transformed vegetation index) and NDVI had coefficient of variation values under 5%, whereas with GNDVI (green normalized difference vegetation index), the value was under 10%. Overall, the vegetation indices that include near-infrared (NIR) bands are less affected by field condition changes.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs14194792