Evaluation of Multispectral Data Acquired from UAV Platform in Olive Orchard

Abstract

Precision agriculture is a management strategy to improve resource efficiency, production, quality, profitability and sustainability of the crops. In recent years, olive tree management is increasingly focused on determining the correct health status of the plants in order to distribute the main resource using different technologies. In the olive grove, the focus is often on the use of multispectral information from UAVs (Unmanned Aerial Vehicle), but it is not known how important spectral and biometric information actually is for the agronomic management of the olive grove. The aim of this study was to investigate the ability of multispectral data acquired from a UAV platform to predict nutritional status, biometric characteristics, vegetative condition and production of olive orchard as tool to DSS. Data were collected on vegetative characteristics closely related to vigour such as trunk cross-sectional area (TCSA), Nitrogen concentration of the leaves, canopy area and canopy volume. The production was collected for each plant to create an accurate yield map. The flight was carried out with a UAV equipped with a multispectral camera, at an altitude of 50 m and with RTK correction. The flight made it possible to determine the biometric condition and the spectral features through the normalized difference vegetation index (NDVI). The NDVI map allowed to determine the canopy area. The Structure for Motion (SfM) algorithm allow to determine the 3D canopy volume. The experiment showed that the NDVI was able to determine with high accuracy the vegetative characteristic as canopy area (r = 0.87 ***), TCSA (r = 0.58 ***) and production (r = 0.63 ***). The vegetative parameters are closely correlated with the production, especially the canopy area (r = 0.75 ***). Data clustering showed that the production of individual plants is closely dependent on leaf nitrogen concentration and vigour status.

Plant phenotyping relevance

UAVマルチスペクトル画像、NDVI、SfMによる樹冠面積・体積などの植物形質推定を評価し、実測値との相関で検証しているため、フェノタイピング手法が中心である。

Code and data availability

The paper reports UAV multispectral phenotyping of an olive orchard (NDVI, canopy area, canopy volume, TCSA, nitrogen, yield), but no public dataset, imagery, code, or model deposit is provided. The Data Availability Statement reads 'Not applicable', and processing used commercial/proprietary software (Agisoft Photosan

No evidence-backed public reproduction asset is currently recorded.