Abstract
The use of unmanned aerial vehicles (UAVs) for remote sensing applications in precision viticulture significantly increased in the last years. UAVs’ capability to acquire high spatiotemporal resolution and georeferenced imagery from different sensors make them a powerful tool for a better understanding of vineyard spatial and multitemporal heterogeneity, allowing the estimation of parameters directly impacting plants’ health status. In this way, the decision support process in precision viticulture can be greatly improved. However, despite the proliferation of these innovative technologies in viticulture, most of the published studies rely only on data from a single sensor in order to achieve a specific goal and/or in a single/small period of the vineyard development. In order to address these limitations and fully exploit the advantages offered by the use of UAVs, this study explores the multi-temporal analysis of vineyard plots at a grapevine scale using different imagery sensors. Individual grapevine detection enables the estimation of biophysical and geometrical parameters, as well as missing grapevine plants. A validation procedure was carried out in six vineyard plots focusing on the detected number of grapevines and missing grapevines. A high overall agreement was obtained concerning the number of grapevines present in each row (99.8%), as well as in the individual grapevine identification (mean overall accuracy of 97.5%). Aerial surveys were conducted in two vineyard plots at different growth stages, being acquired for RGB, multispectral and thermal imagery. Moreover, the extracted individual grapevine parameters enabled us to assess the vineyard variability in a given epoch and to monitor its multi-temporal evolution. This type of analysis is critical for precision viticulture, constituting as a tool to significantly support the decision-making process.
Highlights
The need to assess vineyard spatiotemporal variability is crucial in viticulture, as it is directly related to grapevine health status and yield [1], which can be achieved through precision viticulture (PV)
Derived from precision agriculture (PA) concepts [2], in PV, different technologies for vineyard management and grape production are employed for data acquisition and processing, aiming, among others, to maximize the oenological potential of vineyards, according to their spatiotemporal variability, by adopting site-specific management practices to increase both quality and yield [3,4]
This study explores the usage of unmanned aerial vehicles (UAVs)-based photogrammetric outcomes to extract individual grapevine geometrical and biophysical parameters within vineyard plots
Summary
The need to assess vineyard spatiotemporal variability is crucial in viticulture, as it is directly related to grapevine health status and yield [1], which can be achieved through precision viticulture (PV). Traditional airborne remote sensing platforms such as satellites and manned aircraft, both suitable for applications requiring a regional coverage, were used in PV to detect grapevine varieties [6], vigour assessment [7,8], vineyard disease mapping [9], leaf area index (LAI) and canopy density estimation [10,11]. Given their coarser spatial resolution, crop and non-crop data are often mixed or represent multiple plants, lacking true individual grapevine information [12]. Vibrations induced by the vehicles can interfere in data quality and the high costs of LiDAR sensors constitute a drawback to their widespread adoption
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