Abstract
Unmanned Aerial Vehicles (UAVs) with multispectral sensors are increasingly attractive in geosciences for data capture and map updating at high spatial and temporal resolutions. These autonomously-flying systems can be equipped with different sensors, such as a six-band multispectral camera (Tetracam mini-MCA-6), GPS Ublox M8N, and MEMS gyroscopes, and miniaturized sensor systems for navigation, positioning, and mapping purposes. These systems can be used for data collection in precision viticulture. In this study, the efficiency of a light UAV system for data collection, processing, and map updating in small areas is evaluated, generating correlations between classification maps derived from remote sensing and production maps. Based on the comparison of the indices derived from UAVs incorporating infrared sensors with those obtained by satellites (Sentinel 2A and Landsat 8), UAVs show promise for the characterization of vineyard plots with high spatial variability, despite the low vegetative coverage of these crops. Consequently, a procedure for zoning map production based on UAV/UV images could provide important information for farmers.
Highlights
In the domain of precision farming, the contemporary generation of aerial images with high spatial resolution is of great interest
Unmanned Aerial Vehicles (UAVs) with multispectral sensors are becoming increasingly attractive in viticulture for data capture and map updating at high spatial and temporal resolutions
This paper first presents a camera system designed for georeferenced NIR orthophoto generation, which was reliably used on a UAV (Figure 9)
Summary
In the domain of precision farming, the contemporary generation of aerial images with high spatial resolution is of great interest. Useful in particular are aerial images in the thermal (TIRS) infrared (Suarez et al, 2010) and near-infrared (NIR) spectrum (Nebiker et al, 2008). Unmanned Aerial Vehicles (UAVs) with multispectral sensors are becoming increasingly attractive in viticulture for data capture and map updating at high spatial and temporal resolutions. These systems can be used for data collection in precision viticulture (Arno, 2008), (Bellvert, 2014) and (Montesinos, 2015). Airborne thermal and multispectral images have been applied successfully to the detection of water stress at larger scales. Normalized canopy temperature, chlorophyll content, and photochemical reflectance indices were demonstrated to be the best indicators of early and advanced water stress
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