Terroir 2014 banner
IVES 9 IVES Conference Series 9 Construction of a 3D vineyard model using very high resolution airborne images

Construction of a 3D vineyard model using very high resolution airborne images

Abstract

In recent years there has been a growth in interest and number of research studies regarding the application of remote optical and thermal sensing by unmanned aerial vehicle (UAV) in agriculture and viticulture. Many papers report on the use of images to map or estimate the growth and water status of plants, or the heterogeneity of different parcels. Most often, NDVI or other similar indices are used. However, analysis of this type of image is difficult in vineyards covered with grass, because contrast between the green of the grass and the green of the vine is low and difficult to classify. This paper presents the acquisition methodology of very high-resolution (5 [cm]) images and their processing to construct a three-dimensional surface model for the creation of precise digital surface and terrain models in order to separate different strata of a vineyard.

The images were acquired with a Sensefly Swinglet CAM unmanned aerial vehicle at an altitude of 110 [m], allowing for a resolution of 5 [cm]. The images were combined using Pix4D software, with a lateral overlap of 75% and a longitudinal overlap of 60%. The produced digital terrain and surface model was subtracted and an extraction mask containing only vine pixel was created. The results show the importance of using a precise digital terrain model. The raster file obtained by subtracting the DSM and the DTM showed values between -0.1 and + 2 m. in good accordance with the average value of the vine. The great majority of pixels fell between the threshold (0.5 [m]) and the topping values 1.6[m]). Using this procedure and parameters, an extremely precise surface model is obtained, as well as the pattern of the vineyard rows and, to some extent, the location of different plants stocks. This mask could be used to analyse images of the same plot taken at different times. The extraction of only vine pixels will facilitate subsequent analyses, for example, a supervised classification of these pixels.

DOI:

Publication date: July 29, 2020

Issue: Terroir 2014

Type: Article

Authors

S Burgos (1), M Mota (1), D. Noll (1), W. Metz (1), N. Delley (2), M. Kasser (2), B. Cannelle (2)

(1) University for Viticulture and Oenology Changins, 1260 Nyon Switzerland 
(2) School of Engineering and management Vaud (HEIG-VD), 1400 Yverdon, Switzerland 

Contact the author

Keywords

UAV, vineyard, green cover, 3D-models, precision viticulture

Tags

IVES Conference Series | Terroir 2014

Citation

Related articles…

Short-term relationships between climate and grapevine trunk diseases in southern French vineyards

[lwp_divi_breadcrumbs home_text="IVES" use_before_icon="on" before_icon="||divi||400" module_id="publication-ariane" _builder_version="4.19.4" _module_preset="default" module_text_align="center" module_font_size="16px" text_orientation="center"...

Bioclimatic shifts and land use options for Viticulture in Portugal

Land use, plays a relevant role in the climatic system. It endows means for agriculture practices thus contributing to the food supply. Since climate and land are closely intertwined through multiple interface processes, climate change may lead to significant impacts in land use. In this study, 1-km observational gridded datasets are used to assess changes in the Köppen–Geiger and Worldwide Bioclimatic (WBCS)

Aromatic maturity is a cornerstone of terroir expression in red wine

Harvesting grapes at adequate maturity is key to the production of high-quality red wines. Enologists and wine makers define several types of maturity, including technical maturity, phenolic maturity and aromatic maturity. Technical maturity and phenolic maturity are relatively well documented in the scientific literature, while articles on aromatic maturity are scarcer. This is surprising, because aromatic maturity is, without a doubt, the most important of the three in determining wine quality and typicity (including terroir expression). Optimal terroir expression can be obtained when the different types of maturity are reached at the same time, or within a short time frame. This is more likely to occur when the ripening takes place under mild temperatures, neither too cool, nor too hot. Aromatic expression in wine can be driven, from low to high maturity, by green, herbal, fresh fruit, ripe fruit, jammy fruit, candied fruit or cooked fruit aromas. Green and cooked fruit aromas are not desirable in red wines, while the levels of other aromatic compounds contribute to the typicity of the wine in relation to its origin. Wines produced in cool climates, or on cool soils in temperate climates, are likely to express herbal or fresh fruit aromas; while wines produced under warm climates, or on warm soils in temperate climates, may express ripe fruit, jammy fruit or candied fruit aromas. Growers can optimize terroir expression through their choice of grapevine variety. Early ripening varieties perform better in cool climates and late ripening varieties in warm climates. Additionally, maturity can be advanced or delayed by different canopy management practices or training systems.

Optimizing stomatal traits for future climates

Stomatal traits determine grapevine water use, carbon supply, and water stress, which directly impact yield and berry chemistry. Breeding for stomatal traits has the strong potential to improve grapevine performance under future, drier conditions, but the trait values that breeders should target are unknown. We used a functional-structural plant model developed for grapevine (HydroShoot) to determine how stomatal traits impact canopy gas exchange, water potential, and temperature under historical and future conditions in high-quality and hot-climate California wine regions (Napa and the Central Valley). Historical climate (1990-2010) was collected from weather stations and future climate (2079-99) was projected from 4 representative climate models for California, assuming medium- and high-emissions (RCP 4.5 and 8.5). Five trait parameterizations, representing mean and extreme values for the maximum stomatal conductance (gmax) and leaf water potential threshold for stomatal closure (Ψsc), were defined from meta-analyses. Compared to mean trait values, the water-spending extremes (highest gmax or most negative Ysc) had negligible benefits for carbon gain and canopy cooling, but exacerbated vine water use and stress, for both sites and climate scenarios. These traits increased cumulative transpiration by 8 – 17%, changed cumulative carbon gain by -4 – 3%, and reduced minimum water potentials by 10 – 18%. Conversely, the water-saving extremes (lowest gmax or least negative Ψsc) strongly reduced water use and stress, but potentially compromised the carbon supply for ripening. Under RCP 8.5 conditions, these traits reduced transpiration by 22 – 35% and carbon gain by 9 – 16% and increased minimum water potentials by 20 – 28%, compared to mean values. Overall, selecting for more water-saving stomatal traits could improve water-use efficiency and avoid the detrimental effects of highly negative canopy water potentials on yield and quality, but more work is needed to evaluate whether these benefits outweigh the consequences of minor declines in carbon gain for fruit production.

A better understanding of the climate effect on anthocyanin accumulation in grapes using a machine learning approach

The current climate changes are directly threatening the balance of the vineyard at harvest time. The maturation period of the grapes is shifted to the middle of the summer, at a time when radiation and air temperature are at their maximum. In this context, the implementation of corrective practices becomes problematic. Unfortunately, our knowledge of the climate effect on the quality of different grape varieties remains very incomplete to guide these choices. During the Innovine project, original experiments were carried out on Syrah to study the combined effects of normal or high air temperature and varying degrees of exposure of the berries to the sun. Berries subjected to these different conditions were sampled and analyzed throughout the maturation period. Several quality characteristics were determined, including anthocyanin content. The objective of the experiments was to investigate which climatic determinants were most important for anthocyanin accumulation in the berries. Temperature and irradiance data, observed over time with a very thin discretization step, are called functional data in statistics. We developed the procedure SpiceFP (Sparse and Structured Procedure to Identify Combined Effects of Functional Predictors) to explain the variations of a scalar response variable (a grape berry quality variable for example) by two or three functional predictors (as temperature and irradiance) in a context of joint influence of these predictors. Particular attention was paid to the interpretability of the results. Analysis of the data using SpiceFP identified a negative impact of morning combinations of low irradiance (lower than about 100 μmol m−2 s−1 or 45 μmol m−2 s−1 depending on the advanced-delayed state of the berries) and high temperature (higher than 25oC). A slight difference associated with overnight temperature occurred between these effects identified in the morning.