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…

Impact of yeast derivatives to increase the phenolic maturity and aroma intensity of wine

Using viticultural and enological techniques to increase aromatics in white wine is a prized yet challenging technique for commercial wine producers. Equally difficult are challenges encountered in hastening phenolic maturity and thereby increasing color intensity in red wines. The ability to alter organoleptic and visual properties of wines plays a decisive role in vintages in which grapes are not able to reach full maturity, which is seen increasingly more often as a result of climate change. A new, yeast-based product on the viticultural market may give the opportunity to increase sensory properties of finished wines. Manufacturer packaging claims these yeast derivatives intensify wine aromas of white grape varieties, as well as improve phenolic ripeness of red varieties, but the effects of this application have been little researched until now. The current study applied the yeast derivative, according to the manufacture’s instructions, to the leaves of both neutral and aromatic white wine varieties, as well as on structured red wine varieties. Chemical parameters and volatile aromatics were analyzed in grape musts and finished wines, and all wines were subjected to sensory analysis by a tasting panel. Collective results of all analyses showed that the application of the yeast derivative in the vineyard showed no effect across all varieties examined, and did not intensify white wine aromatics, nor improve phenolic ripeness and color intensity in red wine.

Comparison of imputation methods in long and varied phenological series. Application to the Conegliano dataset, including observations from 1964 over 400 grape varieties

A large varietal collection including over 1700 varieties was maintained in Conegliano, ITA, since the 1950s. Phenological data on a subset of 400 grape varieties including wine grapes, table grapes, and raisins were acquired at bud break, flowering, veraison, and ripening since 1964. Despite the efforts in maintaining and acquiring data over such an extensive collection, the data set has varying degrees of missing cases depending on the variety and the year. This is ubiquitous in phenology datasets with significant size and length. In this work, we evaluated four state-of-the-art methods to estimate missing values in this phenological series: k-Nearest Neighbour (kNN), Multivariate Imputation by Chained Equations (mice), MissForest, and Bidirectional Recurrent Imputation for Time Series (BRITS). For each phenological stage, we evaluated the performance of the methods in two ways. 1) On the full dataset, we randomly hold-out 10% of the true values for use as a test set and repeated the process 1000 times (Monte Carlo cross-validation). 2) On a reduced and almost complete subset of varieties, we varied the percentage of missing values from 10% to 70% by random deletion. In all cases, we evaluated the performance on the original values using normalized root mean squared error. For the full dataset we also obtained performance statistics by variety and by year. MissForest provided average errors of 17% (3 days) at budbreak, 14% (4 days) at flowering, 14.5% (7 days) at veraison, and 17% (3 days) at maturity. We completed the imputations of the Conegliano dataset, one of the world’s most extensive and varied phenological time series and a steppingstone for future climate change studies in grapes. The dataset is now ready for further analysis, and a rigorous evaluation of imputation errors is included.

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)

Measurement of redox potential as a new analytical winegrowing tool

Excell laboratory has initiated the development of an analytical method based on electrochemistry to evaluate the ability of wines to undergo or resist to oxidative phenomena. Electrochemistry is a powerful tool to probe reactions involving electron transfers and offers possibility of real-time measurements. In that context, the laboratory has implemented electrochemical analysis to assess oxidation state of different wine matrices but also in order to evaluate oxidative or reduced character of leaf and soil. Initially, our laboratory focused on dosage of compounds involved in responses of plant stresses and we were also interested in microbiological activity of soils. These analyses were compared with the measurement of redox potential (Eh) and pH which are two fundamental variables involved in the modulation of plant metabolism. Indeed, the variation of redox states of the plant reflects its biological activity but also its capacity to absorb nutriments. The Eh-pH conditions mainly determine metabolic processes involved in soil and leaf and our goal is to determine if this combined analytical approach will be sufficiently precise to detect biological evolutions (plant health, parasitic attack…).

The modification of cultural practices in grapevine cv. Syrah, does it modify the characteristics of the musts?

The work shows the results of a year of experimentation (2020) in a Syrah variety vineyard in La Roda (Castilla-La Mancha, Spain). The trial approach was on a randomized block design with two factors: Irrigation (I) and Pruning (P).
Irrigation schedules were adjusted to apply amounts close to 1,500 m3/ha. With this provision, 2 different irrigation treatments were proposed: I1) Start of irrigation from pea-sized grape to post-harvest (providing at least 20 % of the total amount of irrigation water to be provided post-harvest); I2) Start of irrigation from pea-sized grape to harvest (usual irrigation practice in the study area). Pruning was proposed with two treatments, one at the end of January (P1), which is pruning on a conventional date; and P2) pruning carried out at the beginning of budding. In total, 4 repetitions were designed with 4 elementary plots, each one of them representing one of the proposed treatments (I1P1; I1P2; I2P1; I2P2). In total, 16 plots were worked on and each elementary plot consisted of 30 strains, distributed in 3 lines.
The productive response was evaluated with the yield results of the harvest harvested at 23 ºBrix. The qualitative response was measured in the musts through the indices of technological (acidity, pH and potassium) and phenolic maturity and aromatic compounds in free and glycosylated fractions. The treatments tested had, in general, an effect on the different variables analyzed.