Sentinel-2 Data Analysis and Comparison with UAV Multispectral Images for Precision Viticulture

Precision viticulture (PV) requires the use of technologies that can detect the spatial and temporal variability of vineyards and, at the same time, allow useful information to be obtained at sustainable costs. In order to develop a cheap and easy-to-handle operational monitoring scheme for PV, the aim of this work was to evaluate the possibility of using Sentinel-2 multispectral images for long-term vineyard monitoring through the Normalized Difference Vegetation Index (NDVI). Vigour maps of two vineyards located in northeastern Italy were computed from satellite imagery and compared with those derived from UAV multispectral images; their correspondence was evaluated from qualitative and statistical points of view. To achieve this, the UAV images were roughly resampled to 10 m pixel size in order to match the spatial resolution of the satellite imagery. Preliminary results show the potential use of open source Sentinel-2 platforms for monitoring vineyards, highlighting links with the information given in the agronomic bulletins and identifying critical areas for crop production. Despite the large differences in spatial resolution, the results of the comparison between the UAV and Sentinel-2 data were promising. However, for long-term vineyard monitoring at territory scale, further studies using multispectral sensor calibration and groundtruth data are required

On-the-go yield and sugar sensing in grape harvester

This paper summarises the results of a joint R+D project between university and industry. The study was developed at the Alt Penedès region, in Barcelona, during the 2006 and 2007 (on 3, 22, 69 fields respectively). The quality sensors set-up in year 2007, mounted on a New Holland SB55 grape harvester, were: two load cells, one refractometer, an ambient temperature prove and a GPS antenna, while in 2006 only the load cells and the GPS performed properly. The method used for this study is as follows: 1. Data recording from GPS and Logger (the latter is use for according and digitalising the sensor signal); 2. Wireless download of data to a PC; 3. Automatic data integration in a single file; 4. Lane automatic identification based on trajectory angles, machine forward speed determination, effective time calculation, masic flow, kg/m, and total amount harvested, kg/hopper, computation of characteristic soluble solid content and temperature during harvest; 5. Data broadcasting through GPRS to the winery; 6. Comparison of transmitted data with the invoice of the winery containers. After the season was finished, a data post processing was performed in order to a assess the causes of isolated incidences that were registered in 10 fields. Also a recalibration of the sensors for future seasons was performed. At current stage R 2 of 0.9547 is found between winery and in field yield data. Beside georeference data were gathered and compare to the remote photos in “Instituto Cartográfico de Cataluña”. Site-specific yield maps and speed maps have been computed while broad soluble solid information is not available due to slight dysfunctions of the grape juice pumping system towards to the refractometer

Assessing Investment in Precision Farming for Reducing Pesticide Use in French Viticulture

The paper develops a mathematical programming model for assessing the impact of Environmental Policy instruments on French winegrowing farm’s adoption of pesticides-saving technologies. We model choices with regards to investment in precision farming and plant protection practices, in a multi-periodic framework with sequential decision, integrating uncertainty on fungal disease pressure and imperfect information on equipment performance. We focus on recursive models maximizing a Utility function. These models are applied on a representative sample of 534 winegrowers from the French Farm Accountancy Data Network (FADN). As expected, both ecotaxes and green subsidies make precision farming equipment more profitable, but the investment rate remains however low and concentrated on basic systems. One explanation is grower’s financial constraint in a context of market crisis and farm indebtedness. Shortcomings and further development of the models are discussed.Discrete Stochastic Programming, Precision Farming, Viticulture, Pesticides, Environmental Policy, Crop Production/Industries, Farm Management,

Precision viticulture in Brazil: current research status on wine grape.

Technologies associated to precision viticulture (PV) are not currently used by Brazilian growers. To overcome this situation, a research is being carried out since 2011 in a vineyard of Merlot using a wide range of PV technologies. During this period, several PV research activities were performed which will be concluded in a couple of years. Therefore, final results depend on further variable evaluation which should be done by means of geostatistic, Geographic Information Systems and Principal Component Analysis. This paper briefly presents a series of methodological procedures used in different ways to attain the objective of this research project. In the sequence, it describes one final result and nine partial ones. Morphological and physicochemical analyses of soil showed that the vineyards are established on three taxonomic classes of soil ? Argissolo, Cambissolo and Neossolo −, which are formed by ten mapping units. The partial results are mainly related to the utilization of GIS, modeling and must and wine composition of five mapping units; however they show results of only one year. With the complete set of analyses, data should be spatialized and maps prepared. Then, it will be possible to recommend different practices to each soil type and to aid oenologists to direct wines to a specific quality pattern

A cellular automaton framework for within-field vineyard variance and grape production simulation

Winegrowers for generations know it all too well that grapes harvested from different areas within a vineyard will produce wines of different flavours, mainly due to within-field variance in vine vigour caused by environmental variability from various factors, such as soil properties, microclimate conditions, and rootstock. Recent research attempts on the use of state-of-the-art technologies to model/ simulate within-field variance at a vineyard scale are outlined. Consequently, the paper illustrates a cellular automaton (CA) framework being developed for simulating the within-field variance in grapevine plant vigour, phenological events and vineyard production using random or real thematic mappings of likely key factors that contribute to the observed variance. The CA approach provides an alternative software tool to conventional crop estimation methods that are dependent upon expensive yield sampling methods

Precision viticulture: use of new technologies to improve efficiency in spray applications in vineyard

Postprint (published version

Precision viticulture focusing southern Brazil.

There are four main wine regions in Rio Grande do Sul state, Brazil: (1) "Serra Gaúcha"; (2) São Francisco Valley; (3) "Serra do Sudeste" and (4) "Campos de Cima da Serra". The region (1) is the oldest wine region of Brazil, related to Italian immigration in nineteen century. Regions (2), (3) and (4) are newer, showing similarities but soft changes in climate and soil conditions. Precision viticulture (PV) has advanced in these poles in the last 20 years. Different techniques related to precision viticulture in the context of the precision agriculture (PA) network of Embrapa, including soil mapping, physical properties sensors, remote sensing, spectrorradiometry and miscellaneous methods. Results suggest a medium technological development of PA in Brazil, with the most approaches related to grain production and few enterprises of growing fruit or viticulture, including PV. Most techniques considered an academic context or, in a few specific cases, the productive sector

Configuration and specifications of an unmanned aerial vehicle for precision viticulture

[SPA] Los vehículos aéreos no tripulados (UAV) con sensores multiespectrales son cada vez más atractivos en ciencias de la tierra para la captura de datos y actualización de mapas con alta resolución espacial y temporal. Estos sistemas de vuelo autónomo pueden equiparse con diferentes tipos de sensores, tales como cámaras multiespectrales y sensores miniaturizados, para facilitar la navegación, el posicionamiento y la elaboración de mapas de alta resolución. Estos sistemas ya se están utilizando para la recolección de datos en la viticultura de precisión. En este estudio, se pretende evaluar la eficiencia de los estos vehículos para la recolección de datos, procesamiento y actualización de mapas en áreas pequeñas, así como su comparación con otros índices derivados de los satélites (Sentinel IIA y Landsat 8). Los resultados indican que los UAV son interesantes para la caracterización de las parcelas de viña con alta variabilidad espacial, a pesar de la baja cobertura vegetal de estos cultivos. [ENG] 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 multispectral camera 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 by the generation of 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 IIA and Landsat 8). The results indicate that UAVs are a promising option for the characterization of vineyard plots with high spatial variability, despite the low vegetative coverage of these crops