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IVES 9 IVES Conference Series 9 Development of a GRASS-GIS application for the characterization of vineyards in the province of Trento

Development of a GRASS-GIS application for the characterization of vineyards in the province of Trento

Abstract

The physical factors that influence the grape ripening include elevation, slope, aspect, potential global radiation, sun hours and soil type of the vineyards.

Many of these features could be derived from Digital Elevation Models (DEM), using Geographic Information Systems (GIS). There are several commercial and open-source GIS-applications available and also the geodata are continuously increasing in amount, spatial resolution, frequency, but their use remains matter of specialists!
In the present work we developed an easy to use and open-source application, accessible on the web, exploiting the functionalities of GRASS-GIS in the analysis of geospatial data and PostgreSQL/PostGIS as geodatabase, allowing a rapid characterisation of the sites.

Each vineyard is identified through the compilation of a simple form on the web. The required fields are the cadastral codes of the zone as well as of the parcels, which composes it. After sending the request an automatic procedure starts, which extracts the geometry of the vineyard from the vector cadastral map of the Autonomous Province of Trento, provided by the PAT – S.I.A.T. office (www.siat.provincia.tn.it). The Digital Terrain Model at 10 m resolution (PAT –S.I.A.T.) was used in the open source GIS software GRASS 6.4 to derive the slope and aspect maps (r.slope.aspect function), whereas the cumulated global radiation, and mean insolation (sun hours) during the vegetative period (1st April – 31th October) were calculated at 20 m resolution using the r.sun command. In the following step GRASS GIS performs the query of all the available raster maps (digital elevation model, slope, aspect, etc.) within the limits of the vineyard and returns the correspondent mean values.

Moreover three bioclimatic indices (Winkler, Huglin, and Gladstones) are automatically calculated, based on modelling of 10-years of meteorological data from 64 weather station distributed over the Province, and the elevation of the site.

The data are automatically stored in the ‘vineyards’ table of the database and result immediately available on the web. The procedure is written in php and can be adapted to every region and purpose, modifying the vector and the raster layers. The input of the cadastral data can occur also by means of a comma separated values (.csv) sheet, allowing the characterisation of hundreds of vineyards in few minutes.

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Acevedo-Opazo, C., Tisseyre, B., Ojeda, H., Ortega-Farias, S., Guillaume, S. (2008). Is it possible to assess the spatial variability of vine water status? OENO One, 42(4), 203.
Cohen, Y., Gogumalla, P., Bahat, I., Netzer, Y., Ben-Gal, A., Lenski, I., … Helman, D. (2019). Can time series of multispectral satellite images be used to estimate stem water potential in vineyards? In Precision agriculture ’19, The Netherlands: Wageningen Academic Publishers, pp. 445–451.
Laroche-Pinel, E., Duthoit, S., Albughdadi, M., Costard, A. D., Rousseau, J., Chéret, V., & Clenet, H. (2021). Towards vine water status monitoring on a large scale using sentinel-2 images. remote sensing, 13(9), 1837.
Laroche-Pinel,E. (2021). Suivi du statut hydrique de la vigne par télédétection hyper et multispectrale. Thèse INP Toulouse, France.
Scholander, P.F., Bradstreet, E.D., Hemmingsen, E.A., & Hammel, H.T. (1965). Sap pressure in vascular plants: Negative hydrostatic pressure can be measured in plants. Science, 148(3668), 339–346.

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Optimizing stomatal traits for future climates

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