Use of remotely sensed data for the evaluation of inter-row cover intensity in vineyards

Vineyards are a high-income crop and can also have an important landscape value, especially incertain areas of Italy. Vineyards show large soil erosion rates depending on climate variability, localtopography and vine management. Farming machineries can also determine compaction and affectsoil hydraulic properties, runoff and erosion at different levels depending on inter-rows soilmanagement.This work, with focus on a pilot area located in the municipality of Carpeneto, Alessandria province(Piedmont, NW Italy), concerns the adoption of satellite optical data from the Copernicus Sentinel 2(S2) mission to describe vineyard properties. A first analysis was addressed at testing if and how S2data can map differences in vineyards management and behaviour. It was achieved at field level withreference to some experimental plots presenting different inter-row soil management (tillage -CT-,tillage with downstream 10-m-strip grass cover -ST- and total permanent grass cover -GC-).Reference vineyards were placed on sloping areas and set with up-and-down tillage ('rittochino' inItalian language). A NDVI image time series (TS) was obtained from the level 2 S2 data for thegrowing season 2017-2018. TS was processed at plot level and proved to be effective in showingvegetation response to mechanical interventions during the growing season; in particular ripping inCT and shredding in GC in late spring and, during summer, mowing and topping were highlighted;minor variations in NDVI were observed after harvest in all plots.Secondly, a wider analysis was achieved including all the vineyards located in the municipality ofCarpeneto. These were mapped by photo-interpretation and grouped in clusters with reference to thelocal NDVI TS (averaged at plot level). Clustering was obtained by K-means unsupervisedclassification. Results suggest that vineyards can be classified according to the intensity of inter-row'ssoil management.A further analysis was aimed at exploring the role of the native S2 bands in describing vineyarddifferences and inter-row coverage. Preliminary results suggest that single-bands data could be jointlyused with vegetation indices to better describe vine growth dynamics in row-crops. Further studieson remotely sensed data could provide spatially variable inputs for applications in erosion riskmanagement and land analysis.