Modeling SP Atial-Temporal Wine Yield Based on Land Surface Temperature, Vegetation Indices and GIS - The Case of the Douro Wine Region

This work aims to integrate Remote Sensing (RS) and cadastral data in QGIS software to perform the spatiotemporal mapping of Wine Yield (WY) cluster zones in the Douro region. Spatiotemporal modelling approach for prediction of wine yield was based on Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST) and topographic data. The results showed that 74% $(\mathrm{R}^{2}=0.744,\ \mathrm{n}=128,\ \mathrm{p} WY interannual variability at administrative division could be explained by the developed model. This information allows establishing wine production region pattern which can improve the agronomic and economic efficiency of vineyard and winery operations.