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Semantic Scholar Open Access 2021 1 sitasi

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

Paulo Jorge Pires Moreira L. Duarte M. Cunha A. Teodoro
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Abstrak

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% $(\mathrm{R}^{2}=0.744,\ \mathrm{n}=128,\ \mathrm{p} < 0.000)$ 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.

Topik & Kata Kunci

Computer Science

Penulis (4)

P

Paulo Jorge Pires Moreira

L

L. Duarte

M

M. Cunha

A

A. Teodoro

Format Sitasi

APA MLA BibTeX
Moreira, P.J.P., Duarte, L., Cunha, M., Teodoro, A. (2021). Modeling SP Atial-Temporal Wine Yield Based on Land Surface Temperature, Vegetation Indices and GIS - The Case of the Douro Wine Region. https://doi.org/10.1109/IGARSS47720.2021.9554857

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Lihat di Sumber doi.org/10.1109/IGARSS47720.2021.9554857
Informasi Jurnal
Tahun Terbit
2021
Bahasa
en
Total Sitasi
1×
Sumber Database
Semantic Scholar
DOI
10.1109/IGARSS47720.2021.9554857
Akses
Open Access ✓