| publications-2261 |
Peer reviewed articles |
2017 |
I. Campos, C.M.U. Neale, A. Calera |
Is row orientation a determinant factor for radiation interception in row vineyards? |
Australian Journal of Grape and Wine Research |
10.1111/ajgw.12246 |
AI & Machine Learning |
Uncategorized |
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No abstract available |
633945 |
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| publications-2262 |
Peer reviewed articles |
2017 |
J. Villodre, I. Campos, H. Lopez-Corcoles, J. Gonzalez-Piqueras, L. GonzĂĄlez, V. Bodas, S. Sanchez-Prieto, A. Osann, A. Calera |
Mapping Optimum Nitrogen Crop Uptake |
Advances in Animal Biosciences |
10.1017/S2040470017000231 |
Uncategorized |
Precipitation & Ecological Systems |
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No abstract available |
633945 |
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| publications-2263 |
Peer reviewed articles |
2015 |
Silvia Vanino, Giuseppe Pulighe, Pasquale Nino, Carlo De Michele, Salvatore Bolognesi, Guido DâUrso |
Estimation of Evapotranspiration and Crop Coefficients of Tendone Vineyards Using Multi-Sensor Remote Sensing Data in a Mediterranean Environment |
Remote Sensing |
10.3390/rs71114708 |
Uncategorized |
Precipitation & Ecological Systems |
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The sustainable management of water resources plays a key role in Mediterranean viticulture, characterized by scarcity and competition of available water. This study focuses on estimating the evapotranspiration and crop coefficients of table grapes vineyards trained on overhead âtendoneâ systems in the Apulia region (Italy). Maximum vineyard transpiration was estimated by adopting the âdirectâ methodology for ETp proposed by the Food and Agriculture Organization in Irrigation and Drainage Paper No. 56, with crop parameters estimated from Landsat 8 and RapidEye satellite data in combination with ground-based meteorological data. The modeling results of two growing seasons (2013 and 2014) indicated that canopy growth, seasonal and 10-day sums evapotranspiration values were strictly related to thermal requirements and rainfall events. The estimated values of mean seasonal daily evapotranspiration ranged between 4.2 and 4.1 mm·dâ1, while midseason estimated values of crop coefficients ranged from 0.88 to 0.93 in 2013, and 1.02 to 1.04 in 2014, respectively. The experimental evapotranspiration values calculated represent the maximum value in absence of stress, so the resulting crop coefficients should be used with some caution. It is concluded that the retrieval of crop parameters and evapotranspiration derived from remotely-sensed data could be helpful for downscaling to the field the local weather conditions and agronomic practices and thus may be the basis for supporting grape growers and irrigation managers. |
633945 |
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| publications-2264 |
Peer reviewed articles |
2018 |
Spiegel, H., Mosleitner, T.; Sandén T.; Zaller J.G. |
Effects of two decades of organic and mineral fertilization of arable crops on earthworms and standardized litter decomposition. |
Die Bodenkultur, 62, 17-28. |
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Uncategorized |
Precipitation & Ecological Systems |
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No abstract available |
633945 |
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| publications-2265 |
Peer reviewed articles |
2018 |
Isidro Campos, Christopher M.U. Neale, Timothy J. Arkebauer, Andrew E. Suyker, Ivo Z. Gonçalves |
Water productivity and crop yield: A simplified remote sensing driven operational approach |
Agricultural and Forest Meteorology |
10.1016/j.agrformet.2017.07.018 |
Data Management & Analytics |
Uncategorized |
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No abstract available |
633945 |
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| publications-2266 |
Peer reviewed articles |
2018 |
Dalezios N.R., Dercas N., and Eslamian S.S. |
Water scarcity management: part 2: satellite-based composite drought analysis |
International Journal of Global Environmental Issues |
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Simulation & Modeling |
Irrigation Systems |
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No abstract available |
633945 |
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| publications-2267 |
Peer reviewed articles |
2017 |
S. Stamatiadis, J. S. Schepers, E. Evangelou, C. Tsadilas, A. Glampedakis, M. Glampedakis, N. Dercas, N. Spyropoulos, N. R. Dalezios, K. Eskridge |
Variable-rate nitrogen fertilization of winter wheat under high spatial resolution |
Precision Agriculture |
10.1007/s11119-017-9540-7 |
Simulation & Modeling |
Precipitation & Ecological Systems |
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No abstract available |
633945 |
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| publications-2268 |
Peer reviewed articles |
2018 |
G. B. Chirico, A. Pelosi, C. De Michele, S. Falanga Bolognesi, G. D'Urso |
Forecasting potential evapotranspiration by combining numerical weather predictions and visible and near-infrared satellite images: an application in southern Italy |
The Journal of Agricultural Science |
10.1017/s0021859618000084 |
Simulation & Modeling |
Precipitation & Ecological Systems |
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AbstractIrrigation according to reliable estimates of crop water requirements (CWR) is one of the key strategies to ensure long-term sustainability of irrigated agriculture. In southern Mediterranean regions, during the irrigation season, CWR is almost totally controlled by the potential evapotranspiration of the irrigated crop. An innovative system for forecasting crop potential evapotranspiration (ETp) has been implemented recently in the Campania region (southern Italy). The system produces ETp forecasts with a lead time of up to 5 days, by coupling the visible and near-infrared crop imagery with numerical weather prediction outputs of a limited area model. The forecasts are delivered to farmers with a simple and intuitive web app interface, which makes daily real-time ETp maps accessible from desktop computers, tablets and smartphones. Forecast performances were evaluated for maize fields of two farms in two irrigation seasons (2014â2015). The mean absolute bias of the forecasted ETp was <0.3 mm/day and the RMSE was <0.6 mm/day, both for lead times up to 5 days. |
633945 |
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| publications-2269 |
Peer reviewed articles |
2005 |
Marie Launay, Martine Guerif |
Assimilating remote sensing data into a crop model to improve predictive performance for spatial applications |
Agriculture, Ecosystems & Environment |
10.1016/j.agee.2005.06.005 |
Simulation & Modeling |
Irrigation Systems |
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No abstract available |
633945 |
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| publications-2270 |
Peer reviewed articles |
2017 |
F. Vuolo, L. Essl, L. Zappa, T. Sandén, H. Spiegel |
Water and nutrient management: the Austria case study of the FATIMA H2020 project |
Advances in Animal Biosciences |
10.1017/s2040470017000541 |
Data Management & Analytics |
Precipitation & Ecological Systems |
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No abstract available |
633945 |
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