The Danube Basin has been hit by several droughts in the last few years. As climate change makes weather extremes and temperature records in late winter and early spring more likely, water availability and irrigation possibilities become more important. In this paper, the crop water demand at field and national scale within the Danube Basin is presented using a dense time series of multispectral Sentinel-2 data, for crop type maps derived with deep learning techniques and physically-based models for crop parameter retrieval and crop growth modelling.

Crop Water Availability Mapping in the Danube Basin Based on Deep Learning, Hydrological and Crop Growth Modelling / Migdall, Silke; Dotzler, Sandra; Gleisberg, Eva; Appel, Florian; Muerth, Markus; Bach, Heike; Weikmann, Giulio; Paris, Claudia; Marinelli, Daniele; Bruzzone, Lorenzo. - In: ENGINEERING PROCEEDINGS. - ISSN 2673-4591. - 9:1(2022), pp. 42.1-42.5. (Intervento presentato al convegno EFITA 2021 tenutosi a Online nel 25th-26th May 2021) [10.3390/engproc2021009042].

Crop Water Availability Mapping in the Danube Basin Based on Deep Learning, Hydrological and Crop Growth Modelling

Weikmann, Giulio;Paris, Claudia;Marinelli, Daniele
Penultimo
;
Bruzzone, Lorenzo
Ultimo
2022-01-01

Abstract

The Danube Basin has been hit by several droughts in the last few years. As climate change makes weather extremes and temperature records in late winter and early spring more likely, water availability and irrigation possibilities become more important. In this paper, the crop water demand at field and national scale within the Danube Basin is presented using a dense time series of multispectral Sentinel-2 data, for crop type maps derived with deep learning techniques and physically-based models for crop parameter retrieval and crop growth modelling.
2022
The 13th EFITA International Conference
Basel, CH
MDPI
Migdall, Silke; Dotzler, Sandra; Gleisberg, Eva; Appel, Florian; Muerth, Markus; Bach, Heike; Weikmann, Giulio; Paris, Claudia; Marinelli, Daniele; Br...espandi
Crop Water Availability Mapping in the Danube Basin Based on Deep Learning, Hydrological and Crop Growth Modelling / Migdall, Silke; Dotzler, Sandra; Gleisberg, Eva; Appel, Florian; Muerth, Markus; Bach, Heike; Weikmann, Giulio; Paris, Claudia; Marinelli, Daniele; Bruzzone, Lorenzo. - In: ENGINEERING PROCEEDINGS. - ISSN 2673-4591. - 9:1(2022), pp. 42.1-42.5. (Intervento presentato al convegno EFITA 2021 tenutosi a Online nel 25th-26th May 2021) [10.3390/engproc2021009042].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/330200
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