Articles | Volume 15, issue 4
https://doi.org/10.5194/essd-15-1555-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-15-1555-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
05 Apr 2023
Data description paper |
| 05 Apr 2023
| 05 Apr 2023
Regional data sets of high-resolution (1 and 6 km) irrigation estimates from space
Department of Civil and Environmental Engineering, University of Perugia,
Perugia, Italy
Research Institute for Geo-Hydrological Protection, National Research
Council, Perugia, Italy
Luca Brocca
Research Institute for Geo-Hydrological Protection, National Research
Council, Perugia, Italy
Sara Modanesi
Research Institute for Geo-Hydrological Protection, National Research
Council, Perugia, Italy
Christian Massari
Research Institute for Geo-Hydrological Protection, National Research
Council, Perugia, Italy
Angelica Tarpanelli
Research Institute for Geo-Hydrological Protection, National Research
Council, Perugia, Italy
Silvia Barbetta
Research Institute for Geo-Hydrological Protection, National Research
Council, Perugia, Italy
Raphael Quast
Department of Geodesy and Geoinformation, Research Unit Remote
Sensing, Vienna University of Technology (TU Wien), Vienna, Austria
Mariette Vreugdenhil
Department of Geodesy and Geoinformation, Research Unit Remote
Sensing, Vienna University of Technology (TU Wien), Vienna, Austria
Vahid Freeman
Earth Intelligence, Spire Global, 2763 Luxembourg, Luxembourg
Anaïs Barella-Ortiz
Observatori de l'Ebre (OE), Ramon Llull University – CSIC, 43520
Roquetes, Spain
Pere Quintana-Seguí
Observatori de l'Ebre (OE), Ramon Llull University – CSIC, 43520
Roquetes, Spain
David Bretreger
School of Engineering, The University of Newcastle, Callaghan, New
South Wales 2308, Australia
Espen Volden
European Space Agency, ESRIN, Frascati, Italy
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Cited
18 citations as recorded by crossref.
- The Temporal-Stability-Based Irrigation MAPping (TSIMAP) Method: A Virtuous Trade-Off between Accuracy, Flexibility, and Facility for End-Users J. Dari et al. 10.3390/w16050644
- Mitigating the impact of dense vegetation on the Sentinel-1 surface soil moisture retrievals over Europe S. Massart et al. 10.1080/22797254.2023.2300985
- Winter snow deficit was a harbinger of summer 2022 socio-hydrologic drought in the Po Basin, Italy F. Avanzi et al. 10.1038/s43247-024-01222-z
- Estimating distributed autumn irrigation water use in a large irrigation district by combining machine learning with water balance models X. Qian et al. 10.1016/j.compag.2024.109110
- The development of an operational system for estimating irrigation water use reveals socio-political dynamics in Ukraine J. Dari et al. 10.5194/hess-28-2651-2024
- Estimating multi-scale irrigation amounts using multi-resolution soil moisture data: A data-driven approach using PrISM G. Paolini et al. 10.1016/j.agwat.2023.108594
- Benefits and pitfalls of irrigation timing and water amounts derived from satellite soil moisture L. Zappa et al. 10.1016/j.agwat.2024.108773
- Retrieving the irrigation actually applied at district scale: Assimilating high-resolution Sentinel-1-derived soil moisture data into a FAO-56-based model P. Laluet et al. 10.1016/j.agwat.2024.108704
- Towards the Improvement of Soil Salinity Mapping in a Data-Scarce Context Using Sentinel-2 Images in Machine-Learning Models J. Sirpa-Poma et al. 10.3390/s23239328
- A Digital Twin of the terrestrial water cycle: a glimpse into the future through high-resolution Earth observations L. Brocca et al. 10.3389/fsci.2023.1190191
- Exploring the actual spatial resolution of 1 km satellite soil moisture products L. Brocca et al. 10.1016/j.scitotenv.2024.174087
- Spatial and temporal forecasting of groundwater anomalies in complex aquifer undergoing climate and land use change A. Talib et al. 10.1016/j.jhydrol.2024.131525
- Integrating hydrologic modeling and satellite remote sensing to assess the performance of sprinkler irrigation C. Zheng et al. 10.1080/10095020.2024.2344615
- An inter-comparison of approaches and frameworks to quantify irrigation from satellite data S. Kragh et al. 10.5194/hess-28-441-2024
- PrISM at Operational Scale: Monitoring Irrigation District Water Use during Droughts G. Paolini et al. 10.3390/rs16071116
- Irrigation impact on boundary layer and precipitation characteristics in Weather Research and Forecasting model simulations during LIAISE‐2021 M. Udina et al. 10.1002/qj.4756
- Regional data sets of high-resolution (1 and 6 km) irrigation estimates from space J. Dari et al. 10.5194/essd-15-1555-2023
- An inter-comparison of approaches and frameworks to quantify irrigation from satellite data S. Kragh et al. 10.5194/hess-28-441-2024
16 citations as recorded by crossref.
- The Temporal-Stability-Based Irrigation MAPping (TSIMAP) Method: A Virtuous Trade-Off between Accuracy, Flexibility, and Facility for End-Users J. Dari et al. 10.3390/w16050644
- Mitigating the impact of dense vegetation on the Sentinel-1 surface soil moisture retrievals over Europe S. Massart et al. 10.1080/22797254.2023.2300985
- Winter snow deficit was a harbinger of summer 2022 socio-hydrologic drought in the Po Basin, Italy F. Avanzi et al. 10.1038/s43247-024-01222-z
- Estimating distributed autumn irrigation water use in a large irrigation district by combining machine learning with water balance models X. Qian et al. 10.1016/j.compag.2024.109110
- The development of an operational system for estimating irrigation water use reveals socio-political dynamics in Ukraine J. Dari et al. 10.5194/hess-28-2651-2024
- Estimating multi-scale irrigation amounts using multi-resolution soil moisture data: A data-driven approach using PrISM G. Paolini et al. 10.1016/j.agwat.2023.108594
- Benefits and pitfalls of irrigation timing and water amounts derived from satellite soil moisture L. Zappa et al. 10.1016/j.agwat.2024.108773
- Retrieving the irrigation actually applied at district scale: Assimilating high-resolution Sentinel-1-derived soil moisture data into a FAO-56-based model P. Laluet et al. 10.1016/j.agwat.2024.108704
- Towards the Improvement of Soil Salinity Mapping in a Data-Scarce Context Using Sentinel-2 Images in Machine-Learning Models J. Sirpa-Poma et al. 10.3390/s23239328
- A Digital Twin of the terrestrial water cycle: a glimpse into the future through high-resolution Earth observations L. Brocca et al. 10.3389/fsci.2023.1190191
- Exploring the actual spatial resolution of 1 km satellite soil moisture products L. Brocca et al. 10.1016/j.scitotenv.2024.174087
- Spatial and temporal forecasting of groundwater anomalies in complex aquifer undergoing climate and land use change A. Talib et al. 10.1016/j.jhydrol.2024.131525
- Integrating hydrologic modeling and satellite remote sensing to assess the performance of sprinkler irrigation C. Zheng et al. 10.1080/10095020.2024.2344615
- An inter-comparison of approaches and frameworks to quantify irrigation from satellite data S. Kragh et al. 10.5194/hess-28-441-2024
- PrISM at Operational Scale: Monitoring Irrigation District Water Use during Droughts G. Paolini et al. 10.3390/rs16071116
- Irrigation impact on boundary layer and precipitation characteristics in Weather Research and Forecasting model simulations during LIAISE‐2021 M. Udina et al. 10.1002/qj.4756
Latest update: 29 Jun 2024
Short summary
Irrigation is the main source of global freshwater consumption. Despite this, a detailed knowledge of irrigation dynamics (i.e., timing, extent of irrigated areas, and amounts of water used) are generally lacking worldwide. Satellites represent a useful tool to fill this knowledge gap and monitor irrigation water from space. In this study, three regional-scale and high-resolution (1 and 6 km) products of irrigation amounts estimated by inverting the satellite soil moisture signals are presented.
Irrigation is the main source of global freshwater consumption. Despite this, a detailed...
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