TY - JOUR
T1 - Double-scale analysis on the detectability of irrigation signals from remote sensing soil moisture over an area with complex topography in central Italy
AU - Dari, Jacopo
AU - Brocca, Luca
AU - Quintana-Seguí, Pere
AU - Casadei, Stefano
AU - Escorihuela, María José
AU - Stefan, Vivien
AU - Morbidelli, Renato
N1 - Funding Information:
The authors acknowledge the support from European Space Agency under the IRRIGATION+ project (contract n. 4000129870/20/I-NB). The authors wish to thank the AFOR (Agenzia FOrestale Regionale) Umbria and VISTA (Vetrina Informatica per Sistemi di Trasparenza nell'Agroalimentare) project for providing the ground truth data on the irrigation occurrence used in this study. The authors thank the THEIA Pole.
Funding Information:
The authors acknowledge the support from European Space Agency under the IRRIGATION+ project (contract n. 4000129870/20/I-NB ). The authors wish to thank the AFOR (Agenzia FOrestale Regionale) Umbria and VISTA (Vetrina Informatica per Sistemi di Trasparenza nell'Agroalimentare) project for providing the ground truth data on the irrigation occurrence used in this study. The authors thank the THEIA Pole.
Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/3
Y1 - 2022/3
N2 - Despite a detailed knowledge of the spatial-temporal dynamics of irrigation being necessary to optimize the agricultural production without exacerbating the pressure exercised on the water resource, such information is still often lacking worldwide. In this study, a double-scale analysis on the detectability of the irrigation occurrence over an area in central Italy through remote sensing soil moisture is proposed; the period of interest is a 3-year time span from 2017 to 2019. The detectability of district- or sub-district-scale irrigation signals through remotely sensed soil moisture data is investigated at two different spatial resolutions: 1 km and plot scale. Three soil moisture products sampled at 1 km resolution are evaluated: a DISPATCH (DISaggregation based on Physical And Theoretical scale CHange) downscaled version of SMAP (Soil Moisture Active Passive) and two Sentinel-1-derived products, namely the 1 km version delivered by Copernicus and a plot-scale-born version developed by THEIA and aggregated at 1 km. The THEIA Sentinel-1 product aggregated at 100 m is used in the plot-scale analysis. Over the study area, the irrigation extent is determined by the fragmentation of the agricultural fields and the complex topography, making the adoption of plot-scale data necessary. Satisfactory results are obtained by comparing maps of irrigated areas at 100 m spatial resolution produced through the k-means clustering algorithm with ground-truth data, since the method fails only once out of seven in properly reproducing the irrigated or non-irrigated conditions occurred over four pilot agricultural fields.
AB - Despite a detailed knowledge of the spatial-temporal dynamics of irrigation being necessary to optimize the agricultural production without exacerbating the pressure exercised on the water resource, such information is still often lacking worldwide. In this study, a double-scale analysis on the detectability of the irrigation occurrence over an area in central Italy through remote sensing soil moisture is proposed; the period of interest is a 3-year time span from 2017 to 2019. The detectability of district- or sub-district-scale irrigation signals through remotely sensed soil moisture data is investigated at two different spatial resolutions: 1 km and plot scale. Three soil moisture products sampled at 1 km resolution are evaluated: a DISPATCH (DISaggregation based on Physical And Theoretical scale CHange) downscaled version of SMAP (Soil Moisture Active Passive) and two Sentinel-1-derived products, namely the 1 km version delivered by Copernicus and a plot-scale-born version developed by THEIA and aggregated at 1 km. The THEIA Sentinel-1 product aggregated at 100 m is used in the plot-scale analysis. Over the study area, the irrigation extent is determined by the fragmentation of the agricultural fields and the complex topography, making the adoption of plot-scale data necessary. Satisfactory results are obtained by comparing maps of irrigated areas at 100 m spatial resolution produced through the k-means clustering algorithm with ground-truth data, since the method fails only once out of seven in properly reproducing the irrigated or non-irrigated conditions occurred over four pilot agricultural fields.
KW - Irrigation detection
KW - Irrigation mapping
KW - K-means algorithm
KW - Land surface modeling
KW - Remote sensing
KW - Soil moisture
KW - Temporal stability
UR - https://www.scopus.com/pages/publications/85123602985
U2 - 10.1016/j.advwatres.2022.104130
DO - 10.1016/j.advwatres.2022.104130
M3 - Article
AN - SCOPUS:85123602985
SN - 0309-1708
VL - 161
JO - Advances in Water Resources
JF - Advances in Water Resources
M1 - 104130
ER -
SDG 2 Zero Hunger