On the potential of Advanced Microwave Sounding Unit (AMSU) data for assessing soil moisture variability in the Basilicata Region

Soil moisture (SM) data can be used in various contexts related to the hydrological cycle, including agricultural monitoring, water resource management, and natural hazard assessment. In recent years, remote sensing data have been widely used to retrieve SM data at different spatial and temporal scales. In this study, we investigated the potential of the Soil Wetness Index (SWI), an index based on data acquired by the Advanced Microwave Sounding Unit (AMSU) onboard the Meteorological Operational Satellite Program of Europe (MetOp) satellites, to provide reliable information on SM variability over a medium period. SWI variability at the monthly scale in the 2013-2016 period was analyzed for the Basilicata region (southern Italy), and the results, whose accuracy was evaluated for comparison with the SM product generated using the Advanced SCAtterometer (ASCAT) data, seem to indicate the good sensitivity of the proposed index, which showed mean correlation (r) values around 0,73 when considering both MetOp-A and -B satellites.

Authors

Publication Details

Journal
Rendiconti online della Società Geologica Italiana
Published
2025-05-26
DOI
https://doi.org/10.3301/rol.2025.13
Primary Topic
Soil Moisture and Remote Sensing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

On the potential of Advanced Microwave Sounding Unit (AMSU) data for assessing soil moisture variability in the Basilicata Region

Binh Pham‐Duc, Meriam Lahsaini, Raffaele Albano, Teodosio Lacava et al.
Rendiconti online della Società Geologica Italiana
Soil Moisture and Remote Sensing
article

On the potential of Advanced Microwave Sounding Unit (AMSU) data for assessing soil moisture variability in the Basilicata Region

Binh Pham‐Duc, Meriam Lahsaini, Raffaele Albano, Teodosio Lacava, Arianna Mazzariello
article en

Abstract

Soil moisture (SM) data can be used in various contexts related to the hydrological cycle, including agricultural monitoring, water resource management, and natural hazard assessment. In recent years, remote sensing data have been widely used to retrieve SM data at different spatial and temporal scales. In this study, we investigated the potential of the Soil Wetness Index (SWI), an index based on data acquired by the Advanced Microwave Sounding Unit (AMSU) onboard the Meteorological Operational Satellite Program of Europe (MetOp) satellites, to provide reliable information on SM variability over a medium period. SWI variability at the monthly scale in the 2013-2016 period was analyzed for the Basilicata region (southern Italy), and the results, whose accuracy was evaluated for comparison with the SM product generated using the Advanced SCAtterometer (ASCAT) data, seem to indicate the good sensitivity of the proposed index, which showed mean correlation (r) values around 0,73 when considering both MetOp-A and -B satellites.

Rendiconti online della Società Geologica ItalianaVol. 66
Openalex Percentile: Top 89%
Soil Moisture and Remote Sensing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.