Monthly drought Soil Moisture Anomalies (SMA) at 1 km from soil moisture data of the TU Wien Copernicus - Sentinel 1 RT1 dataset over Italy, monthly time-series (2017-2022)

General Description

Monthly drought Soil Moisture Anomalies (SMA) at 1 km from soil moisture data of the TU Wien Copernicus - Sentinel 1 RT1 dataset over Italy, monthly time-series (2017-2022)The Soil Moisture Anomalies (SMA) dataset is generated using the soil moisture dataset of the TU Wien  Copernicus - Sentinel 1 RT1 dataset. The dataset time spans from 2017 to September 2022. The dataset is applicable in analysing the soil moisture alterations down to the local scale, as well as in evaluating the multiple other processes dependent on the evolution of soil moisture not only in the hydrosphere but also in the atmosphere and biosphere. The dataset includes:

Monthly time-series:

Monthly aggregated SMA generated aggreagating soil moisture anomalies at dekad (10-day period) scale.

Data Details

Time period: Jan 2017 – September 2022

Type of data: Soil moisture anomaly data aggregated at monthly temporal scale

How the data was collected or derived: TU Wien Copernicus - Sentinel 1 RT1 soil moisture dataset obtained using Python.

Statistical methods used: standardized soil moisture anomalies.

Coordinate reference system: EPSG:4326

Bounding box (Xmin, Ymin, Xmax, Ymax): (-60, 20, 70, 88)

Spatial resolution: 0.008333 d.d. (1km)

Image size: 15600 x 8160 pixels

File format: Cloud Optimized Geotiff (COG) format.

Support

If you discover a bug, artefact, or inconsistency, or if you have a question please contact: [e-mail]

Reference

Brocca, L., Gaona, J., Bavera, D., Fioravanti, G., Puca, S., Ciabatta, L., ... & Wagner, W. (2024). Exploring the actual spatial resolution of 1 km satellite soil moisture products. Science of the Total Environment, 945, 174087. https://doi.org/10.1016/j.scitotenv.2024.174087

Name convention

To ensure consistency and ease of use across and within the projects, we follow the standard Open-Earth-Monitor file-naming convention. The convention works with 10 fields that describe important properties of the data. In this way, users can search files, prepare data analysis etc, without needing to open files. The fields are:

Generic variable name: ssma= Surface Soil Moisture Anomaly

Variable procedure combination: s1.rt1 = Sentinel 1 RT1 Copernicus TU-Wien dataset.

Statistical methods used: Mean per month.

Spatial support: 1 km

Depth reference: s5cm = surface soil moisture in the uppermost 5 cm layer

Time reference begin time: 20170101 = 2017-01-01

Time reference end time: 20220930 = 2022-09-30

Bounding box: it = Italy

EPSG code: epsg4326 = EPSG:4326

Version code: v20240310 = 2024-03-10 (creation date)