Soil Moisture Prediction for Eastern Africa 1991-2023 [Part 2]: Combined and Gap-filled Random Forest Replication Files.

Published: 24 March 2026| Version 1 | DOI: 10.17632/pwz9ncnybs.1
Contributor:
Zoe Helbing

Description

The attached datasets enable the prediction of soil moisture (SM) over Eastern Africa from 1991-2023. For this, the following files are provided: 1. [Available in other Dataset]: SM estimations: European Space Agency Climate Change Initiative Soil Moisture (ESA CCI SM) processed data including the active, passive, combined, and gap-filled product from 1991 to 2023. 2. [Available in other Dataset]: Predictors: El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), Vegetation Optical Depth (VOD), Elevation, Slope, Aspect, MODIS Land Cover, Preciptation, Temperature, Urban Extend, and Seasonality. 3. Random Forest (RF) Replication: For each ESA CCI SM dataset (active, passive, combined, gap-filled), a parquet and pkl file is provided to analyse and replicate predicton processes. Due to upload limitations, only the combined and gap-filled are uploaded here, the active and passive are available in another database.

Files

Categories

Remote Sensing, Climate Prediction, Machine Learning, Africa, Eastern Africa, Soil Moisture, Microwave Remote Sensing

Licence