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

Domaine:

environment and energyclimate

Type de record:

dataset
Créateur:
Hel
Éditeur:
Men
Hôte:avatar
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.

Visit

doi.orgdata.mendeley.com

Tags

Remote SensingClimate PredictionMachine LearningAfricaEastern AfricaSoil MoistureMicrowave Remote Sensing

Licenses

info:eu-repo/semantics/openAccessCreative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcode

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