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Real-Time Agricultural Drought Monitoring in the Horn of Africa using MODIS and CHIRPS Data

Dr. Abebe Tesfaye, Halima Ibrahim
Published
December 18, 2023
Read Time
10 minutes
Citations
23
Field
sustainable_development

Abstract

Development of drought early warning system integrating MODIS vegetation indices with CHIRPS rainfall data, providing 30-day lead time for agricultural drought conditions across Ethiopia, Kenya, and Somalia.

Citation

apa
Dr. Abebe Tesfaye, Halima Ibrahim (2023). Real-Time Agricultural Drought Monitoring in the Horn of Africa using MODIS and CHIRPS Data. SpatioNEX Research.
mla
Dr. Abebe Tesfaye, Halima Ibrahim. "Real-Time Agricultural Drought Monitoring in the Horn of Africa using MODIS and CHIRPS Data." SpatioNEX Research, 2023.
chicago
Dr. Abebe Tesfaye, Halima Ibrahim. "Real-Time Agricultural Drought Monitoring in the Horn of Africa using MODIS and CHIRPS Data." SpatioNEX Research (2023).
bibtex
@article{spationex,
  title={Real-Time Agricultural Drought Monitoring in the Horn of Africa using MODIS and CHIRPS Data},
  author={Dr. Abebe Tesfaye, Halima Ibrahim},
  journal={SpatioNEX Research},
  year={2023},
  volume={null},
  pages={null},
  doi={null}
}

The Horn of Africa faces recurrent drought events threatening food security for millions. This innovation brief presents a real-time monitoring system for agricultural drought using satellite-derived indices.

System Components

1. MODIS NDVI/EVI for vegetation health assessment

2. CHIRPS rainfall estimates

3. Vegetation Condition Index (VCI) calculation

4. Temperature Condition Index (TCI) from MODIS LST

5. Vegetation Health Index (VHI) as combined drought indicator

Validation

• System accuracy: 89.7% compared to ground observations

• Successful prediction of 2022 drought in Eastern Kenya 35 days in advance

• Currently operational for 12 million hectares of agricultural land

Publication Details

Funding
USAID

Keywords

drought monitoring
agriculture
MODIS
CHIRPS
food security
early warning
Horn of Africa
remote sensing

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