Ahmed et al. (2025) A Continental-Scale tracking for mobile drought dynamics across Africa using Multivariate drought Index Fusion

Identification

• Journal: International Journal of Applied Earth Observation and Geoinformation
• Year: 2025
• Date: 2025-10-18
• Authors: N. K. Ahmed, Shuanggen Jin
• DOI: 10.1016/j.jag.2025.104917

Research Groups

• Shanghai Astronomical Observatory, Chinese Academy of Sciences, China
• School of Astronomy and Space Science, University of Chinese Academy of Sciences, China
• School of Artificial Intelligence, Anhui University, China
• School of Surveying and Land Information Engineering, Henan Polytechnic University, China
• Civil Engineering Department, Faculty of Engineering, Sohag University, Egypt

Short Summary

This study proposes a novel Multivariate Drought Index Fusion (MDIF) to dynamically track the spatiotemporal trajectory of mobile drought fronts across Africa from 2000 to 2024, revealing persistent drought hotspots and a dominant northeast-to-southwest propagation pathway.

Objective

• To develop a multivariate drought index (MDIF) by combining remote sensing and climatic indicators using Principal Component Analysis (PCA).
• To compare the proposed MDIF index with globally accepted Standardized Precipitation Index (SPI) and Vegetation Health Index (VHI) using correlation and time series analysis.
• To track drought front dynamics across Africa from 2000 to 2024, quantifying their spatiotemporal characteristics (speed, direction, distance).
• To analyze the long-term trends and persistent corridors of drought propagation using statistical and spatial analysis techniques.

Study Configuration

• Spatial Scale: Entire African continent (approximately 30 million square kilometers), with data re-sampled to a consistent spatial resolution of 0.1 degrees (approximately 10 kilometers). Minimum drought patch area tracked was 1,000 square kilometers.
• Temporal Scale: 2000 to 2024 (25 years), with monthly temporal resolution.

Methodology and Data

• Models used:
  • Multivariate Drought Index Fusion (MDIF) based on Principal Component Analysis (PCA).
  • Connected Component Labeling (CCL) algorithm for identifying drought clusters.
  • Vector tracking algorithms for calculating drought front velocity and direction.
  • Bilinear interpolation for spatial consistency and resolution harmonization.
• Data sources:
  • Satellite:
    • MODIS MOD13Q1 Normalized Difference Vegetation Index (NDVI) (250 m, 16-day composites, aggregated monthly).
    • MODIS MOD11A2 Land Surface Temperature (LST) (1 km, 8-day composites, aggregated monthly).
    • NOAA STAR Vegetation Health Index (VHI) (4 km, weekly, aggregated monthly).
    • MODIS MCD12Q1 Land Cover (500 m) for non-vegetation masking.
  • Observation/Reanalysis:
    • Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) v2.0 precipitation (0.05 degrees, monthly).
    • SPEIbase v2.7 Standardized Precipitation-Evapotranspiration Index (SPEI) at a 3-month timescale (0.5 degrees, monthly).

Main Results

• The MDIF exhibited significant correlations with SPI-3 (Pearson correlation coefficient, r = 0.72–0.84) in arid and semi-arid regions, and with VHI (r = 0.76–0.87) over vegetated regions, confirming its robustness in capturing both meteorological and ecological drought conditions.
• The Horn of Africa was identified as a long-term drought hotbed, experiencing severe events during 2006, 2011, 2017–2019, and 2022–2023.
• Southern Africa experienced severe multi-year droughts from 2014 to 2017, with other extensive episodes in 2001–2002 and 2005–2006.
• Tracking analysis, for the first time, indicated a dominant northeast-to-southwest trajectory of drought fronts over sub-Saharan Africa.
• Highest drought front propagation speeds were observed in Southern Africa (e.g., south Angola, north Namibia, south Mozambique), reaching up to 180 kilometers per month.
• Drought front density hotspots were identified in southern Madagascar (>120 fronts) and north Algeria/Libya (>100 fronts).

Contributions

• Development of a novel Multivariate Drought Index Fusion (MDIF) based on PCA, integrating multiple remote sensing and climatic indicators for comprehensive drought monitoring.
• First-ever continent-scale algorithmic surveillance of mobile drought fronts across Africa, quantifying their density, velocity, and dominant directions of propagation.
• Shifts the paradigm from static drought mapping to dynamic propagation analysis, providing new scientific understanding of droughts as moving phenomena.
• Enhances continental drought early warning systems by offering dynamic mapping of drought intensity and mobility, crucial for resilience planning and transboundary management.

Funding

• Henan International Science and Technology Cooperation Key Project (Grant No. 241111520700)
• Henan Department of Education’s “Double First-Class” Project (Grant No. 760507/033)
• Henan Polytechnic University Startup Foundation Project (Grant No. 722403/067/002)

Citation

@article{Ahmed2025ContinentalScale,
  author = {Ahmed, N. K. and Jin, Shuanggen},
  title = {A Continental-Scale tracking for mobile drought dynamics across Africa using Multivariate drought Index Fusion},
  journal = {International Journal of Applied Earth Observation and Geoinformation},
  year = {2025},
  doi = {10.1016/j.jag.2025.104917},
  url = {https://doi.org/10.1016/j.jag.2025.104917}
}