Trisulistiani, Fifin
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Spatio-Temporal Modeling of Agricultural Drought in Indramayu Using the NDDI Index (2015-2024) Septiani, Sypa; Siahan, Irene; Talitha Aqilah, Hilya; Oktaviani, Dela; Trisulistiani, Fifin; Alifia, Salwa; Handayani, Tiara; Zahrotunnisa, Siti
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2025 No. 1 (2025): Proceedings of 2025 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2025i1.635

Abstract

This study examines the spatio-temporal patterns of agricultural drought in Indramayu Regency, Indonesia, using the Normalized Difference Drought Index (NDDI) derived from Landsat imagery between 2015 and 2024. The analysis employed spatial autocorrelation techniques, including Global Moran’s I and Local Indicators of Spatial Association (LISA), to identify spatial clustering and persistence of drought conditions. The results show consistent spatial vulnerability, with the southern region forming stable High-High drought clusters across multiple years, while the northern region remains dominated by LowLow clusters. These findings indicate that drought distribution in Indramayu demonstrates strong spatial persistence and temporal continuity, reflecting long-term environmental and landuse characteristics. A supporting correlation analysis between NDDI and rice productivity (? = 0.164; p-value = 0.651) revealed no significant relationship, suggesting that effective irrigation systems have mitigated the impact of meteorological drought on agricultural output. Overall, the study highlights the need for location-specific drought management in spatially vulnerable southern areas to enhance agricultural resilience and regional food security.