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Seasonal Pattern Analysis of Multi-Source Drought Indicators Remote Sensing in Beed District, Maharashtra

Author

Listed:
  • Neha Andure
  • Ankush Kadam
  • Sonali Jadhav
  • Sidheshwa Raut
  • Shafiyoddin Sayya

Abstract

Drought is a major challenge in the semi-arid regions of India, particularly in Beed District. This study analysed seasonal drought patterns using multi-source remote sensing datasets from 2010–2025, including NDVI, VCI, VHI, NDWI, SPI-12, LST, and SMI. The indices were integrated using a Composite Drought Index (CDI) and processed in the Google Earth Engine (GEE) platform. The results showed that drought severity increased progressively from Kharif to Rabi and Summer. The highest vegetation condition was observed during Kharif (NDVI = 0.2635), while Summer exhibited the lowest vegetation health (VHI = 13.96) and highest thermal stress (LST = 25.27°C). The mean CDI decreased from 45.62 in Kharif to 24.67 in Summer, while drought frequency increased from 25–30% to 70–75%.The findings demonstrate the effectiveness of remote sensing for seasonal drought monitoring and support drought management strategies in drought-prone regions.

Suggested Citation

  • Neha Andure & Ankush Kadam & Sonali Jadhav & Sidheshwa Raut & Shafiyoddin Sayya, 2026. "Seasonal Pattern Analysis of Multi-Source Drought Indicators Remote Sensing in Beed District, Maharashtra," International Journal of Scientific Research in Science and Technology, Technoscience Academy, vol. 13(3), pages 1209-1217, June.
    • Handle: RePEc:etm:ijsrst:v13:y2026:i3:id:1717
    DOI: 10.32628/IJSRST26133260
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