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This study assesses drought in Rajasthan, one of India’s most drought-affected states. The study region’s agriculture drought condition is assessed using GIS and remote sensing (RS) techniques. The drought condition is analyzed using both spatial and non-spatial datasets. To maximize efficiency, temporal pictures from MODIS and NOAA-AVHRR satellites are used as alternate sources for the study. Drought is measured using the Normalized Difference Vegetation Index (NDVI), the Vegetation Condition Index (VCI), and the meteorological-based Standardized Precipitation Index. From the satellite images, NDVI values are obtained through GIS processing, and then they are used to derive the values of VCI and generate drought maps. The SPI index is also derived utilizing observed precipitation data to classify the drought regions based on precipitation variation. The obtained results prove and justify the usefulness of RS and GIS techniques for drought assessment and identification of drought conditions.

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Drought Assessment of Rajasthan Using NDVI, VCI, and SPI Index

  • 会议论文

  • 发表日期：

    2025年

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  • Dharm Raj Bairwa,
  • Manoj Kumar Diwakar

摘要

This study assesses drought in Rajasthan, one of India’s most drought-affected states. The study region’s agriculture drought condition is assessed using GIS and remote sensing (RS) techniques. The drought condition is analyzed using both spatial and non-spatial datasets. To maximize efficiency, temporal pictures from MODIS and NOAA-AVHRR satellites are used as alternate sources for the study. Drought is measured using the Normalized Difference Vegetation Index (NDVI), the Vegetation Condition Index (VCI), and the meteorological-based Standardized Precipitation Index. From the satellite images, NDVI values are obtained through GIS processing, and then they are used to derive the values of VCI and generate drought maps. The SPI index is also derived utilizing observed precipitation data to classify the drought regions based on precipitation variation. The obtained results prove and justify the usefulness of RS and GIS techniques for drought assessment and identification of drought conditions.