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Remote sensing-derived combined index for agricultural drought assessment of rabi pulse crops in Bundelkhand region, India

Author

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  • Abhishek Danodia

    (Indian Institute of Remote Sensing, Indian Space Research Organization)

  • Anuradha Kushwaha

    (Indian Institute of Remote Sensing, Indian Space Research Organization)

  • N. R. Patel

    (Indian Institute of Remote Sensing, Indian Space Research Organization)

Abstract

In this study, a novel approach defined for drought severity of Bundelkhand region of India, especially for rabi (winter) season crops using analytical hierarchy process established a Multi-Criteria Decision-Making approach based combined drought index (CDI). The remote sensing multi-sensor derived datasets, as long-term MODIS satellite data, rainfall from CHIRPS datasets and soil moisture from Era Interim datasets, used for quantification for the 2001–2018 period. The CDI is generated by integrated multi-spectral indices as Vegetation Condition Index, Temperature Condition Index, Precipitation Condition Index, Soil Moisture Condition Index using analytical hierarchy process derived weightage with a consistency ratio of 4.2% and consistency index of 0.038 value. The results show that Jalaun, Hamirpur and Banda districts as Northern part affected more as compared to Lalitpur and parts of Jhansi districts as the Southern part of the study area. The statistical analysis illustrated a significant correlation between crop yield anomaly and CDI for all districts for rabi pulses crops. Thus, a geospatial platform-based approach using historical earth observations with analytical hierarchy process integrated expert advice to finalize variables and their weighing will make this methodology more realistic, easier and quicker to apply in future at any region. Eventually, remote sensing can address the drought risk or severity for all kind of crop ecosystem by using cohesive approach derived from multi-sensor satellite datasets.

Suggested Citation

  • Abhishek Danodia & Anuradha Kushwaha & N. R. Patel, 2021. "Remote sensing-derived combined index for agricultural drought assessment of rabi pulse crops in Bundelkhand region, India," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(10), pages 15432-15449, October.
    • Handle: RePEc:spr:endesu:v:23:y:2021:i:10:d:10.1007_s10668-021-01305-3
    DOI: 10.1007/s10668-021-01305-3
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    References listed on IDEAS

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    1. Saaty, Thomas L., 1990. "How to make a decision: The analytic hierarchy process," European Journal of Operational Research, Elsevier, vol. 48(1), pages 9-26, September.
    2. N. Patel & Kamana Yadav, 2015. "Monitoring spatio-temporal pattern of drought stress using integrated drought index over Bundelkhand region, India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 77(2), pages 663-677, June.
    3. Saaty, Thomas L. & Vargas, Luis G., 1987. "Uncertainty and rank order in the analytic hierarchy process," European Journal of Operational Research, Elsevier, vol. 32(1), pages 107-117, October.
    4. Pandey, S. & Bhandari, H. & Hardy, B., 2007. "Economic Costs of Drought and Rice Farmers’ Coping Mechanisms: A Cross-Country Comparative Analysis," IRRI Books, International Rice Research Institute (IRRI), number 281814.
    5. Arnab Kundu & N. R. Patel & S. K. Saha & Dipanwita Dutta, 2017. "Desertification in western Rajasthan (India): an assessment using remote sensing derived rain-use efficiency and residual trend methods," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 86(1), pages 297-313, March.
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