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Drought severity assessment using automated land surface temperature retrieval technique

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Abstract

Drought affects the natural features, economic conditions, and living beings. Climate change impacts numerous factors linked to drought on a global scale. A temperature rise contributes to a decline in precipitation, evaporation, and transpiration; hydrologic and agricultural dryness results from increased temperature. In deciding the energy flux between the atmosphere and the earth's surface, land surface temperature (LST) is a critical environmental factor. The assessment of the temporal variations of surface temperature and monitoring of drought uses Normalized Difference Vegetation Index (NDVI). The raster calculator in ArcGIS software performs the calculation using the different equations to obtain the vegetation index, land surface emissivity (LSE), brightness temperature, and surface temperature. Integrating the tools in ArcGIS software, the authors created a model for the automatic retrieval of surface temperature. The model results provided the land surface temperature for different years from 2016 to 2020. The minimum and maximum LST derived from the model was ranging from 14.54 to 49.90°C (2016–2020). The minimum and maximum NDVI derived from the model was ranging from -0.97 to 0.99 (2016–2020). The in situ surface temperature and Landsat-derived surface temperature had a 92 % of correlation. There was a nearly 99 % of correlation between NDVI and LST during 2016–2020. Due to the temperature rise and insufficient rainfall, there was stress in crops, and the region experienced a drought situation.

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Data availability

The Landsat satellite data and SRTM DEM required for the research work was obtained from the USGS Earth Explorer website https://earthexplorer.usgs.gov/. The rainfall and temperature data were collected from the State Ground and Surface Water Resources Data Centre, Water Resource Department, Tharamani, Chennai – 600113 and also from State Level Water Testing Laboratory, Tamilnadu Water Supply and Drainage Board, Chepauk, Chennai – 600005. Geology, geomorphology, and soil maps were obtained from National Bureau of Soil Survey & Land Use Planning (NBSS & LUP), Bangalore.

Code availability

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Acknowledgements

The authors acknowledge the support from State Ground and Surface Water Resources Data Centre, Tharamani, Tamil Nadu, India, and USGS Earth Explorer for providing the necessary data for carrying out this research work.

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Authors and Affiliations

  1. Department of Civil Engineering, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, India

    Kamalanandhini Mohan & Annadurai Ramasamy

  2. Ontario, Canada

    James Varghese

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  1. Kamalanandhini Mohan
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  2. Annadurai Ramasamy
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  3. James Varghese
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Correspondence to Kamalanandhini Mohan.

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Responsible Editor: Venkatramanan Senapathi

This article is part of the Topical Collection on Recent advanced techniques in water resources management

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Mohan, K., Ramasamy, A. & Varghese, J. Drought severity assessment using automated land surface temperature retrieval technique. Arab J Geosci 14, 2358 (2021). https://doi.org/10.1007/s12517-021-08672-1

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