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Interdecadal Variations in Agricultural Drought Monitoring Using Land Surface Temperature and Vegetation Indices: A Case of the Amahlathi Local Municipality in South Africa

Author

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  • Phumelelani Mbuqwa

    (Department of Geography and Environmental Science, University of Fort Hare, Private Bag X1314, Alice 5700, Eastern Cape Province, South Africa
    Geospatial Application, Climate Change and Environmental Sustainability Lab–GACCES, University of Fort Hare, Alice 5700, Eastern Cape Province, South Africa)

  • Hezekiel Bheki Magagula

    (Department of Geography and Environmental Science, University of Fort Hare, Private Bag X1314, Alice 5700, Eastern Cape Province, South Africa)

  • Ahmed Mukalazi Kalumba

    (Department of Geography and Environmental Science, University of Fort Hare, Private Bag X1314, Alice 5700, Eastern Cape Province, South Africa
    Geospatial Application, Climate Change and Environmental Sustainability Lab–GACCES, University of Fort Hare, Alice 5700, Eastern Cape Province, South Africa)

  • Gbenga Abayomi Afuye

    (Department of Geography and Environmental Science, University of Fort Hare, Private Bag X1314, Alice 5700, Eastern Cape Province, South Africa
    Geospatial Application, Climate Change and Environmental Sustainability Lab–GACCES, University of Fort Hare, Alice 5700, Eastern Cape Province, South Africa)

Abstract

Agricultural droughts in South Africa, particularly in the Amahlathi Local Municipality (ALM), significantly impact socioeconomic activities, sustainable livelihoods, and ecosystem services, necessitating urgent attention to improved resilience and food security. The study assessed the interdecadal drought severity and duration in Amahlathi’s agricultural potential zone from 1989 to 2019 using various vegetation indicators. Landsat time series data were used to analyse the land surface temperature (LST), soil-adjusted vegetation index (SAVI), normalized difference vegetation index (NDVI), and standardized precipitation index (SPI). The study utilised GIS-based weighted overlay, multiple linear regression models, and Pearson’s correlation analysis to assess the correlations between LST, NDVI, SAVI, and SPI in response to the agricultural drought extent. The results reveal a consistent negative correlation between LST and NDVI in the ALM, with an increase in vegetation (R 2 = 0.9889) and surface temperature. LST accuracy in dry areas increased to 55.8% in 2019, despite dense vegetation and a high average temperature of 40.12 °C, impacting water availability, agricultural land, and local ecosystems. The regression analysis shows a consistent negative correlation between LST and NDVI in the ALM from 1989 to 2019, with the correlation between vegetation and surface temperature increasing since 2019. The SAVI indicates a slight improvement in overall average vegetation health from 0.18 in 1989 to 0.25 in 2009, but a slight decrease to 0.21 in 2019. The SPI at 12 and 24 months indicates that drought severely impacted vegetation cover from 2014 to 2019, with notable recovery during improved wet periods in 1993, 2000, 2003, 2006, 2008, and 2013, possibly due to temporary drought relief. The findings can guide provincial drought monitoring and early warning programs, enhancing drought resilience, productivity, and sustainable livelihoods, especially in farming communities.

Suggested Citation

  • Phumelelani Mbuqwa & Hezekiel Bheki Magagula & Ahmed Mukalazi Kalumba & Gbenga Abayomi Afuye, 2024. "Interdecadal Variations in Agricultural Drought Monitoring Using Land Surface Temperature and Vegetation Indices: A Case of the Amahlathi Local Municipality in South Africa," Sustainability, MDPI, vol. 16(18), pages 1-21, September.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:18:p:8125-:d:1480293
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    References listed on IDEAS

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    1. Yousfi, Salima & Marín, José & Parra, Lorena & Lloret, Jaime & Mauri, Pedro V., 2022. "Remote sensing devices as key methods in the advanced turfgrass phenotyping under different water regimes," Agricultural Water Management, Elsevier, vol. 266(C).
    2. Charles Samuel Mutengwa & Pearson Mnkeni & Aleck Kondwakwenda, 2023. "Climate-Smart Agriculture and Food Security in Southern Africa: A Review of the Vulnerability of Smallholder Agriculture and Food Security to Climate Change," Sustainability, MDPI, vol. 15(4), pages 1-13, February.
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