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Land Use and Land Cover Change Monitoring and Prediction of a UNESCO World Heritage Site: Kaziranga Eco-Sensitive Zone Using Cellular Automata-Markov Model

Author

Listed:
  • Nityaranjan Nath

    (Department of Geography, Gauhati University, Guwahati 781014, India)

  • Dhrubajyoti Sahariah

    (Department of Geography, Gauhati University, Guwahati 781014, India)

  • Gowhar Meraj

    (Centre for Climate Change & Water Research (C3WR), Suresh Gyan Vihar University, Jaipur 302017, India)

  • Jatan Debnath

    (Department of Geography, Gauhati University, Guwahati 781014, India)

  • Pankaj Kumar

    (Institute for Global Environmental Strategies, Hayama 240-0115, Japan)

  • Durlov Lahon

    (Department of Geography, Gauhati University, Guwahati 781014, India)

  • Kesar Chand

    (G.B Pant National Institute of Himalayan Environment, Himachal Regional Centre, Kullu 175126, India)

  • Majid Farooq

    (Centre for Climate Change & Water Research (C3WR), Suresh Gyan Vihar University, Jaipur 302017, India)

  • Pankaj Chandan

    (National Development Foundation, N.D.F., Shakuntla Bhawan, Jammu 180018, India)

  • Suraj Kumar Singh

    (Centre for Climate Change & Water Research (C3WR), Suresh Gyan Vihar University, Jaipur 302017, India)

  • Shruti Kanga

    (Department of Geography, School of Environment and Earth Sciences, Central University of Punjab, VPO-Ghudda, Bathinda 151401, India)

Abstract

The Kaziranga Eco-Sensitive Zone is located on the edge of the Eastern Himalayan biodiversity hotspot region. In 1985, the Kaziranga National Park (KNP) was declared a World Heritage Site by UNESCO. Nowadays, anthropogenic interference has created a significant negative impact on this national park. As a result, the area under natural habitat is gradually decreasing. The current study attempted to analyze the land use land cover (LULC) change in the Kaziranga Eco-Sensitive Zone using remote sensing data with CA-Markov models. Satellite remote sensing and the geographic information system (GIS) are widely used for monitoring, mapping, and change detection of LULC change dynamics. The changing rate was assessed using thirty years (1990–2020) of Landsat data. The study analyses the significant change in LULC, with the decrease in the waterbody, grassland and agricultural land, and the increase of sand or dry river beds, forest, and built-up areas. Between 1990 and 2020, waterbody, grassland, and agricultural land decreased by 18.4, 9.96, and 64.88%, respectively, while sand or dry river beds, forest, and built-up areas increased by 103.72, 6.96, and 89.03%, respectively. The result shows that the area covered with waterbodies, grassland, and agricultural land is mostly converted into built-up areas and sand or dry river bed areas. According to this study, by 2050, waterbodies, sand or dry river beds, and forests will decrease by 3.67, 3.91, and 7.11%, respectively; while grassland and agriculture will increase by up to 16.67% and 0.37%, respectively. The built-up areas are expected to slightly decrease during this period (up to 2.4%). The outcome of this study is expected to be useful for the long-term management of the Kaziranga Eco-Sensitive Zone.

Suggested Citation

  • Nityaranjan Nath & Dhrubajyoti Sahariah & Gowhar Meraj & Jatan Debnath & Pankaj Kumar & Durlov Lahon & Kesar Chand & Majid Farooq & Pankaj Chandan & Suraj Kumar Singh & Shruti Kanga, 2023. "Land Use and Land Cover Change Monitoring and Prediction of a UNESCO World Heritage Site: Kaziranga Eco-Sensitive Zone Using Cellular Automata-Markov Model," Land, MDPI, vol. 12(1), pages 1-21, January.
  • Handle: RePEc:gam:jlands:v:12:y:2023:i:1:p:151-:d:1022773
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    References listed on IDEAS

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    Cited by:

    1. Rajeev Singh Chandel & Shruti Kanga & Suraj Kumar Singh & Bojan Ðurin & Olga Bjelotomić Oršulić & Dragana Dogančić & Julian David Hunt, 2023. "Assessing Sustainable Ecotourism Opportunities in Western Rajasthan, India, through Advanced Geospatial Technologies," Sustainability, MDPI, vol. 15(14), pages 1-18, July.
    2. Aboubakar Gasirabo & Chen Xi & Baligira R. Hamad & Umwali Dufatanye Edovia, 2023. "A CA–Markov-Based Simulation and Prediction of LULC Changes over the Nyabarongo River Basin, Rwanda," Land, MDPI, vol. 12(9), pages 1-20, September.
    3. Jatan Debnath & Dhrubajyoti Sahariah & Anup Saikia & Gowhar Meraj & Nityaranjan Nath & Durlov Lahon & Wajahat Annayat & Pankaj Kumar & Kesar Chand & Suraj Kumar Singh & Shruti Kanga, 2023. "Shifting Sands: Assessing Bankline Shift Using an Automated Approach in the Jia Bharali River, India," Land, MDPI, vol. 12(3), pages 1-26, March.

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