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Elephant habitat modeling in Sai Yok National Park using high-resolution Pléiades data.

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Title: Elephant habitat modeling in Sai Yok National Park using high-resolution Pléiades data.
Authors: Mukhopadhyay, Anirban1 (AUTHOR) anirban@ukw.edu.pl, Pal, Indrajit2 (AUTHOR), Hati, Jyoti Prakash1 (AUTHOR), Pramanick, Niloy3 (AUTHOR), Acharyya, Rituparna1 (AUTHOR), Bharadwazdata, Ganni S. V. S. Aditya2 (AUTHOR), Pramanick, Malay2 (AUTHOR)
Source: Landscape & Ecological Engineering. Apr2025, Vol. 21 Issue 2, p443-459. 17p.
Subject Terms: *Life sciences, *Park use, *Random forest algorithms, *Land use, *Tourism
Abstract: This research aimed to evaluate elephant habitat conditions in the Sai Yok National Park, Thailand, using high-resolution Pléiades imagery and InVEST Model's Habitat Quality Assessment (HQA) model. Land use was also analyzed as an input in the model using feature selection via the Grey-Level Co-occurrence Matrix (GLCM) and classification using the Random Forest (RF) algorithm. The risk and vulnerability of the elephant habitat were analyzed using several corresponding indices to understand the spatial distribution of anthropogenic activities and point out the areas for immediate conservation needs. The research results show a rapid change in land use between 2013 and 2022, with forest cover significantly decreasing and cultivated land increasing. Habitat degradation index data indicates that changes in land use have resulted in a significant decline in habitat quality due to palpable human pressure. This study also highlighted the eastern boundary of the study region as a possible risk zone for elephant habitat, where the tourism sector is expanding. Despite the potential to improve local livelihoods, these economic activities would eventually negatively influence elephant habitats. The integration of decision support technology with the results provided by this study can help stakeholders and policymakers create sustainable land-use plans that are ecologically diligent. [ABSTRACT FROM AUTHOR]
Database: Energy & Power Source
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DbLabel: Energy & Power Source
An: 184231761
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  Label: Title
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  Data: Elephant habitat modeling in Sai Yok National Park using high-resolution Pléiades data.
– Name: Author
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  Data: <searchLink fieldCode="AR" term="%22Mukhopadhyay%2C+Anirban%22">Mukhopadhyay, Anirban</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> anirban@ukw.edu.pl</i><br /><searchLink fieldCode="AR" term="%22Pal%2C+Indrajit%22">Pal, Indrajit</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hati%2C+Jyoti+Prakash%22">Hati, Jyoti Prakash</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pramanick%2C+Niloy%22">Pramanick, Niloy</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Acharyya%2C+Rituparna%22">Acharyya, Rituparna</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Bharadwazdata%2C+Ganni+S%2E+V%2E+S%2E+Aditya%22">Bharadwazdata, Ganni S. V. S. Aditya</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Pramanick%2C+Malay%22">Pramanick, Malay</searchLink><relatesTo>2</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Landscape+%26+Ecological+Engineering%22">Landscape & Ecological Engineering</searchLink>. Apr2025, Vol. 21 Issue 2, p443-459. 17p.
– Name: Subject
  Label: Subject Terms
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  Data: *<searchLink fieldCode="DE" term="%22Life+sciences%22">Life sciences</searchLink><br />*<searchLink fieldCode="DE" term="%22Park+use%22">Park use</searchLink><br />*<searchLink fieldCode="DE" term="%22Random+forest+algorithms%22">Random forest algorithms</searchLink><br />*<searchLink fieldCode="DE" term="%22Land+use%22">Land use</searchLink><br />*<searchLink fieldCode="DE" term="%22Tourism%22">Tourism</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: This research aimed to evaluate elephant habitat conditions in the Sai Yok National Park, Thailand, using high-resolution Pléiades imagery and InVEST Model's Habitat Quality Assessment (HQA) model. Land use was also analyzed as an input in the model using feature selection via the Grey-Level Co-occurrence Matrix (GLCM) and classification using the Random Forest (RF) algorithm. The risk and vulnerability of the elephant habitat were analyzed using several corresponding indices to understand the spatial distribution of anthropogenic activities and point out the areas for immediate conservation needs. The research results show a rapid change in land use between 2013 and 2022, with forest cover significantly decreasing and cultivated land increasing. Habitat degradation index data indicates that changes in land use have resulted in a significant decline in habitat quality due to palpable human pressure. This study also highlighted the eastern boundary of the study region as a possible risk zone for elephant habitat, where the tourism sector is expanding. Despite the potential to improve local livelihoods, these economic activities would eventually negatively influence elephant habitats. The integration of decision support technology with the results provided by this study can help stakeholders and policymakers create sustainable land-use plans that are ecologically diligent. [ABSTRACT FROM AUTHOR]
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      – Type: doi
        Value: 10.1007/s11355-025-00648-7
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      – Code: eng
        Text: English
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        Type: general
      – SubjectFull: Park use
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      – SubjectFull: Random forest algorithms
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      – SubjectFull: Land use
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      – SubjectFull: Tourism
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            NameFull: Mukhopadhyay, Anirban
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            – D: 01
              M: 04
              Text: Apr2025
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              Y: 2025
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