A data-driven approach to forest health assessment through multivariate analysis and machine learning techniques.

Journal: BMC plant biology
Published Date:

Abstract

BACKGROUND: Himalayan forests are fragile, rich in biodiversity, and face increasing threats from anthropogenic pressures and climate change. Assessing their health is critical for sustainable forest management. This study integrated ecological indicators (tree density, size, regeneration, deforestation, slope, grazing, and erosion) with machine learning (ML) to classify forest health and identify key drivers across 37 Western Himalayan sites. Principal component analysis (PCA) reduced data dimensionality, highlighting major ecological gradients. K-means clustering was used to group forests into three distinct classes based on ecological characteristics, due to its efficiency in identifying natural patterns within multivariate data. ML models, including Decision Tree (DT), Random Forest (RF), and Support Vector Machine (SVM) were trained and validated using an 80:20 train-test split and 5-fold cross-validation.

Authors

  • Raja Waqar Ahmed Khan
    Department of Botany, The University of Azad Jammu and Kashmir, Muzaffarabad, Pakistan.
  • Hamayun Shaheen
    Department of Botany, The University of Azad Jammu and Kashmir, Muzaffarabad, Pakistan.
  • Muhammad Ejaz Ul Islam Dar
    Department of Botany, The University of Azad Jammu and Kashmir, Muzaffarabad, Pakistan.
  • Tariq Habib
    Department of Botany, The University of Azad Jammu and Kashmir, Muzaffarabad, Pakistan.
  • Muhammad Manzoor
    Department of Plant Sciences, Quaid-i-Azam University, Islamabad, 45320, Pakistan.
  • Syed Waseem Gillani
    Department of Plant Sciences, Quaid-i-Azam University, Islamabad, 45320, Pakistan.
  • Abeer Al-Andal
    Department of Biology, College of Science, King Khalid University, Abha, 61413, Saudi Arabia.
  • John Oluwafemi Ayoola
    Department of Forest Resources Management, Ladoke Akintola University of Technology, Ogbomoso, P.M.B. 4000, Nigeria. joayoola68@lautech.edu.ng.
  • Muhammad Waheed
    Department of Botany, Faculty of Life Science, University of Okara, Okara, 56130, Pakistan.