Journal of Biometrics & Biostatistics

Department of Mechanical and Electronic Engineering, Northwest A&F University, Yangling 712100, China

Publications

• Mini Review   
  Integrating Machine Learning for Enhanced Fractional Vegetation Coverage Analysis
  Author(s): Garofalo Costan*
  
  Fractional Vegetation Coverage (FVC) is a critical parameter in ecological and environmental studies. It represents the proportion of ground covered by green vegetation, providing essential information for understanding ecosystem dynamics, monitoring environmental changes, and managing natural resources. Traditionally, FVC estimation relied on field surveys and remote sensing techniques. However, the advent of Machine Learning (ML) has revolutionized this field, offering enhanced accuracy and efficiency in FVC analysis. This essay delves into the integration of machine learning for enhanced fractional vegetation coverage analysis, exploring its methodologies, applications, benefits, and challenges. Before the integration of machine learning, FVC estimation primarily relied on field-based methods and remote sensing techniques. Field-based methods involve direct .. Read More»
  DOI: 10.37421/2155-6180.2024.15.224

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