Comparative analysis of ecological sensitivity assessment using the coefficient of variation method and machine...

Area of Science:

• Environmental Science
• Ecology
• Geospatial Analysis

Background:

• Ecological sensitivity assessment is crucial for environmental protection and resource management.
• Understanding spatial variations in ecological sensitivity informs targeted conservation strategies.

Purpose of the Study:

• To assess and map the ecological sensitivity of Xifeng County.
• To explore the spatial distribution patterns and differences in ecological sensitivity.
• To evaluate the effectiveness of machine learning in ecological sensitivity assessment.

Main Methods:

• Selected 12 assessment factors across ecological, geological, and human environments.
• Employed the coefficient of variation method and machine learning algorithms.
• Analyzed spatial distribution patterns and regional differences in ecological sensitivity.

Main Results:

• Ecological sensitivity in Xifeng County is generally low in the north and high in the south.
• 41.90% of the area exhibits very high and high sensitivity, concentrated in mountainous and hilly regions.
• 35.51% of the area shows very low and low sensitivity, primarily in plains and low mountainous areas.

Conclusions:

• The assessment results align with the actual environmental conditions in Xifeng County.
• The study contributes to the refinement of ecological sensitivity assessment methodologies and models.
• Findings provide a scientific basis for regional ecological environment protection and sustainable resource utilization.