[Multi-scale correlation analysis of soil organic carbon with its influence factors using wavelet transform]

Area of Science:

• Environmental Science
• Soil Science
• Geographic Information Systems (GIS)

Background:

• Soil organic carbon (SOC) is crucial for soil health and ecosystem function.
• Understanding the spatial variability of SOC density and its drivers is essential for effective land management.
• Previous studies have explored SOC influencing factors, but multi-scale analysis remains critical.

Purpose of the Study:

• To quantitatively analyze the multi-scale correlation between SOC density and its influencing factors (NDVI, elevation, slope, aspect) in Guangdong Province.
• To reveal the scale-dependent nature of these relationships.
• To identify the primary drivers of SOC density variation across different spatial scales.

Main Methods:

• Geographic Information Systems (GIS) for spatial data handling.
• One-dimensional Discrete Wavelet Transform (DWT) for multi-scale decomposition.
• Analysis of SOC density and influencing factors along four transects in a mountainous region.

Main Results:

• Correlation between SOC density and influencing factors demonstrated significant scale-dependence.
• Normalized Difference Vegetation Index (NDVI) showed the strongest influence at 2, 8, and 16 km scales.
• Elevation was most influential at 8 and 16 km scales; slope had a weak influence; aspect's negative effect increased with scale (>2 km).

Conclusions:

• NDVI and elevation are the dominant factors controlling SOC density across multiple scales in the study area.
• Slope and aspect exert weaker influences, primarily significant at larger scales for specific transects.
• The findings highlight the importance of scale in understanding SOC dynamics and informing targeted soil management strategies.