Welcome to the Soil Quality Index Calculator

This application implements a comprehensive workflow for calculating and mapping soil quality indices using Principal Component Analysis (PCA) and geostatistical methods.

Workflow Steps:

1. Input Data: Upload your soil data (CSV/XLS) with X, Y coordinates and soil properties
2. Exploratory Analysis: Examine correlations and remove highly correlated variables (>0.98)
3. PCA Analysis: Perform Principal Component Analysis to determine variable weights
4. SQI Calculation: Define normalization parameters and calculate the Soil Quality Index
5. Spatial Assessment: Apply geostatistical interpolation (Kriging or IDW)
6. Results: Visualize spatial distribution and download maps

Data Requirements:

• CSV or Excel file with soil property data
• Mandatory columns: X, Y (coordinates)
• Soil properties: Any numerical variables (pH, organic matter, texture, nutrients, physical properties, etc.)
• The application will automatically detect all numerical variables for analysis
• Study area boundary (optional): GeoJSON or GeoPackage format

Normalization Types:

• More is Better: Higher values indicate better soil quality (e.g., organic matter, nutrients)
• Less is Better: Lower values indicate better soil quality (e.g., bulk density)
• Optimal Range: Values within a specific range are considered optimal (e.g., pH, texture)

Recommended Optimal Ranges:

• pH: 6.5 - 7.5 (optimal for most crops)
• Clay: 10% - 25% (balanced texture)
• Silt: 30% - 50% (good water retention)
• Sand: 40% - 60% (adequate drainage)
• EC: 2.0 - 15.0 dS/m (moderate salinity range)

Select Variables for Analysis:

Remove Highly Correlated Variables

Run PCA Analysis

PCA Parameters:

Configure normalization for each variable:

Select the normalization type and define optimal ranges where applicable.

Run Interpolation