Quadrat analysis software for the detection of spatial or temporal clustering

Area of Science:

• Spatial analysis
• Geographic Information Systems (GIS)
• Statistical software

Background:

• The Boots and Getis quadrat analysis method is crucial for identifying spatial and temporal clustering.
• Manual analysis of spatial data can be time-consuming and prone to error.

Purpose of the Study:

• To present a software program that automates the quadrat analysis procedure.
• To provide a tool for detecting spatial or temporal clustering efficiently.

Main Methods:

• The software compares observed values in sampling units to values expected under random distribution.
• It employs a chi-square test for non-random dispersion assessment.
• A t-test is utilized to evaluate non-regular dispersion patterns.

Main Results:

• The developed software successfully automates the quadrat analysis process.
• It provides statistical significance for spatial or temporal clustering detection.

Conclusions:

• Automated quadrat analysis software enhances the efficiency of spatial and temporal clustering detection.
• The tool supports data analysis using dBase-compatible files and requires DOS 3.3 or higher.