The significant geomorphological hazard of collapsed cavities (CC) causes notable environmental transformations. To address this issue, the pipe collapse pattern was examined using two statistical methods, the Density Correlation Function (DCF) and the Mark Coloration Function (MCF). Key predictor variables like organic carbon (OC), sodium adsorption ratio (SAR), and exchangeable sodium percentage (ESP) were utilized to comprehend their impact on spatial distribution over time. The study was found that lower OC levels increase susceptibility to CC, while higher SAR and ESP amounts enhance the potential for collapsed cavities. The methodology and discoveries of this research can offer valuable insights for land managers, stakeholders, and researchers.