Fuzzy Tessellation Approach for Environmental Site Characterization

Abstract

Environmental site investigations are carried out prior to the reclamation of industrially contaminated sites. It is required to take samples and analyze the laboratory reports to find out the distribution of contaminants over the site. In this study, an algorithm based on fuzzy assessment and overlapped partitioning is proposed to identify the topology of polluted areas in a given industrial site. The primary objective is to locate contaminated zones accurately with sparse data in a preliminary investigation and the second is to reduce the size of the area that is resubjected to expensive sampling methods (such as deep drilling) in the detailed phase of the investigation. If these objectives are achieved, a considerable cost reduction occurs in the process of site characterization.