SPATIAL CLUSTERING OF ENVIRONMENTAL POLLUTION RISK AREAS USING KERNEL DENSITY ANALYSIS IN THE VALLEYS OF TRABZON, TURKEY


MEMİŞOĞLU T., ÇOLAK H. E.

FRESENIUS ENVIRONMENTAL BULLETIN, vol.27, no.6, pp.4357-4366, 2018 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 27 Issue: 6
  • Publication Date: 2018
  • Journal Name: FRESENIUS ENVIRONMENTAL BULLETIN
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI)
  • Page Numbers: pp.4357-4366
  • Keywords: Environmental Pollution, Spatial Clustering, Kernel Density, GIS, AHP, Trabzon, GIS, AHP, GROUNDWATER, POLLUTANTS, PROVINCE, CHINA, BASIN
  • Karadeniz Technical University Affiliated: Yes

Abstract

After the industrial revolution, environmental pollution is one of the major problem in the world. Pollution size further increase with each passing day along with industrialization, rapid population growth, and urbanization activities. In this study, the aim is to identify environmental pollution risk areas using Geographic Information Systems (GIS), determinate of the accuracy of the clustering test and to compare pollution size with respect to these areas in the three mainstream valleys located in Trabzon. In this context, a geodatabase design was assessed the environmental pollutants in these valleys and spatial data were brought together in this system. Pollutant factors in these stream valleys primarily were determined by questionnaire assessment, and then evaluated with pairwise comparison matrix using normalized values. These factor weights used as input values for Analytical Hierarchy Method (AHP). With factor weights, kernel density analysis was applied; finally, the risk of pollution intense regions was identified; and results were indicated on the maps. In this study, result maps show important points in the stream valley to be protected and show which points need to be taken under environmental pollution protection. The resulting maps also represent significant contributions to the establishment of environmental information systems for the Watershed Protection Action Plan and with the generated prediction maps, it can be determined in which areas the pollution very intense and this contribute significantly where preventions will be taken in the stream valleys.