Environmental Impact Assessment of Nuclear Power Plant Accident using Spatial Information Modeling: A Case Study of Chernobyl

Abstract

: This paper demonstrates the effectiveness of advanced spatial modeling techniques for environmental monitoring and impact assessment through a case study of Chernobyl nuclear accident occurred in 1986. Land-cover types changed after the accident are analysed by a post classification comparison method using bi-temporal Landsat TM data acquired in 1986 and 1992 near the accident site. Spatial modeling including various kriging algorithms are also applied to analyze the relationships between Cesium concentrations in soil and thyroid cancer incidence rates in Belarus, which was greatly damaged by the accident. The change detection results clearly showed the decrease of croplands and the increase of abandoned lands, and concrete structures were newly built around the nuclear plant to prevent the spread of radioactive contamination. In Belarus, high Cesium concentrations were observed in southern areas with high thyroid cancer risk estimated by Poisson kriging. Geographically weighted regression, which could account for geographic variations of independent variables including Cesium concentrations and distances from the Chernobyl nuclear power plant, was applied to extract the relationships between the independent variables and the thyroid cancer risk. The estimated risk values showed a correlation coefficient value of 0.98 with respect to the thyroid cancer risk values, which implied that the thyroid cancer risk in Belarus was affected by the accident. In conclusion, it is expected that advanced spatial modeling techniques applied in this study would be useful for environmental impact assessment and public health research.

Research Trend Analysis of Geospatial Information in South Korea Using Text-Mining Technology

“…However, this phenomenon has been decreasing over time. In the time series frequency analysis, LANDSAT showed a sharp decline during periods 3-4, and KOMPSAT, MODIS, and GEOKOMPSAT showed a sustained increase over periods [1][2][3][4] (Figure 8(b)). To expand interdisciplinary research, it seems reasonable to try to center on the Satellite Image domain, which has a high betweenness centrality value.…”

“…GI is information that expresses geographical location and attributes in a form that computers can recognize [2][3][4]. GI can apply to all information on the Earth's surface, underground, and in the ocean and atmosphere [5,6].…”