Soil Contamination Mapping with Hyperspectral Imagery: Pre- Dnieper Chemical Plant (Ukraine) Case Study

Abstract

Radioactive contamination of soils is an issue of severe importance for Ukraine remaining with a significant post-Soviet baggage of not settled problems regarding radioactive waste. Regular radioecological observations and up-to-date contamination mapping based on advanced geoinformation techniques give an ability to prepare for, respond to, and manage potential adverse effects from pollution with radionuclides and heavy metals. Hyperspectral satellite imagery provides potentially powerful tool for soil contamination detection and mapping. An intention to find a relation between remotely sensed hyperspectral and ground-based measured soil contamination fractions in area of the uranium mill tailings deposits near Kamianske city was made. An advanced algorithm based on known TCMI (target-constrained minimal interference)-matched filter with a nonnegative constraint was applied to determine the soil contamination fractions by hyperspectral imagery. The time series maps of spatial distribution of the soil contamination fractions within study area around the Sukhachevske tailings dump are presented. Time series analysis of the map resulted in two independent parameters: the average value for the entire observation period and the daily mean increment of the soil contamination fractions.