Pidgorodetska L. Rationale for Complex Estimation of Water Bodies Ecological State on the Basis of Remote Sensing Data and Ground-based Observations Taking Lake Svityaz as an Example

The goal of this research is the complex estimation of water bodies ecological state using ground-based and remote sensing data. It is made on the example of the Lake Svityaz. To achieve this goal the following methods were applied: system analysis, cluster analysis, multi-criteria evaluation (hierarchy analysis method) and fractal analysis, adapt balance compliance method and computer modelling. The computer processing of multispectral images of the Lake Svityaz using NDVI, temperature maps, depth map as informative features was performed. It allowed to identify seven types of lake's microlandscapes for each year of observation. The relative areas of the Svityaz microlandscapes were determined. The microlandscape structure of the water body using fractal analysis method was described. Thereby, the water macrophytes distribution in every year of observation is characterized by the multifractal dimensions Dq. The Lake Svityaz as the object of study was considered as an ecosystem in which physical, chemical and biological processes are most tightly interdependent. The hierarchy analysis method was used for creation of a hierarchy model of the ecological state estimation. The model and the expert ecological state's assessments of the Lake Svityaz are based on the ground measurements during 1988-2009. The correlation between the expert ecological state's assessments and multifractal dimensions D(q<0) is in the range 0.715-0.784. It proves the possibility of express-diagnostics conducting of the lake's ecological state estimation using the microlandscape's relative areas changes which can be evaluated by the satellite data processing. It was discovered that the adapt balance compliance method enabled to conduct modelling and forecasting the Lake Svityaz ecological state dynamics during the recreational load change. KEY WORDS: Remote Sensing, Water Ecosystem, Microladscape, Ecological State Estimation, Satellite Data.