Geoinformation Monitoring of Eutrophication and Turbidity of Surface Water Bodies in Urban Areas (Case study in Kyiv)
Abstract
The aim of this study is to develop an algorithm for geoinformation monitoring of the condition of surface water bodies in urban areas, using Kyiv as a case study, and to identify patterns in their spatial distribution and the dynamics of eutrophication levels and turbidity based on high-resolution satellite data. The study was conducted using the Normalized Difference Chlorophyll Index (NDCI) and the Normalized Difference Turbidity Index (NDTI). The study employed cartographic analysis, digital processing of geospatial data, remote sensing, as well as cluster and multivariate analysis to produce electronic maps within the QGIS environment (Version 3.44.7). Based on the degree of water saturation within Kyiv, three zones were identified: insufficient, moderate, and sufficient water saturation. Eutrophication was assessed using NDCI values derived from satellite imagery. High positive NDCI values (up to 0.8) were detected in shallow bays of the Dnipro River, oxbow lakes, channels, selected slow-flowing lakes, and ponds, indicating degradation processes in these water bodies. Using summer satellite imagery from 2020–2024, the NDTI was calculated for Kyiv’s reservoirs. The index was computed in QGIS using the Raster Calculator tool. The NDTI enables not only the assessment of water turbidity but also the analysis of its spatial distribution across water bodies, which is important for identifying potential sources of suspended solids. The obtained NDTI values ranged from −0.767 to 0.46 and were conditionally classified into three groups: −0.767 to 0 (relatively clear water, low turbidity), 0.001 to 0.3 (moderate turbidity), and 0.301 to 0.46 (high turbidity). The scientific novelty of the study lies in the development of a geoinformation-based monitoring algorithm for urban surface water bodies using high-resolution satellite data, enabling an integrated assessment of their environmental condition based on NDCI and NDTI indicators.