Analysis of automated mapping techniques for changes in water bodies

Authors

  • O.О. Kavats
  • Y.V. Kavats
  • K.L. Sergieieva
  • D.М. Roi

DOI:

https://doi.org/10.34185/1562-9945-5-160-2025-17

Keywords:

water resources, water bodies, automated mapping, satellite monitoring, remote sensing methods, spectral indices, machine learning

Abstract

InInland water resources are vital components of the water system for every country, and their supply is strategic. Growing demand for water and climate change are exacerbating water management problems in arid and semi-arid regions, which experience water shortages due to low and irregular rainfall and high evapotranspiration. Monitoring inland waters is of strategic importance for a country's development. Assessing the ecological status, volume and area of water bodies is key to analysing and forecasting the water balance and spatial distri-bution among regions. Monitoring water bodies is particularly relevant in countries most af-fected by rapid climate change. As a result of climate change in Ukraine, there is a negative process of deterioration of natural moisture conditions, as a result of which areas of exces-sive moisture are disappearing in the Polissya zone, and the process of desertification has begun in the south. Ground-based measurements to assess changes in the area of water bod-ies are an expensive and resource-intensive approach, which is particularly difficult in re-mote areas. The article discusses the main methods of automated mapping of changes in wa-ter bodies using remote sensing data. The use of heterogeneous data in combination with a combination of methods based on spectral indices and machine learning demonstrates the best results. The article discusses automated mapping methods using remote monitoring and the applicability of these methods for analysing water resources in Ukraine. The main classi-cal methods are based on the use of spectral indices, machine learning and image threshold-ing. The use of heterogeneous data in combination with a combination of methods demon-strates the best results. It should be noted that such methods do not allow obtaining an accu-rate threshold value for relatively small water bodies. The method of mapping surface waters using radar images and the method of selecting the optimal threshold, the reference water mask, showed the best results.

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Published

2025-07-01