We investigated habitat preference of Common Sandpipers as part of a monitoring program in the Őrség National Park, Hungary. Field observations were conducted during the summers between 2008 and 2012 along a 47-km long section of the River Rába. During the observations we recorded the number and location of birds on the river bank. We divided the studied area into 1 km long sections and measured the proportion of the visually distinguishable habitat types (water, low gravel and sand bank, vegetation and degraded area) from a digitalized map. Furthermore, we recorded the number of the low banks and the number of bends of the river within each section, as well as the sections’ distance from the closest hydroelectric power plants and human settlements. In 2012 we also performed a detailed habitat mapping, recording the proportion of the vegetation types along the river bank and the number of fishing spots, embankment strengthenings and gravel banks. We tested the correlations between these habitat variables and number of birds present in the river sections. Our results show that Common Sandpipers were observed more frequently in locations which have (1) larger number and area of low gravel and sand banks, (2) less dense vegetation, and (3) lower proportion of degraded habitats. These findings can be taken into account in the conservation management of River Rába

Geospatial tools and geocoding systems play an increasingly significant role in the modernization and operation of municipal water utility networks. This research explored how geocoding systems could improve network management, facilitate leak detection, and enhance hydraulic modeling accuracy. Various geocoding services, including Google, Bing Maps, and OpenStreetMap APIs were analyzed using address data from a small Central European municipality. The analysis was performed in February and March of 2024. The accuracy and efficiency of these systems in handling spatial data for domestic water networks were assessed and results showed that geocoding accuracy depended on the quality of the service provider databases and the formatting of input data. Google proved the most reliable, while Bing and OpenStreetMap were less accurate. Additionally, the Location Database developed by Lechner Knowledge Center was used as a reliable local reference for comparison with global services. Geocoding results were integrated into GIS softwares (Google Earth ver. 7.3.6.9796, QGIS ver. 3.36, ArcGIS ver 10.8.2) to enable spatial analysis and comparison of geographic coordinates. The findings highlight geocoding’s critical role in efficient water network management, particularly for mapping consumer data and rapidly localizing leaks and breaks. Our findings directly support hydraulic modeling tasks, contributing to sustainable operations and cost-effective interventions.