Analyses of riverbed shape evolution are crucial for environmental protection and local water management. For narrow rivers located in forested, mountain areas, it is difficult to use remote sensing data used for large river regions. We performed a study of the Prądnik River, located in the Ojców National Park (ONP), Poland. A multitemporal analysis of various data sets was performed. Light detection and ranging (LiDAR)-based data and orthophotomaps were compared with classical survey methods, and 78 cross-sectional profiles were done via GNSS and tachymetry. In order to add an extra time step, the old maps of this region were gathered, and their content was compared with contemporary data. The analysis of remote sensing data suggests that they do not provide sufficient information on the state and changes of riverbanks, river course or river depth. LiDAR data sets do not show river bottoms, and, due to plant life, do not document riverbanks. The orthophotomaps, due to tree coverage and shades, cannot be used for tracking the whole river course. The quality of old maps allows only for general shape analysis over time. This paper shows that traditional survey methods provide sufficient accuracy for such analysis, and the resulted cross-sectional profiles can and should be used to validate other, remote sensing, data sets. We diagnosed problems with the inventory and monitoring of such objects and proposed methods to refine the data acquisition.

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The article examines the quality of reprocessed GNSS data for determination of seasonal effect in a coordinates' time series. The authors are looking for long-term changes of NEU components on the basis of weekly EPN solutions from the years 1996-2016. This is one of the first such in-depth studies using such a long time period and a large number of stations. Amplitude and its RMS values of fitting function are analysed. The analysis shows that there are significant repeatable coordinate variations: 4.7 mm, 2.9 mm and 8.3 mm for the dN, dE and dU components, respectively. The research also shows a group of coordinates' time series with very small RMS values below the coordinates' accuracy (1 mm for horizontal, 3 mm for vertical components), leading to a very good function fitting with relatively small amplitude magnitudes. The authors did not remark any connection with the above described phenomena and geographical location or type of setting up of a base station.

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The commonly used methods in digital cartography are based on the minimum dimensions of black and white objects. This article presents a solution in which both the colour of the symbols and the background on which they are presented are relevant in the context of setting the minimum dimensions of the objects on a map. To achieve this, the authors have developed a perception coefficient that is an extension of the formal definitions of minimum object dimensions. In support of the presented solutions, the authors offer several cartographic examples. The article also contains experimental research that examines the impact of colour on the recognition of objects by means of specially prepared surveys. These results are compared against the theoretical values of the perception coefficient. The research objective was achieved by developing new solutions that could be used in the cartographic production processes of any national map agency.