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In recent decades geospatial technologies (GST) have been affected by a process of rapid development. One of their applications involves the documentation of the protected areas reference state and the development of high-quality models for their preservation and management. The research area of this paper is Lake Zmajevo oko (Lake Dragon eye), near Rogoznica (Croatia). The research goals were to create a multisensor model of the lake and present the application of these technologies for promotional purposes. The secondary objective was to obtain morphometric data about the lake. The research methodology included performing the process of UAV photogrammetry and bathymetry. In UAV photogrammetry, a Phantom 4 Pro was used. In the bathymetric survey, an integrated system composed of WASSP S3 multibeam depth sounder (MBES) and the Hemisphere V320 GNSS smart antenna was used. The data collected by both methods were combined and an multisensor high-quality model of the lake was created. Te n underwater tunnels on the steep sides of the lake were detected. From the derived models, the volume and surface area of the lake, as well as the length of the lake shoreline were calculated. Furthermore, a virtual walk around the lake was made to promote this area. A physical model of the lake, which can serve as a souvenir, was printed with the 3D printer Prusa i3 MK3. The collected high-quality data can serve as the basis for future research, while derived models and a virtual walk can be used for its promotion.

Advances in geospatial technologies (GST) have revolutionized the ability to quantify spatio- temporal changes in various geomorphological forms at different scales. One of the most complex geomorphological forms are tufa and travertine cascades whose evolution is the subject of numerous research in various scientific fields. In this paper, we are presenting a new methodological framework for analyzing tufa formation dynamic (TFD) at three levels of research (macro-meso- micro) using the close-range photogrammetry (CRP) method, handheld 3D scanner, and terrestrial laser scanner (TLS). The results, 3D models and digital elevation models (DEMs), of the first (reference) measurement at three levels of research, are presented in this paper. Reference models were generated using Agisoft Metashape, Artec Studio Professional 15, and SCENE software. Measurements were done in an artificial tufa tunnel, located within the Jaruga, the second oldest hydroelectric power plant in the world construct ed within National Park Krka, Croatia. This tunnel is a specific tufa-forming environment. The subject of the next paper will be the comparison of interval tufa 3D tufa models at three levels of research and the calculation of volumetric (mm3 a-1) and linear (mm a−1) tufa growth rates after two years of exposure to the Krka River. The presented methodological framework will expand the knowledge about TFD within this specific depositional sub- environment and can be applied in the dynamic formation analysis of other hydroprecipitates.

In most urban environments, loss of natural vegetation, the reduction of open spaces, and the rapid invasive transformation of the natural environment into impervious has happened. These changes can lead to a decline in life quality and in an increase of various economic, social, ecological, and infrastructural problems and risks. The complexity of the urban environment at various scales requires the application of high spatial and temporal resolution data in the process of urban planning. In this paper, specific urban planning indicators (UPIs), divided into two groups, have been derived for statistical circles (SC) of Split settlement in Croatia. Vegetation indicators (TCR - tree cover ratio, LCR - lawn cover ratio, GCR - green cover ratio) and indicators of urbanization (SCR - street cover ratio, BCR - building cover ratio, IMR - impervious surface ratio) were derived from the derived land cover model. It was generated from WorldView-3 (WV3) imagery with the GEOBIA method. A superv ised machine learning technique support vector machine (SVM) was used. A significant spatial variability between UPIs at SCs was observed. The UPIs values at the studied level are the reflection of the historical spatial- functional development of the Split settlement. These type of UPIs can be used at the neighborhood level of urban planning and analysis of different issues in an urban environment.