![]() Based on the dataset from the 2nd (1819 – 1827) and 3rd military survey maps (1869 – 1887), aerial photos (19) and orthophoto mosaics (2002, 20) the in-channel mor-phological, as well as the land cover changes, were identified. The aim of this paper was to evaluate the morphological response to human intervention and flood events on three types of river segments (natural, regulated and water-gap) of the 72-km-long river reach of the mean-dering Hornád River in Slovakia over the last 197 years. However, there has been a significant reduction of these free meanders in the last 70 years. In the 19th century, the Hornád River in Slovakia was an unmanaged river system with well-developed free meanders. We openly release Semantic Riverscapes-the dataset we collected and processed, bridging another gap in the field. Due to simplicity, accuracy and effectiveness, this workflow is transferable and cost-effective for large-scale investigations of riverscapes and linear heritage. The results of this study can benefit urban planners in formulating riverside development policies, analyzing the perception of plans for a future scenario before an area is redeveloped, and the method can also aid relevant parties in having a macro understanding of the overall situation of the river as a basis for follow-up research. The results suggest that using this approach, rivers and surrounding landscapes can be analyzed automatically and efficiently, and the mean pixel accuracy (MPA) of the developed model is 90%, which advances state of the art. Then, the relationship between the people's subjective visual perception and the river landscape environment as seen by computers has been established. Concurrent surveys, immersive and non-immersive VR, are used to evaluate these photos, with a total of 111 participants expressing their perceptions across multiple dimensions. The approach is demonstrated with an experiment on a section of the Grand Canal in China where UAV oblique panoramic imagery has been processed using semantic segmentation for visual evaluation with an index system we designed. Addressing these challenges, this study proposes an alternative: a novel workflow for visual analysis of urban river landscapes by combining unmanned aerial vehicle (UAV) oblique photography with computer vision (CV) and virtual reality (VR). The latter only reflects the subjective perception and also entails a laborious process. The former is expensive, hindering large-scale analyses, and it is conducted only on street-level or top-down imagery. Send us a direct message via Twitter or Instagram or email via our contact form.Traditional approaches for visual perception and evaluation of river landscapes adopt on-site surveys or assessments through photographs. Imagery at higher zoom levels © Microsoft. Labels and map data © OpenStreetMap contributors. Radar data via RainViewer is limited to areas with radar coverage, and may show anomalies. Weather forecast maps use the latest data from the NOAA-NWS GFS model. Imagery is captured at approximately 10:30 local time for “AM” and 13:30 local time for “PM”. HD satellite images are updated twice a day from NASA-NOAA polar-orbiting satellites Suomi-NPP, and MODIS Aqua and Terra, using services from GIBS, part of EOSDIS. Heat source maps show the locations of wildfires and areas of high temperature using the latest data from FIRMS and InciWeb. Tropical storm tracks are created using the latest forecast data from NHC, JTWC, NRL and IBTrACS. Blue clouds at night represent low-lying clouds and fog. EUMETSAT Meteosat images are updated every 15 minutes.Ĭity lights at night are not real-time. Live weather images are updated every 10 minutes from NOAA GOES and JMA Himawari-8 geostationary satellites. Explore beautiful interactive weather forecast maps of wind speed, pressure, humidity, and temperature. Watch LIVE satellite images with the latest rainfall radar. Track tropical storms, hurricanes, severe weather, wildfires and more. Zoom Earth visualizes the world in real-time.
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