RESUMO
Shaded relief is an effective method for visualising terrain on topographic maps, especially when the direction of illumination is adapted locally to emphasise individual terrain features. However, digital shading algorithms are unable to fully match the expressiveness of hand-crafted masterpieces, which are created through a laborious process by highly specialised cartographers. We replicate hand-drawn relief shading using U-Net neural networks. The deep neural networks are trained with manual shaded relief images of the Swiss topographic map series and terrain models of the same area. The networks generate shaded relief that closely resemble hand-drawn shaded relief art. The networks learn essential design principles from manual relief shading such as removing unnecessary terrain details, locally adjusting the illumination direction to accentuate individual terrain features, and varying brightness to emphasise larger landforms. Neural network shadings are generated from digital elevation models in a few seconds, and a study with 18 relief shading experts found that they are of high quality.
Assuntos
Gráficos por Computador , Redes Neurais de Computação , Algoritmos , Estimulação LuminosaRESUMO
The intermediate host of Fasciola hepatica is Lymnaea truncatula in Switzerland. The snail and the free-living stages of the parasite require a moderate climate and moisture for survival, reproduction, and transmission. In Switzerland, these conditions are present in many regions, resulting in a mean prevalence of bovine fasciolosis from 8.4 to 21.4%. An interactive map was created in order to demonstrate the relative risk of transmission by modelling the environmental conditions that promote the survival and reproduction of the larval stages of the parasite and the parasite's intermediate host. The map is based on temperature and rainfall data, soil conditions including ground water and forest cover in Switzerland. Extensive information on the free-living stages of F. hepatica and the intermediate host L. truncatula and how the development of these are affected by these environmental factors was used to create the interactive risk map.