Satellite imagery are collected at large scale and made freely available by institutions ESA and NASA. This data is collected at high spatial (10-30 m) and temporal (~2 weeks) resolution making it ideal for many applications. However, going from raw satellite imagery to nice looking image mosaics can be quite a mouthful. Here, I show how to use the gdalcubes R-package to produce a nationwide image mosaic of Denmark.
Digital elevation models (DEMs) are very convenient for modeling water flow. Some of the applications include delineation of watersheds, flowlines, or deriving useful other useful measures such as the ‘height above nearest drainage’ (HAND, link to another post on this). As a consequence of climate change, the frequency of extreme precipitation events is expected to increase in the future. Therefore, knowing the whereabouts of water is highly relevant and an important tool for the management of surface water in the landscape.
In a previous post I showed how to use R for creating bathymetric maps for lakes. To make this process even easier, I have created two apps using Shiny. The maps can be downloaded, opened in Google Earth on both desktop and mobile making it easy to bring along. Try theme out!
Shiny for interactive data exploration The R Shiny framework is a simple way to turn R analysis or pipelines into interactive web applications.
Knowing the depth of in aquatic environments are of interest to many e.g. sailors in coastal waters or anglers in lakes. We can measure the depth at different geographic coordinates and use this information to produce bathymetric maps and contour lines. Often however, measurements are only obtained from relatively few points which means that interpolation is required to produce continuous and pretty maps. Higher quality maps can be produced using modern sonar and echo-sounder technology but this may also require gaps to be interpolated.
Wind traveling across water surfaces creates waves. Wave action depends on several parameters including fetch which is the unobstructed length which the wind can travel across a water surface from a given direction. Areas with high wind fetch are often exposed areas but this also depends on the primary wind direction. By calculating wind fetch, we can quantify exposure of different areas and shorelines in waterbodies.
Rain, rain and more rain - 2019 was a very wet year in Denmark and especially September and October were very rainy (DR news). The year ended with 905.2 mm which tied the previous record from 1999. The normal amount is around 700 mm. It continued to rain in 2020 with February and already on February 23 the previous record was surpassed (DR news). The extreme amount of water caused flooding in several parts of Denmark.