Norway is a country with huge climate variations between seasons, lowlands and mountains, coastal areas and inland, and between north and south. In the recent years, we have also seen more extreme weather and greater fluctuations in temperature and snow cover. At the same moment of time there might be meters of snow in the mountains, while the trees are blooming by the fjord a few kilometers away. Outdoor activities are popular among citizens and tourists alike, and in Norway you can do typical summer and winter activities all year around. The goal of this blog post is to create a near real time map of the snow cover, where the snow blends into the landscape.
As shown on this blog, I like to create maps and 3D visualisations using a wide range of open source tools, combined with various programming techniques. This snow mapping experiment is no exception. Open Source allows me to mix and match the tools and techniques I need, and doing this programmatically has the added benefit of automation. When the full map making process is defined, we can easily run it for various areas and terrains. It was an important goal of this project to keep the snow cover up-to-date on a daily basis.
Geospatial datasets can be very large, and we often have to divide the data into chunks to be able to run calculations. I have divided mainland Norway into 218 cells, each covering an area of 50 x 50 km. With datasets at 10 meters resolution, all tools presented below were capable of processing the data.
The Norwegian Mapping Authority released its topographic datasets in 2013. This included an elevation model of mainland Norway at 10 m resolution. The Norwegian Water Resources and Energy Directorate (NVE) is monitoring the country's water resources, and they provide data of snow gain, snow melt and snow depth. As my map is aimed towards cross-country skiers, I’m using a dataset showing areas with a skiing surface, based on interpolated weather observations.
Elevation data
The 10 m digital elevation model (DEM) from the Norwegian Mapping Authority was used to blend the snow into the landscape. A few GDAL commands allowed me to create a 50 x 50 km DEM from the nationwide DEM, and to translate it into the various formats supported by the tools in use.
The 10 m elevation model contains too much detail to represent a snow cover. I could downsample the dataset, but that would blur out important terrain features like mountain ridges and valley edges. Terrain Sculptor came to the rescue. It is a tool by Bernhard Jenny and Anna Leonowicz to generalize terrain models for relief shading. It removes unnecessary and distracting terrain details, and better resembles a smooth snow covered landscape. Unfortunately, Terrain Sculptor can only be used with a graphical interface, and not as a command line tool, so it can not be used in an automatic process. I used it to create a generalised terrain model for the 50 x 50 km area of Jotunheimen and Tyin.
The generalised elevation model was used to create a shaded relief. We can easily create a grayscale hillshade with GDAL, but the snow required some tints to look better. I created a continuous colour scale from blue shadows to white with a touch of yellow, and turned the grayscale hillshade into a tinted hillshade. For areas without snow, I used the same elevation data to create a color relief progressing from green for lower elevations up through yellows/browns, and on to grays and white at the highest elevations.
Finally, the elevation model was used to calculate steep terrain (slope) where there will be less snow. The steep terrain will be subtracted from the snow surface to improve the view in alpine areas. This was achieved in a series of steps: A slope surface was calculated from the DEM, and then areas steeper than 50 degrees were extracted and vectorised. The process of vectorising raster data is described below.
Snow cover
The skiing surface dataset from the Norwegian Water Resources and Energy Directorate (NVE) is available from a public Web Map Service (WMS) with a 1 km resolution. The dataset is updated 8 times a day. The original WMS image includes 4 colours: Blue represents skiing surface with dry snow, violet is surface with wet snow, yellow is areas with little snow, and green is areas without snow. As the map is targeted towards cross country skiers, the dry (blue) and wet (violet) snow are combined into one layer. The areas with little snow (yellow) are not included in this map, but could be used to create a more gradual shift between snow cover and bare ground.
To avoid the pixelated appearance of the snow surface, the image is vectorised into smooth scalable snow polygons. This was achieved using Potrace by Peter Selinger, an open source tool for tracing bitmaps. Potrace transforms the the blocky WMS image into smooth vectors. It supports GeoJSON output, which makes it easier to use in geographic applications. A problem with this technique is that the smooth polygons seem more accurate than they are. There are other, and probably better, ways to interpolate the data, as following height contours in the area.
With all the map layers in place, Mapnik was used to generate the map shown below. Mapnik is an open source toolkit to generate beautiful maps from different vector and raster sources. The order and styles are expressed in an XML document, and then applied to the data. First, colour relief, lakes, snow polygons, steep terrain, glacier polygons and road lines are added in turn. Then all the layers are blended with the hillshade, before adding buildings and a thin lake outline as a final touch.
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| The snow map of Jountunheimen we're going to create. |
As shown on this blog, I like to create maps and 3D visualisations using a wide range of open source tools, combined with various programming techniques. This snow mapping experiment is no exception. Open Source allows me to mix and match the tools and techniques I need, and doing this programmatically has the added benefit of automation. When the full map making process is defined, we can easily run it for various areas and terrains. It was an important goal of this project to keep the snow cover up-to-date on a daily basis.
 |
| Crosscountry skiing in Jotunheimen national park. Photo: Bjørn Sandvik |
The Norwegian Mapping Authority released its topographic datasets in 2013. This included an elevation model of mainland Norway at 10 m resolution. The Norwegian Water Resources and Energy Directorate (NVE) is monitoring the country's water resources, and they provide data of snow gain, snow melt and snow depth. As my map is aimed towards cross-country skiers, I’m using a dataset showing areas with a skiing surface, based on interpolated weather observations.
Elevation data
The 10 m digital elevation model (DEM) from the Norwegian Mapping Authority was used to blend the snow into the landscape. A few GDAL commands allowed me to create a 50 x 50 km DEM from the nationwide DEM, and to translate it into the various formats supported by the tools in use.
The 10 m elevation model contains too much detail to represent a snow cover. I could downsample the dataset, but that would blur out important terrain features like mountain ridges and valley edges. Terrain Sculptor came to the rescue. It is a tool by Bernhard Jenny and Anna Leonowicz to generalize terrain models for relief shading. It removes unnecessary and distracting terrain details, and better resembles a smooth snow covered landscape. Unfortunately, Terrain Sculptor can only be used with a graphical interface, and not as a command line tool, so it can not be used in an automatic process. I used it to create a generalised terrain model for the 50 x 50 km area of Jotunheimen and Tyin.
The generalised elevation model was used to create a shaded relief. We can easily create a grayscale hillshade with GDAL, but the snow required some tints to look better. I created a continuous colour scale from blue shadows to white with a touch of yellow, and turned the grayscale hillshade into a tinted hillshade. For areas without snow, I used the same elevation data to create a color relief progressing from green for lower elevations up through yellows/browns, and on to grays and white at the highest elevations.
Finally, the elevation model was used to calculate steep terrain (slope) where there will be less snow. The steep terrain will be subtracted from the snow surface to improve the view in alpine areas. This was achieved in a series of steps: A slope surface was calculated from the DEM, and then areas steeper than 50 degrees were extracted and vectorised. The process of vectorising raster data is described below.
Snow cover
The skiing surface dataset from the Norwegian Water Resources and Energy Directorate (NVE) is available from a public Web Map Service (WMS) with a 1 km resolution. The dataset is updated 8 times a day. The original WMS image includes 4 colours: Blue represents skiing surface with dry snow, violet is surface with wet snow, yellow is areas with little snow, and green is areas without snow. As the map is targeted towards cross country skiers, the dry (blue) and wet (violet) snow are combined into one layer. The areas with little snow (yellow) are not included in this map, but could be used to create a more gradual shift between snow cover and bare ground.
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| The original WMS image of skiing conditons. |
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| Wet at dry skiing conditions combined. Each square is 1 x 1 km. |
To avoid the pixelated appearance of the snow surface, the image is vectorised into smooth scalable snow polygons. This was achieved using Potrace by Peter Selinger, an open source tool for tracing bitmaps. Potrace transforms the the blocky WMS image into smooth vectors. It supports GeoJSON output, which makes it easier to use in geographic applications. A problem with this technique is that the smooth polygons seem more accurate than they are. There are other, and probably better, ways to interpolate the data, as following height contours in the area.
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| Vectorised image from Potrace. |
With all the map layers in place, Mapnik was used to generate the map shown below. Mapnik is an open source toolkit to generate beautiful maps from different vector and raster sources. The order and styles are expressed in an XML document, and then applied to the data. First, colour relief, lakes, snow polygons, steep terrain, glacier polygons and road lines are added in turn. Then all the layers are blended with the hillshade, before adding buildings and a thin lake outline as a final touch.
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| Jotunheimen and Tyin covered with a snow cover obtained from the Norwegian Water Resources and Energy Directorate on. The map image is applied to a 3D model using elevation data from the Norwegian Mapping Authority. |
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