Europa Maps

[Magdalena Liendo]

Registrantsuse available use maps developed by the downstream user sectors to prepare their chemical safety assessments under REACH that reflect relevant and realistic information on uses and conditions of use.

Here are maps for vanilla Europa Universalis II, showing terrain and province IDs. For the rules on getting maps, see the article on terra incognita. For more detailed information on province attributes, consult the EU2 Atlas.

This proposal is part of the EU soil strategy for 2030. Its aim is to specify the conditions for a healthy soil, determine options for monitoring soil, and lay out rules conducive to sustainable soil use and restoration.

A staggering 61% of EU soils are in an unhealthy state, according to the EUSO soil health dashboard based on the evidence currently available. This figure is an underestimate of the actual extent of soil degradation, given the recognised lack of data on many other soil degradation issues, such as soil contamination.

The current value is in line with the headline assessment made for the establishment of a Soil Mission that 60-70% of the soils of Europe were in an unhealthy state. The most prevalent types of soil degradation appear to be loss of soil organic carbon (53%), the loss of soil biodiversity (37%), and the risk of peatland degradation (30%).

In addition, the dashboard shows that most of the unhealthy soils are in fact subject to more than one type of soil degradation. Tackling different types of soil degradation is important for the soil restoration agenda.

The EUSO soil health dashboard is based on a set of 15 indicators of soil degradation processes, covering the following nine topics: soil erosion, soil pollution, nutrients, loss of soil organic carbon, loss of soil biodiversity, soil compaction, soil salinisation, loss of organic soils and soil sealing.

The dashboard is based on the scientific evidence available to date; in practice however, the indicators only cover a subset of degradation processes affecting soils. The EUSO team at the JRC hopes that the dashboard will put a spotlight on the current soil data gaps, with a view to steering improved data sharing and targeted research.

A novelty of the EUSO soil health dashboard lies in the use of the convergence of evidence approach, which spatially combines datasets to highlight the intensity and location of soil degradation processes. The resulting map shows, for the first time, where scientific evidence converges to indicate areas that are likely to be affected by soil degradation. In other words, it provides an indication of where unhealthy soils may be located in the EU.

This was made possible by using EU-wide harmonised datasets, most of which were developed by the JRC and sourced from ESDAC - the long operating European Soil Data Centre, but also coming from the European Environment Agency (EEA) and other institutions. Over time, other data will be added from different sources.

Another novelty is the setting of threshold values to determine when soils can be considered healthy or unhealthy. Thresholds have been set for each soil degradation process, based on a combination of scientific estimates and established critical limits. They represent an estimate of the point beyond which most soils can reasonably be considered vulnerable to a certain process. Given the very wide range of soil types, some of these EU-wide thresholds may result in large uncertainties. In the future, the accuracy of the EUSO dashboard map will be improved by applying locally based thresholds, or offer users the option to create maps based on the thresholds they consider most appropriate.

The EUSO soil health dashboard also presents the overlapping area observed between pairs of the 15 soil degradation processes, highlighting typical associations. Finally, statistics and maps are presented for each indicator through an interactive display whereby users can select the type of soil degradation and the scale they are interested in.

Additional elements will be developed to reflect the implementation of specific policy strategies and legislation, e.g. soil strategy, zero pollution action plan, biodiversity strategy, farm-to-fork strategy, and the sustainable development goals.

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Of Jupiter's Galilean satellites, Europa has the best imaging coverage. Much of the surface has been imaged at a resolution of 1 to 4 kilometers per pixel. There is also significant coverage at about 200 meters per pixel, plus small areas at higher resolution, in some cases down to 10 to 20 meters per pixel. But there are also large areas that are poorly imaged. Several global maps have been made of Europa but I felt they could be improved so I decided to make a new one. An important factor is also that no spacecraft that can image Europa well enough to make a new map outdated is going to arrive at Jupiter until the late 2020s at the very earliest (but of course I would love to see my new map become completely outdated as soon as possible!).

To make a map of Europa it is necessary to reproject the spacecraft images to a common projection -- I use simple cylindrical projection -- and then seamlessly mosaic them into a big map. I started by making a global full-color map from the available global color coverage. The best resolution of this color data is approximately 1.5 kilometers per pixel, but the resolution is worse in large areas (typically about 7to 15 kilometers per pixel). I then added the higher resolution data (most of it about is 200 meters per pixel but in some cases the resolution is higher or lower) to the color map. Almost all of the high-resolution data is monochrome (grayscale). High-resolution grayscale data can be added to a color image in Photoshop by making an intensity layer, pasting the grayscale data into that layer and then adjusting brightness and contrast in that layer. The result is an image where the topographic details come from the high-resolution grayscale data, and the color is from lower-resolution color data.

A major complication when making a seamless map from the source images of Europa is that they were obtained at various viewing and illumination geometries. Europa's color and contrast is remarkably variable depending on viewing geometry, even when the illumination geometry doesn't change much. Here is a particularly interesting example:

These images are in simple cylindrical projection. The one with overall lower contrast is from images obtained by NASA's Galileo spacecraft during its G1 orbit while the more contrasty one is from images obtained during Galileo's E14 orbit. These two images were obtained when the illumination geometry was very similar but the viewing geometry was not. Notice the big changes in contrast. Some of the narrow lines appear darker than the surrounding terrain in one image, whereas in the other image they appear slightly brighter. The viewing geometry can be seen below:

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