The International Specifications for Ski Orienteering Maps have been modified and released as ISSkiOM 2019 Revision 3, which is valid from 1st December 2024.
The most important changes:
New symbols for tracks which must be stayed on Sometimes due to special considerations, competitors are required to stay on the track and are forbidden to leave the track to the side or join the track from the side. These tracks are shown on the map with orange color.(IOF ISSkiOM 2019 Revision 3, chapter 2.5)
For a better readability, a white mask (0.15 mm on each side) is used under all green and orange track symbols
New Symbol for Dangerous section
How to work with the new specifications?
To work with the updated symbol sets already now, you can download a so-called silent update in OCAD under the menu Help>Download Update. The next complete OCAD update is planned for November.
To update an existing ski orienteering map to the latest symbol set, use the Update Symbol Set function.
The Canvas function now also supports Map Flip and Map Exchange.
If a Map Exchange (new map) or Map Flip (turn the map over) is inserted in a course, a different canvas can be assigned for each map extract in the canvas function.
Example
A Map Flip has been added to a course.
In the canvas function, two map extracts appear for this course (#1 and #2). The first map extract is assigned to Canvas East, the second to Canvas West.
When exporting, both map extracts are exported as PDF files.
PDF with first part of the course.
PDF with second part of the course after the Map Flip. Note that the map extract and map layout is different to the first part of the course.
The above example can be downloaded here as OCAD file together with other Canvas examples.
If vector data such as Shape, GeoPackages or DXF are imported into OCAD, OCAD must know which imported objects are to be assigned to which OCAD symbols by means of a Cross Reference Table (.ocdCrt) during import.
If the translation table contains errors or gaps, the imported objects are displayed in OCAD as unsymbolized objects, i.e. the objects appear in the drawing area but are not assigned to any OCAD symbol.
What properties do unsymbolized objects have?
Unsymbolized objects are displayed by default in red color on top of the other map objects.
If an unsymbolized object is selected, the layer name is shown in the left part of the status bar.
Hide or Show unsymbolized objects by changing the Show Objects without Symbol option in the Symbol menu.
How can unsymbolized objects be converted?
Option Cross Reference Table:
You can use the Convert Imported Layers to Symbol command from the Map menu to convert unsymbolized objects to symbolized OCAD objects. In the dialog box you can create and/or modify a list of references. A reference consists of a layer (left side) and the corresponding OCAD symbol (right side). Symbol number -1 means that OCAD do not import and delete the layer.
You can save the list to a cross reference (.ocdCrt) file for later use. You can load an existing cross reference file to modify or execute it. Predefined cross reference tables by OCAD can be found in the folder C:\Program Files\OCAD\OCAD 2018 [EDITION]\Crt.
This procedure is useful if geodata is often imported.
Option Manual Assignment:
In the drawing area, select an unsymbolized object.
Select the corresponding OCAD symbol in the symbol box on the right side.
With the last OCAD update there was a small improvement of the OCAD Route Analyzer. The route length, climb and time for each variant is now displayed in the txt file for relay courses.
The txt file will be created in the same folder, where your course setting project is saved when you click on Analyze routes (current course) or Analyze routes (all courses). The txt file contains a summary of all routes, as well as a summary for each course and variant separately.
The values can be added to the Courses dialog, e.g. add Extra length for sprint courses or add Climb used.
Not yet tried the OCAD Route Analyzer? Try it yourself with our demo data.
In the latest OCAD Update, the option Create Feature Map was added to the DEM Wizard to gain even more information from LiDAR data.
The Feature Map can be used to recognize objects close to the ground such as stones, walls, tree trunks, fences, or cars which were previously not or only poorly recognizable on background maps that can be created with the DEM Wizard in OCAD.
How the creation of Feature Maps works
In a LiDAR file, each point is typically assigned to a class based on the reflection of the laser pulse, such as ground, vegetation, buildings or water. Only ground points are used to generate the Hill Shading and Slope Gradient map. This means that a lot of information is lost that is available in points classified differently.
To generate the Feature Map, OCAD reclassifies the LiDAR points so that not only ground points but all points are used for the calculation. You can further define from and up to which height points are taken into account.
Example stone detection Pontresina, Switzerland LiDAR data from 2022, 29 points per square meter, 0.5m cell size, 0.0-2.0m threshold.
Orienteering Map of stony terrain.Slope Gradient Map. Most stones are not visible. The stones that are visible are probably overgrown and therefore classified as ground points.Feature Map. Some stones becomes clearly visible.
Example stone wall detection Jura, Switzerland LiDAR data from 2020, 25 points per square meter, 0.5m cell size, 0.0-1.5m threshold.
Slope Gradient Map. The stone walls are only partially visible.Feature Map. The stone walls become clearly visible.
Example tree trunks detection S-chanf, Switzerland LiDAR data from 2022, 25 points per square meter, 0.5m cell size, 0.0-0.5m threshold.
Slope Gradient Map.Feature Map. Tree trunks are visible and can help to determine the exact position.
Example urban area Zeiningen, Switzerland LiDAR data from 2020, 13 points per square meter, 0.5m cell size, 0.0-2.0m threshold.
Slope Gradient Map.Feature Map. Hedges, walls, cars and bridges becomes visible.Vegetation Height Map. Most of the objects on the Feature Map are also visible on this map.
Example without satisfactory result Lillehammer, Norway LiDAR data from 2017, 10 points per square meter, 0.75m cell size, 0.0-2.0m threshold.
Slope Gradient Map.Feature Map. In this area there are many small trees and bushes with branches down to the ground. It is difficult to distinguish, for example, large stones from trees or knolls from this data.Vegetation Height Map of the same area.
Conclusion:
The information content of the feature map depends on the terrain type, the settings you choose in the dialog and the quality of the LiDAR data, in particular the point density. With good data quality, the feature map can be a useful addition to the existing background maps, to detect objects and help the cartographer to determine the exact position in the terrain.
Credit goes to Jeff Teutsch and his Lidar Case Study – Using simple ground reclassification to see features in data.
