Prerequisites
Problem Statement
The image output is a great help, but for network planning, it's helpful to be able to map the modelled propagation of multiple sites, ie: can these repeaters 'see' each other, etc. The 'page output doesn't allow this.
Proposed Solution
If the image.png output could be accompanied by a georeferencing .pgw 'world file'.
These specify where in the real world the image exists, so we can add them to our maps in a GIS.
Even better if .kml could be output, as other radio propagation software does. maprad.io & ve2dbe's radiomobile are two good ones.
These can be drag'n'dropped onto a Google Earth canvas to build up the coverage of multiple nodes/repeaters.
https://en.wikipedia.org/wiki/World_file
https://qgis.org/
https://maprad.io/
https://www.ve2dbe.com/
Current Alternatives
The .png images can be georeferenced manually in QGIS, and that works, but it's a bit clunky and time-consuming. The site planner already 'knows' where things are. Outputting that in a form that we can use for mapping would be gret.
Importance
Important
Additional Context
We love your work!
Prerequisites
Problem Statement
The image output is a great help, but for network planning, it's helpful to be able to map the modelled propagation of multiple sites, ie: can these repeaters 'see' each other, etc. The 'page output doesn't allow this.
Proposed Solution
If the image.png output could be accompanied by a georeferencing .pgw 'world file'.
These specify where in the real world the image exists, so we can add them to our maps in a GIS.
Even better if .kml could be output, as other radio propagation software does. maprad.io & ve2dbe's radiomobile are two good ones.
These can be drag'n'dropped onto a Google Earth canvas to build up the coverage of multiple nodes/repeaters.
https://en.wikipedia.org/wiki/World_file
https://qgis.org/
https://maprad.io/
https://www.ve2dbe.com/
Current Alternatives
The .png images can be georeferenced manually in QGIS, and that works, but it's a bit clunky and time-consuming. The site planner already 'knows' where things are. Outputting that in a form that we can use for mapping would be gret.
Importance
Important
Additional Context
We love your work!