rvr_interface

Repo for code and script transfer between mundialis and RVR - GRASS GIS addons:

• m.import.rvr imports data for the processing of buildings analysis, green roofs and/or trees analysis.

• r.import.dtm_nrw downloads and imports the NRW digital terrain model (DTM) 1m into the current mapset. Only the extent of the current region is downloaded and imported with a 1m resolution.

• r.import.ndsm_nrw calculates an nDSM by subtracting input digital terrain model (DTM) data (defined by the dtm parameter) from an input DSM indicated by the dsm parameter. If no DTM is defined, NRW DTM data is automatically imported using r.import.dtm_nrw.

• r.in.pdal.worker is a worker addon for r.in.pdal and is used in m.import.rvr.

• m.analyse.buildings

  • r.extract.buildings extracts buildings as vectors and calculates height statistics (minimum, maximum, average, standard deviation, median, percentile) and presumable number of stories using an nDSM-raster, NDVI-raster, and FNK-vector (Flaechennutzungskatalog).
  • r.extract.buildings.worker is a worker module that is started by r.extract.buildings.
  • v.cd.areas calculates differences between two vector layers (e.g. classification and reference) by making use of v.overlay with operator "xor". Only differences with a defined minimum size are extracted.
  • v.cd.areas.worker is a worker module that is started by v.cd.areas.
  • r.extract.greenroofs extracts vegetated roofs from aerial photographs, an nDSM, a building vector layer and optionally an FNK (Flaechennutzungskatalog) and tree vector layer.
  • r.extract.greenroofs.worker is a worker module that is started by r.extract.greenroofs.

• m.analyse.trees

  • r.trees.peaks assigns pixels to nearest peak (tree crown).
  • r.trees.traindata generates training data for a machine learning (ML) model to detect trees and provides a preliminray tree candidate map in either vector or raster format.
  • r.trees.mltrain trains the ML model with the training data from before or own training data.
  • r.trees.mlapply applies the tree classification model in parallel to the area of interest (current region).
  • r.trees.mlapply.worker applies classification model for a region defined by a vector. This module should not be called directly, instead it is called in parallel by r.trees.mlapply.
  • r.trees.postprocess generates single tree delineations from tree pixels and geomorphological peaks.
  • v.trees.param calculates various tree parameters for tree crowns given as input vector map treecrowns.
  • v.trees.param.worker is used within v.trees.param to calculate various tree parameters for tree crowns in parallel.
  • v.trees.species classifies trees in deciduous and coniferous trees.
  • v.trees.cd calculates the change between two given treecrown vector maps (input and reference for time t1 and t2, respectively).
  • v.trees.cd.worker is a worker module that is started by v.trees.cd.

Building and running a docker image

In the folder with the Dockerfile, run

docker build -t rvr_interface:latest .

Instead of "latest", a version number can be used. This should create a local docker image with all needed addons and dependencies. Once the docker image has been created locally, it can be started on Linux with e.g.

xhost local:*
docker run -it --privileged --rm --ipc host \
       -v /path/to/grassdata:/grassdb \
       -v /path/to/rvr_daten:/mnt/data \
       -v "/tmp/.X11-unix:/tmp/.X11-unix:rw" \
       --env DISPLAY=$DISPLAY \
       --device="/dev/dri/card0:/dev/dri/card0" \
       rvr_interface:latest bash

On Windows you need to do the following before starting the docker container:

1. Install Docker Desktop
2. Download and install VcXsrv Windows X Server
3. Start Xlaunch and configure it (see here):
   • in the "Extra Settings" window enable "Disable access control"
   • in the "Finish Configuration" window click "Save configuration" and save it e.g. on the desktop

Now you can run the docker:

# get own IP adress (take the value of IPAdress e.g. 10.211.55.10 and not 127.0.0.1)
Get-NetIPAddress
# or
ipconfig

# set DISPLAY variable (set <YOUR-IP>)
set-variable -name DISPLAY -value <YOUR-IP>:0.0

# start Docker
docker run -it --privileged --rm --ipc host \
       -v C:/Users/path/to/grassdata:/grassdb \
       -v C:/Users/path/to/rvr_daten:/mnt/data \
       --env DISPLAY=$DISPLAY \
       --device="/dev/dri/card0:/dev/dri/card0" \
       rvr_interface:latest bash