For documentation on the current version, please check Knowledge Base.
Poles Analysis
This page describes the Orbit desktop extension “Poles Analysis”.
Main Toolbar > Extract > Poles Analysis
Concepts
The “Poles Analysis” extension automatically detects poles based on a point cloud and a set of user-defined parameters.
Pole detection is based on the geometry of the point cloud: poles are expected to be round and standing straight. Based on this assumption the process of detecting poles can be split into 3 main steps:
- Quickly exclude areas that cannot contain poles.
- Find pole candidates and check if they meet the criteria of being round and straight.
- (Optional) Exclude trees, traffic signs, and poles which are not on the ground.
Source
Use the generic workflow for Point Cloud Based Extensions to define the source file.
The method for the range of interest is 'Area', 'Path' and 'Seed points'.
Parameters
Generic concepts, see Preferences for Detectors
When creating a new project preset parameters are copied from the Detector Preferences.
Changing parameters in the sidebar influences the currently opened project immediately, while Parameters in the Preferences are only taken into account at the moment of Project creation.
Use case
Small pole close to a big one might not be found as it will not show a density peak at the location of a smaller pole. Parameter to change to have higher probability to find the small pole as well: Histogram Cell Size.
Test
Before running the detector on the range of interest, use this step to test if objects are detected as expected.
Measure the object to test if the parameters are defined correctly.
Start - Run the test measurement. If the object conforms with the parameters then the message “Feature is detected” will be shown, otherwise Orbit will provide a tip on the calculated statistics and recommendation on which parameters need to be changed for this feature to be detected as a feature of interest.
Clear the current test measurement.
Workflow on Automated Pole Detection
- Inspect the source dataset
- Set unique parameters for pole detection
- Detect representative poles on small zones
- Detect poles for all input data
- Optional : results can be imported and used to create an Inventory theme to further analyse