Automate It

The very high resolution of UAV-based images (better than 5cm ground resolution) opens new possibilities for mapping. The human operator can easily recognize most objects in the imagery. However, for an efficient workflow, ideally objects of interest should be detected and extracted automatically from the imagery: this expedites the surveying and mapping process. Although automatic image interpretation has a long history in research, the very high resolutions faced with nowadays brings new challenges: working on object basis rather than pixel, but at the same time exploit the pixel resolution for the retrieval of land tenure object features, modelling and exploitation of context in several hierarchy levels, and efficient use of prior knowledge. WP5 aims to exploit the imagery captured in the UAV flights of WP4 to enable automatic land tenure feature extraction. Such an approach cannot deliver complete matching – as some tenure boundaries are only social and not visible to sensors – however, even 50% matching would radically alter tenure mapping workflow costs and times.

 

Ongoing work:

The tool is designed to support the semi-automatic delineation of visible cadastral boundaries from UAV data. The delineation tool combines the output from gPb contour detection and SLIC superpixels based on random forest classification. This repository provides source code,  test data and a manual describing all workflow steps of the tool. The subsequent interactive delineation is managed with the QGIS BoundaryDelineation plugin. This repository provides source code,  test data and a manual describing the plugin’s installation and use. The BoundaryDelineation plugin can be downloaded via the QGIS plugin repository. The following video demonstrates the use of the BoundaryDelineation QGIS plugin.