Application of Deep Learning for Delineation of Visible Cadastral Boundaries from Remote Sensing Imagery

S. Crommelinck*, M.N. Koeva, M.Y. Yang, G. Vosselman

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

28 Citations (Scopus)
472 Downloads (Pure)


Cadastral boundaries are often demarcated by objects that are visible in remote sensing imagery. Indirect surveying relies on the delineation of visible parcel boundaries from such images. Despite advances in automated detection and localization of objects from images, indirect surveying is rarely automated and relies on manual on-screen delineation. We have previously introduced a boundary delineation workflow, comprising image segmentation, boundary classification and interactive delineation that we applied on Unmanned Aerial Vehicle (UAV) data to delineate roads. In this study, we improve each of these steps. For image segmentation, we remove the need to reduce the image resolution and we limit over-segmentation by reducing the number of segment lines by 80% through filtering. For boundary classification, we show how Convolutional Neural Networks (CNN) can be used for boundary line classification, thereby eliminating the previous need for Random Forest (RF) feature generation and thus achieving 71% accuracy. For interactive delineation, we develop additional and more intuitive delineation functionalities that cover more application cases. We test our approach on more varied and larger data sets by applying it to UAV and aerial imagery of 0.02–0.25 m resolution from Kenya, Rwanda and Ethiopia. We show that it is more effective in terms of clicks and time compared to manual delineation for parcels surrounded by visible boundaries. Strongest advantages are obtained for rural scenes delineated from aerial imagery, where the delineation effort per parcel requires 38% less time and 80% fewer clicks compared to manual delineation.
Original languageEnglish
Article number2505
Pages (from-to)1-22
Number of pages22
JournalRemote sensing
Issue number21
Early online date25 Oct 2019
Publication statusPublished - 1 Nov 2019


  • indirect surveying
  • RF
  • CNN
  • image analysis
  • deep learning
  • machine learning
  • boundary delineation
  • boundary extraction
  • cadastral mapping


Dive into the research topics of 'Application of Deep Learning for Delineation of Visible Cadastral Boundaries from Remote Sensing Imagery'. Together they form a unique fingerprint.

Cite this