Semi-automatic detection of field boundaries from high-resolution satellite imagery

Organised by Laboratory of Geo-information Science and Remote Sensing

Tue 25 August 2015 14:00 to 14:30

Venue Lumen, gebouwnummer 100
Room 2

By Joël Davidse (The Netherlands)

Information on the properties of boundaries has always been important. This information can serve as legal protection of ownership, as well as provide valuable input for applications related to crop monitoring or yield forecasting. Attributes of interest are specifically the precise location of the boundary and the size of the area surrounded by the boundary. This information is available in many western parts of the world, where land is expensive. In less developed parts of the world this information is as valuable to the owners of fields too, but often lacking or incomplete. Cadastral systems there are often underdeveloped. Providing this information is a laborious job, requiring high inputs in skilled surveyors, equipped with expensive instruments. Regarding this problem this research investigates the possibility of using very high resolution imagery form the WorldView-2 satellite sensor to be processed towards the end of making this field boundary information available in a more efficient way. The results are verified by other data sources and methods. These include; walking the boundaries in the study area with a handheld GPS, imaging the area using a fixed wing Unmanned Aerial Vehicles (UAV) platform equipped with a NIR camera, and manual on-screen digitizing. The specific study area in Sougoumba, Mali, provided large challenges in the process, due to the heterogeneity in the landscape. The final results show that the methodology of image segmentation is not accurate enough for direct extraction of the exact location of the boundaries and the area involved. On the other hand many boundaries are well delineated, providing a useful aim in already existing practises of manual on-screen digitizing. As a side result the use of UAV’s equipped with lightweight cameras and (preferably) RTK positioning systems seem very promising to have a valuable contribution.