@article{A. Rokhmana_E. Tjahjadi_D. Agustina_2019, title={Cadastral Surveys with Non-metric Camera Using Uav: A Feasibility Study}, volume={4}, url={https://knepublishing.com/index.php/KnE-Engineering/article/view/5856}, DOI={10.18502/keg.v4i3.5856}, abstractNote={<p>Orthophoto maps are believed by mapping communities as a favorable media to generate land parcel boundaries for cadaster survey related projects. However, since burgeoning off-the-shelf cameras mounted on the unmanned aerial vehicle (UAV) are commonly utilized for photographing such boundaries, unreliable and unstable intrinsic parameters of these non-metric cameras impede good quality orthophoto productions. This paper presents an alternative method to measure the boundaries reliably without an existence of the orthophoto. A degraded quality of the orthophoto can be circumvented by our newly proposed method so called direct visual referencing. This method comprises two stages. The first step is to perform on the fly camera calibration to minimize instabilities of the intrinsic components of the non-metric camera. Modifying common and widely known flying paths for aerial photogrammetry mission is enabling a block variant self-calibrating bundle adjustments to proceed. The second step is a digitation process. Carefully selected Premark or prominent features along the boundaries are digitized on arbitrary selected images. These features are then matched to the similar ones onto all available images by performing multi photo geometrically constraint least squares image matching. Final results are 3D coordinates from the multi photos triangulation process. These boundaries coordinates are compared against the GPS-RTK measurements on the field. Deviations of these types of coordinates are around 1 cm. It is obvious that this method meets the precision requirement of the GPS-RTK measurements. Therefore we firmly believed that conducting UAV’s cadastral surveys using direct visual referencing is very promising in the near future.</p&gt;}, number={3}, journal={KnE Engineering}, author={A. Rokhmana, Catur and E. Tjahjadi, Martinus and D. Agustina, Fransisca}, year={2019}, month={Dec.}, pages={227–237} }