The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume XLIII-B2-2022
30 May 2022
 | 30 May 2022


G. S. N. Perera and H. A. Nalani

Keywords: UAV, Underneath Canopy, Ortho-mosaic, DTM, Topographic Surveying

Abstract. With the advancement of sensor technology, unmanned aerial vehicles (UAVs) or drones revolutionize several fields including topographic surveying, agriculture, recreation, emergency, rescue and so on. The autonomous flight modes available in current UAVs make it broaden to manoeuvring by an unskilled person. This, of course, causes to widely use the drone technology among different user communities. Of the revolutionized fields, topographic surveying is prominent because many low cost UAVs with on-board light weight optical payloads often deliver mapping products such as ortho-photos and DEMs with centimetre level accuracy (in XY and Z) that had been exclusively bounded to the expensive field surveying methods earlier. Though drones enables to obtain centimetre level geometric accuracy, the main drawback of the technology is inability to see underneath vegetation canopy which hinders applicability of drones for a complete topographical survey. In order to view beneath the tree canopies, UAV LiDAR is a solution but due to its high cost, it is still not popular among several communities who involve with land surveying. To measure underside vegetation, field surveying methods such as total stations and theodolites traversing are being mainly practised by the users. But it is also not a viable solution since it consumes much time and money. If remotely sensed data collection is able to capture landscapes that had been hampers by the canopies, definitely it will be a cost effective and a rapid solution. As such, oblique imagery (UAV) acquired in manual flight mode at very low altitudes is a good solution. The objective of the study is to develop a novel approach to generate UAV deliveries without vegetation canopy in vegetated areas.

First, autonomous flight mission is completed while maintaining 80% and 70% forward and lateral overlaps. For the terrain patches where they are covered by tree canopies, oblique imageries have been collected while operating the drone manually at low altitudes. Each UAV flight is separately processed and merged in to a single image to extract 2D maps without gaps beneath tree canopies. Re-sampling is fulfilled prior to stitching in order to gain a seamless product. Performed accuracy analysis confirmed that the developed approach is sufficient to produce DTMs and ortho-mosaics having average RMSE-XY 0.087m and RMSE-Z 0.177m at 4.0cm GSD which is really acceptable. Besides, there is not any significant accuracy variation between underneath canopy areas and open areas.