TY - JOUR

T1 - Automatic Extraction of Ground Control Points from 3D LIDAR Mobile Mapping and UAV Imagery for Aerial Triangulation

AU - Naimaee, Reza

AU - Saadatseresht, Mohammad

AU - Omidalizarandi, Mohammad

N1 - Funding Information: We would like to thank Mr. Gholamreza Amini, the respected CEO of Rahkav Road South Company, who investing in the development of a LiDAR mobile mapping system with SLAM capability, has been able to gather complete and valuable data from several villages in Fars province with the help of Mr. Payam Shokarzadeh.

PY - 2023/1/14

Y1 - 2023/1/14

N2 - Installing targets and measuring them as ground control points (GCPs) are time consuming and cost inefficient tasks in a UAV photogrammetry project. This research aims to automatically extract GCPs from 3D LiDAR mobile mapping system (L-MMS) measurements and UAV imagery to perform aerial triangulation in a UAV photogrammetric network. The L-MMS allows to acquire 3D point cloudsof an urban environment including floors and facades of buildings with an accuracy of a few centimetres. Integration of UAV imagery, as complementary information enables to reduce the measurement time as well as increasing the automation of the production line. Therefore, a higher quality measurements and more diverse products are obtained. This research hypothesises that the spatial accuracy of the L-MMS is higher than that of the UAV photogrammetric point clouds. The tie points are extracted from the UAV imagery based on the well-known SIFT method, and then matched. The structure from motion (SfM) algorithm is applied to estimate the 3D object coordinates of the matched tie points. Rigid registration is carried out between the point clouds obtained from the L-MMS and the SfM. For each tie point extracted from the SfM point clouds, a plane is fitted to their corresponding neighbouring points that are selectedfrom the L-MMS point clouds. The re-projection error of the analyses carried out on a test data set of the Glian area in Iran that show a half pixel size accuracy standing for a few centimetres range accuracy. Finally, a significant increasing of speed up in survey operations besides improving the spatial accuracy of the extracted GCPs are achieved.

AB - Installing targets and measuring them as ground control points (GCPs) are time consuming and cost inefficient tasks in a UAV photogrammetry project. This research aims to automatically extract GCPs from 3D LiDAR mobile mapping system (L-MMS) measurements and UAV imagery to perform aerial triangulation in a UAV photogrammetric network. The L-MMS allows to acquire 3D point cloudsof an urban environment including floors and facades of buildings with an accuracy of a few centimetres. Integration of UAV imagery, as complementary information enables to reduce the measurement time as well as increasing the automation of the production line. Therefore, a higher quality measurements and more diverse products are obtained. This research hypothesises that the spatial accuracy of the L-MMS is higher than that of the UAV photogrammetric point clouds. The tie points are extracted from the UAV imagery based on the well-known SIFT method, and then matched. The structure from motion (SfM) algorithm is applied to estimate the 3D object coordinates of the matched tie points. Rigid registration is carried out between the point clouds obtained from the L-MMS and the SfM. For each tie point extracted from the SfM point clouds, a plane is fitted to their corresponding neighbouring points that are selectedfrom the L-MMS point clouds. The re-projection error of the analyses carried out on a test data set of the Glian area in Iran that show a half pixel size accuracy standing for a few centimetres range accuracy. Finally, a significant increasing of speed up in survey operations besides improving the spatial accuracy of the extracted GCPs are achieved.

KW - Ground Control Points

KW - LiDAR Mobile Mapping

KW - UAV photogrammetry

KW - Sparse Bundle Adjustment

KW - Aerial Triangulation

KW - Aerial triangulation

KW - Registration

KW - UAV Imagery

KW - Control Points

UR - http://www.scopus.com/inward/record.url?scp=85146945736&partnerID=8YFLogxK

U2 - 10.5194/isprs-annals-X-4-W1-2022-581-2023

DO - 10.5194/isprs-annals-X-4-W1-2022-581-2023

M3 - Conference article

VL - 10

SP - 581

EP - 588

JO - ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences

JF - ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences

SN - 2194-9042

IS - 4/W1-2022

T2 - 6th SMPR and 4th GIResearch, ISPRS Geospatial Conference

Y2 - 19 February 2023 through 22 February 2023

ER -