Coastal Mapping using DJI Phantom 4 RTK in Post-Processing Kinematic Mode

Topographic and geomorphological surveys of coastal areas usually require the aerial mapping of long and narrow sections of littoral.

The georeferencing of photogrammetric models is generally based on the signalization and survey of GCPs (Ground Control Points) which are very time-consuming tasks.

Direct georeferencing with high camera location accuracy due to on-board multi-frequency Global Navigation Satellite System (GNSS) receivers can limit the need for GCPs.

Recently, DJI has made available the Phantom 4 Real-Time Kinematic (RTK) (DJI-P4RTK) which combines the versatility and the ease of use of previous DJI Phantom models with the advantages of a multi-frequency on-board GNSS receiver.

In this paper, the authors have investigated the accuracy of both photogrammetric models and Digital Terrain Models (DTMs) generated in Agisoft Metashape from two different image datasets (nadiral and oblique) acquired by a DJI-P4RTK.

Camera locations were computed with the Post-Processing Kinematic (PPK) of the Receiver Independent Exchange Format (RINEX) file recorded by the aircraft during flight missions. A Continuously Operating Reference Station (CORS) located at a 15 km distance from the site was used for this task.

The results highlighted that the oblique dataset produced very similar results, with GCPs (3D RMSE = 0.025 m) and without (3D RMSE = 0.028 m), while the nadiral dataset was affected more by the position and number of the GCPs (3D RMSE from 0.034 to 0.075 m).

The introduction of a few oblique images into the nadiral dataset without any GCP improved the vertical accuracy of the model (Up RMSE from 0.052 to 0.025 m) and can represent a solution to speed up the image acquisition of nadiral datasets for PPK with the DJI-P4RTK and no GCPs.

Moreover, the results of this research are compared to those obtained in RTK mode for the same datasets. The novelty of this research is the combination of a multitude of aspects regarding the DJI Phantom 4 RTK aircraft and the subsequent data processing strategies for assessing the quality of photogrammetric models, DTMs, and cross-section profiles.

Read more:

https://www.researchgate.net/publication/340328284_Coastal_Mapping_using_DJI_Phantom_4_RTK_in_Post-Processing_Kinematic_Mode

Utilizing Airborne LiDAR and UAV Photogrammetry Techniques in Local Geoid Model Determination and Validation

This investigation evaluates the performance of Digital Terrain Models (DTMs) generated in different vertical datums by aerial LiDAR and UAV (Unmanned Aerial Vehicle) photogrammetry techniques, for the determination and validation of local geoid models.

Many engineering projects require the point heights referring to a physical surface, i.e., geoid, rather than an ellipsoid. When a high-accuracy local geoid model is available in the study area, the physical heights are practically obtained with the transformation of Global Navigation Satellite System (GNSS) ellipsoidal heights of the points.

Besides the commonly used geodetic methods, this study introduces a novel approach for the determination and validation of the local geoid surface models using photogrammetry. The numeric tests were carried out in the Bergama region, in the west of Turkey. Using direct georeferenced airborne LiDAR and indirect georeferenced UAV photogrammetry-derived point clouds, DTMs were generated in ellipsoidal and geoidal vertical datums, respectively.

After this, the local geoid models were calculated as differences between the generated DTMs. Generated local geoid models in the grid and pointwise formats were tested and compared with the regional gravimetric geoid model (TG03) and a high-resolution global geoid model (EIGEN6C4), respectively. In conclusion, the applied approach provided sufficient performance for modeling and validating the geoid heights with centimeter-level accuracy. 

Read more at https://www.researchgate.net/publication/344146054_Utilizing_Airborne_LiDAR_and_UAV_Photogrammetry_Techniques_in_Local_Geoid_Model_Determination_and_Validation