Next Article in Journal
Individual Tree Crown Segmentation in Two-Layered Dense Mixed Forests from UAV LiDAR Data
Previous Article in Journal
Applications of Unmanned Aerial Systems (UAS): A Delphi Study Projecting Future UAS Missions and Relevant Challenges
Previous Article in Special Issue
Estimating the Threshold of Detection on Tree Crown Defoliation Using Vegetation Indices from UAS Multispectral Imagery
 
 
Article

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

1
Engineering Department, University of Ferrara, via Saragat 1, 44122 Ferrara, Italy
2
AdriaRilievi, via Castel San Pietro 54, 48121 Ravenna, Italy
*
Author to whom correspondence should be addressed.
Received: 12 February 2020 / Revised: 16 March 2020 / Accepted: 27 March 2020 / Published: 30 March 2020
(This article belongs to the Special Issue Unmanned Aerial Vehicles in Geomatics)
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 Ground Control Points (GCPs), which are very time-consuming tasks. Direct georeferencing with high camera location accuracy due to on-board multi-frequency 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, we 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. View Full-Text
Keywords: coastal mapping; PPK; DTM; direct georeferencing; DJI Phantom 4 RTK; UAV coastal mapping; PPK; DTM; direct georeferencing; DJI Phantom 4 RTK; UAV
Show Figures

Figure 1

MDPI and ACS Style

Taddia, Y.; Stecchi, F.; Pellegrinelli, A. Coastal Mapping Using DJI Phantom 4 RTK in Post-Processing Kinematic Mode. Drones 2020, 4, 9. https://doi.org/10.3390/drones4020009

AMA Style

Taddia Y, Stecchi F, Pellegrinelli A. Coastal Mapping Using DJI Phantom 4 RTK in Post-Processing Kinematic Mode. Drones. 2020; 4(2):9. https://doi.org/10.3390/drones4020009

Chicago/Turabian Style

Taddia, Yuri, Francesco Stecchi, and Alberto Pellegrinelli. 2020. "Coastal Mapping Using DJI Phantom 4 RTK in Post-Processing Kinematic Mode" Drones 4, no. 2: 9. https://doi.org/10.3390/drones4020009

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop