Use Case_DJI Phantom4 RTK Drone in Topographical Survey in Saadiyat Lagoons District Enabling Works at Abu Dhabi, United Arab Emirates

Prepared by

Sanju Mathew, Sales Manager, Aeromotus Dubai (DJI Enterprise Drone Solution

Customer

GeoDrones Aerial Services, Dubai, United Arab Emirates

Aerial Image of the Area of Interest taken from Google Earth

Summary and Scope

GeoDrones Aerial Services were contracted to perform Drone-based Topographical Survey of the “Saadiyat Lagoons District Enabling Works” Project at Saadiyat Island, Abu Dhabi, United Arab Emirates. The total area of the project is 622 Hectares (6.22 sqkm) and using DJI’s Phantom4 RTK Drone, the topographical survey data capture was completed in just 3 days. All horizontal coordinates were referenced to WGS 84 UTM 40N. All vertical coordinates were referenced to local Abu Dhabi datum. GeoDrones were able to achieve 2cm GSD accuracy for the data capture and were able to deliver the processed data outputs such as OrthoMaps, Point Cloud, 3D Model using DJI Terra and additionally Point Cloud survey data in 2×2 m grid (ASCII), CAD file with delineation of features and details such as roads, mangrove areas, light posts, buildings, towers, water boundary, manholes, barriers, fences, gates, pedestrian pavements, bridges, shore protection, etc.

Summary / Findings from POC

Camera ModelPhantom 4 RTK
Area Covered622 Ha
Total Flight Time650 minutes
No of Images Captured11,219
Total Size of Raw Images89 GB

Survey Location

The location of the Survey Area is shown on Google Earth below. The KML of the Project boundary was created using coordinates provided by the client. The total area of the project is 622 Hectares (6.22 sqkm).

HSE

As this site is a live construction site, the POC team were provided with a safety briefing for the survey personnel. All survey operations were held away from people and over the space permitted by the GCAA and SBD and in favorable weather conditions. All HSE related measures were fully implemented during the entire survey.

Methodology

1. Pre – Survey

  • The mission plans were created using DJI’s GS RTK App on DJI Smart Controller.
  • The total project area is approx. 622 hectares. The entire area was divided into 4 parts viz. Part A, Part B, Part C and Part D as shown in the figure below.
    The flight altitude was set to 70m above ground.
  • The side overlap was set to 65% and front overlap was set to 75%.

2. Realtime Georeferencing at Site

  • Setting up D-RTK-2
  • DJI D-RTK2 Base Station was setup at 4 different points for each part.
  • The coordinates provided on site were as follows.
Pt Part Easting (m) Northing (m) Z (m)
1A 240738.251 2715642.131 01.01.41
2B 241901.596 2716140.233 01.01.87
3C 242539.287 2714990.261 01.02.05
4D 241744.300 2714105.369 01.03.16
5A 240889.792 2715561.828 01.01.90
6B 241610.667 2716001.361 0.929
7C 242478.952 2714583.717 01.01.87
8D 241922.728 2714251.512 01.03.73
  • The above coordinates were obtained using Municipality 4425 point as base point.
  • GeoDrones used Pt. 1,2,3 and 8 for D-RTK2 setup in Part A, B, C and D respectively.
  • The coordinates recorded by D-RTK2 base station at the 4 points were as follows.
Pt Part Latitude (dd) Longitude (dd) Altitude (Ell.Ht in m)
1A 24.53297324 54.44090817 -31.94607735
2B 24.53767251 54.45230393 -30.68410301
3C 24.52740566 54.45880513 -29.53209877
8D 24.52064782 54.45284978 -29.85610199

3. Phantom 4 RTK flights

  • High resolution RTK geotagged images were captured with 70% overlap covering entire area.
  • 11,219 RTK fixed images were acquired.
  • Total 26 flights were flown for topographic survey covering the entire project area.
  • Flight summary is shown below:
Part Flights Flight Distance (km)
A 747.51
B 753.34
C 642.46
D 640.35

4. Data Processing

  • Orthomosaic Generation using DJI Terra Software
  • The images were processed part by part using DJI Terra software.
  • High resolution orthomosaic images were generated in .tif format.
  • Used the following checkpoints to assess the positional accuracy of the generated orthomosaics. Following results were observed.
Pt Part E_GD (m) N_GD (m) E_CLIENT (m) N_CLIENT (m) dx dy
1D 241971.428 2713903.196 241971.401 2713903.202 0.027 -0.006
2C 243129.608 2714749.098 243129.568 2714749.113 0.040 -0.014
3B 241337.055 2716716.884 241337.093 2716716.843 -0.037 0.040
4B 241757.968 2716978.033 241758.006 2716977.990 -0.037 0.042
5A 240591.755 2715599.631 240591.741 2715599.698 0.014 -0.066
6A 240237.137 2715079.432 240237.134 2715079.487 0.003 -0.055
  • The differences we observed were less than 7cm in coordinates (Easting, Northing and Elevation)

Point Cloud, Digital Terrain Model (using Pix4D Mapper)

  • All Images were processed in Pix4D software for generation of 3D outputs viz. Classified Point Cloud, DTM, etc.
  • Classified Point Cloud in .las format was generated.
  • DTM was generated in .tif format.

Point Grid File (with 1m x 1m Grid) in ASCII format

  • 1m x 1m Grid for XYZ file was generated using Extract Values to Points tool in ArcGIS Pro.
  • Following was the method
    1. 1m Grid file generated using DSM of a part was loaded.
    2. DTM of that part was loaded.
    3. All the Points were given values of the raster cells of the DTM, which is stored as elevation.
  • After the values were extracted from the DTM, the table was then exported to ASCII .txt format using Export Feature Attribute to ASCII tool in ArcGIS Pro.
  • Following was the method
    1. The extracted table was selected as input.
    2. Raster Values were selected as Value field

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