DOI: 10.5061/dryad.6m905qg2p
title: Data from: Integrating a UAV-derived DEM in object-based image analysis increases habitat classification accuracy on coral reefs

description: Very shallow coral reefs (&lt; 5 m deep) are naturally exposed to
 strong sea surface temperature variations, UV radiation and other
 stressors exacerbated by climate change, raising great concern over their
 future. As such, accurate and ecologically informative coral reef maps are
 fundamental for their management and conservation. Since traditional
 mapping and monitoring methods fall short in very shallow habitats,
 shallow reefs are increasingly mapped with Unmanned Aerial Vehicles
 (UAVs). UAV-imagery is commonly processed with Structure-from-Motion (SfM)
 to create orthomosaics and Digital Elevation Models (DEMs) spanning
 several hundred metres. Techniques to convert these SfM products to
 ecologically relevant habitat maps are still relatively underdeveloped.
 Here we demonstrate that incorporating geomorphometric variables (the DEM
 and its derivatives) in addition to spectral information (the orthomosaic)
 can greatly enhance the accuracy of automatic habitat classification.
 Therefore, we mapped three very shallow reef areas off KAUST on the Saudi
 Arabian Red Sea coast with an RTK-ready UAV. Imagery was processed with
 SfM, and classified through Object-Based Image Analysis (OBIA). Within our
 OBIA workflow, we observed overall accuracy increases of up to 11% when
 training a Random Forest classifier on both spectral and geomorphometric
 variables as opposed to traditional methods that only use spectral
 information. Our work highlights the potential of incorporating a UAV’s
 DEM in OBIA for benthic habitat mapping, a promising but still scarcely
 exploited asset.
description: This dataset contains the Supplementary Data to:
   Nieuwenhuis, B.O.; Marchese, F.; Casartelli,
 M.; Sabino, A.; van der Meij, S.E.T.; Benzoni, F. 
 Integrating a UAV-Derived DEM in Object-Based Image Analysis
 Increases Habitat Classification Accuracy on Coral Reefs.
 Remote Sensing. 2022, 14, 5017  
 There are 4 datasets stored here. 
 Dataset 1. UAV orthomosaics and DEMs File
 folder with the UAV orthomosaics and DEMs as .tiff files.
 Orthomosaics and DEMs were constructed by processing DJI Phantom
 4 RTK images with the Structure-from-Motion Software Pix4D.
 The file folder also contains a README.txt file with further
 explanation. Dataset 2.
 Snorkel transect orthomosaics File folder with the
 orthomosaics of the snorkel transects as .tiff files.
 Orthomosaics were created from GoPro Hero 9 imagery processed
 with the Structure-from-Motion Software Agisoft Metashape.
 The file folder also contains a README.txt file with further
 explanation. Dataset 3.
 Habitat classifications File folder with the habitat
 classifications generated in eCognition as
 'shapefiles'. Please note that a shapefile
 consists of multiple files with the extensions: .shp, .shx, .dbf, .cpg,
 .prj, and .shp.xml. All these files should be kept in
 the same directory. The file folder also contains a
 README.txt file with further explanation. 
 Dataset 4. Manual classifications for accuracy
 assessment File folder with the manual
 classifications that were used for the accuracy assessment of the
 automatic classifications in Dataset 3. Manual
 classifications were constructed based on a on-screen interpretation of
 Dataset 1 and 2 and are stored as 'shapefiles'.
 Please note that a shapefile consists of multiple files with the
 extensions: .shp, .shx, and .dbf, .cpg, .prj, and .shp.xml.
 All these files should be kept in the same directory.
 The file folder also contains a README.txt file with further
 explanation.
description: GIS software is necessary to use and view the data. We advise the
 use of either ArcGis or QGIS (open-source).