Which Method for Which Purpose? A Comparison of Line Intercept Transect and Underwater Photogrammetry Methods for Coral Reef Surveys

Abstract

The choice of ecological monitoring methods and descriptors determines the effectiveness of a program designed to assess the state of coral reef ecosystems. Here, we comparer the relative performance of the traditional Line Intercept Transect (LIT) method with three methods derived from underwater photogrammetry: LIT on orthomosaics, photoquadrats from orthomosaics, and surface analyses on orthomosaics. The data were acquired at Reunion Island on five outer reef slopes and two coral communities on underwater lava-flows. Coral cover was estimated in situ using the LIT method and with LITs and photoquadrats digitized on orthomosaic. Surface analyses were done on the same orthomosaics. Structural complexity of the surveyed sites was calculated from digital elevation models using three physical descriptors (fractal dimension, slope, surface complexity), and used to explore their possible influence in coral cover estimates. We also compared the methods in terms of scientific outputs, the human expertise and time required. Coral cover estimates obtained with in situ LITs were higher than those obtained with digitized LITs and photoquadrats. Surfaces analyses on orthomosaics yielded the lowest but most the precise cover estimates (i.e., lowest sample dispersion). Sites with the highest coral cover also had the highest structural complexity. Finally, when we added scientific outputs, and requirements for human expertise and time to our comparisons between methods, we found that surface analysis on the orthomosaics was the most efficient method. Photoquadrats were more time-consuming than both in situ and digitized LITs, even though they provided coral cover estimates similar to those of digitized LITs and yielded more than one descriptor. The LIT in situ method remains the least time-consuming and most effective for species-level taxonomic identifications but is the most limited method in terms of data outputs and representativeness of the ecosystem.

Comparison of Standard Caribbean Coral Reef Monitoring Protocols and Underwater Digital Photogrammetry to Characterize Hard Coral Species Composition, Abundance and Cover

“…In terms of coral cover, our results are similar to the study of Urbina-Barreto et al (2021), where underwater photogrammetry provided significantly lower estimates on coral cover than the line intercept protocol. The average percentage of coral cover obtained by the UWP (c.a.…”

“…To our knowledge, at least six studies using underwater photogrammetry for coral reef monitoring have been published. The protocols mainly differ in the area sampled for analysis, ranging from 60 to 1,655 m 2 , but are similar in image acquisition procedure, cameras utilized, image processing algorithms, fieldwork environmental conditions during data collection (clear water, shallow sites), use of internal control points, and the colony data processing (Palma et al, 2017(Palma et al, , 2019Lechene et al, 2019;Hernández-Landa et al, 2020;Couch et al, 2021;Urbina-Barreto et al, 2021). UWP relies on the surface analysis of the benthic substrate, and obtained metrics seem to be biased by the area considered.…”

“…Results on comparisons between UWP and monitoring protocols to assess reefs characteristics obtained from sites in the Indian and Pacific ocean have been varied. Urbina-Barreto et al (2021) showed that the LIT overestimates coral cover in comparison to UWP. However, Couch et al (2021) observed a high consistency of data between UWP and field visual surveys.…”

Underwater photogrammetry reveals new links between coral reefscape traits and fishes that ensure key functions

“…In fact, the monitoring of a coral reef site usually requires a 1‐h dive using observer‐based methods (i.e., PIT, LIT, Chain and Tape method; see Hill & Wilkinson, 2004) to collect fine‐scale habitat characteristics. The data collected by underwater photogrammetry in the same time interval are standardized (i.e., no observer bias) and allow for computing multiple 2D and 3D habitat descriptors (Urbina‐Barreto, Garnier, et al, 2021b). As both data collection and curation are increasingly automated, indeed, remotely operated vehicles or autonomous underwater vehicles are already used to collect data (Ferrari et al, 2016; Friedman et al, 2012; Obura et al, 2019; Price et al, 2019), and analysis solutions based on open source code (Fukunaga et al, 2019; Urbina‐Barreto, Chiroleu, et al, 2021a) and artificial intelligence are increasingly being developed (e.g., González‐Rivero et al, 2020; Hopkinson et al, 2020; Mohamed et al, 2020).…”

Diver-generated photomosaics as a tool for monitoring temperate rocky reef ecosystems

“…For comparitive purposes this study only examined point count data within 1 m 2 quadrats, however the methodological approaches for data extraction from photomosaics are highly varied. In the case of community composition data, this could have also been collected across the length of our transects by hand-drawing polygons around various community catagories (Urbina-Barreto et al, 2021), or with the aid of machine learning classification algorithms (Mohamed et al, 2020;Ternon et al, 2022). This affords researchers the choice of selecting different data extraction method to best meet study aims as well as the ability to use the same underlying data set, but different methodological approaches for data extraction if new questions arise.…”