Area estimation methods in underwater video surveys: Biases, errors and their impacts on density estimates

Unmanned underwater vehicles (UUVs) are increasingly used for non-invasive data collection, with applications ranging from supporting fisheries stock assessment to biodiversity mapping. Estimating the area surveyed is crucial to calculate densities and abundances from observations. Area estimation methods range from utilising fixed transect dimensions, to advanced approaches that account for path deviations and intra-transect variability in field of view, often integrating multiple sensors or detailed bathymetric data. However, accuracy of position data from remote vehicles is limited by environmental and operational variability. Compounding these differences, researchers rarely fully document methodologies, preventing comparability between datasets. This paper develops a transferable methodology to process UUV position data, assessing the results of 2 width and 12 length estimation methods on estimated area surveyed. This analysis uniquely includes the calculation of associated error and resulting confidence intervals for each approach. Results show species density estimates can vary up to 13% depending on processing applied. The two equations used to calculate transect width cause significant differences between density estimates. Significant differences in transect length also occur depending on the degree and method of smoothing technique applied to position data. Importantly, these differences between methodologies are encompassed by the variance calculated from the position data. Recommendations to obtain representative transect areas are to validate width equations against laser measurements, use incremental position data and include depth when calculating total distance travelled. Due to variation in resulting density estimates across methods it is essential to include confidence intervals and full details of pre-filtering and smoothing procedures.