Underwater photogrammetry is increasingly being used by marine ecologists because of its ability to produce accurate, spatially detailed, non-destructive measurements of benthic communities, coupled with affordability and ease of use. However, independent quality control, rigorous imaging system set-up, optimal geometry design and a strict modeling of the imaging process are essential to achieving a high degree of measurable accuracy and resolution. If a proper photogrammetric approach that enables the formal description of the propagation of measurement error and modeling uncertainties is not undertaken, statements regarding the statistical significance of the results are limited. In this paper, we tackle these critical topics, based on the experience gained in the Moorea Island Digital Ecosystem Avatar (IDEA) project, where we have developed a rigorous underwater photogrammetric pipeline for coral reef monitoring and change detection. Here, we discuss the need for a permanent, underwater geodetic network, which serves to define a temporally stable reference datum and a check for the time series of photogrammetrically derived three-dimensional (3D) models of the reef structure. We present a methodology to evaluate the suitability of several underwater camera systems for photogrammetric and multi-temporal monitoring purposes and stress the importance of camera network geometry to minimize the deformations of photogrammetrically derived 3D reef models. Finally, we incorporate the measurement and modeling uncertainties of the full photogrammetric process into a simple and flexible framework for detecting statistically significant changes among a time series of models.

Measurements derived from remote-sensing research and Held surveys have provided new ice-velocity data for David Glacier-Drygalski Ice Tongue and Priestley and Reeves Glaciers, Antarctica. Average surface velocities were determined by tracking crevasses and other patterns moving with the ice in two sequential satellite images. Velocity measurements were made for different time intervals (1973-90, 1990-92, etc.) using images from various satellite sensors (Landsat 1 MSS, Landsat TM, SPOT XS). in a study of the dynamics of David Glacier-Drygalski IceTongue and Priestley and Reeves Glaciers, global positioning system (GPS) measurements were made between 1989 and 1994. A number of points were measured on each glacier: five points on David Glacier, three on Drygalski Ice Tongue,two on Reeves Glacier—Nansen Ice Sheet and two on Priestley Glacier. (lomparison of the results from GPS data and feature-tracking in areas close to image tie-points shows that errors in measured average velocity from the feature-tracking may be as little as +15-20 m a⁻¹. in areas far from tie-points, such as the outer part of Drygalski Ice Tongue, comparison of the two types of measurements shows differences of about ± 70 m a⁻¹.

This paper discusses critical issues related to the reliability of topographic monitoring systems such as ATS (Automated Total Stations), GNSS (Global Navigation Satellite System) and Ground Based InSAR focusing the attention on controlling the stability of networks infrastructure, which have influence on data correction procedures but are often taken for granted, and on integrating results in GIS (Geographic Information System), under a common reference framework and with respect to open-access ancillary data. The novelty of the paper lies in the demonstration of the efficiency obtained by a proper implementation of the system. Discussion makes reference to an active landslide by using ATS, GNSS and Ground Based InSAR in continuous and periodic mod

Detecting the impacts of natural and anthropogenic disturbances that cause declines in organisms or changes in community composition has long been a focus of ecology. However, a tradeoff often exists between the spatial extent over which relevant data can be collected, and the resolution of those data. Recent advances in underwater photogrammetry, as well as computer vision and machine learning tools that employ artificial intelligence (AI), offer potential solutions with which to resolve this tradeoff. Here, we coupled a rigorous photogrammetric survey method with novel AI-assisted image segmentation software in order to quantify the impact of a coral bleaching event on a tropical reef, both at an ecologically meaningful spatial scale and with high spatial resolution. In addition to outlining our workflow, we highlight three key results: (1) dramatic changes in the three-dimensional surface areas of live and dead coral, as well as the ratio of live to dead colonies before and after bleaching; (2) a size-dependent pattern of mortality in bleached corals, where the largest corals were disproportionately affected, and (3) a significantly greater decline in the surface area of live coral, as revealed by our approximation of the 3D shape compared to the more standard planar area (2D) approach. The technique of photogrammetry allows us to turn 2D images into approximate 3D models in a flexible and efficient way. Increasing the resolution, accuracy, spatial extent, and efficiency with which we can quantify effects of disturbances will improve our ability to understand the ecological consequences that cascade from small to large scales, as well as allow more informed decisions to be made regarding the mitigation of undesired impacts.