Semi-automated Mapping Research Articles

Impact of discontinuity data acquisition methods on rockfall susceptibility assessment using high-resolution 3D point cloud

This research evaluates the influence of various discontinuity data acquisition methods on three-dimensional rockfall susceptibility assessments, employing a high-resolution 3D point cloud of the Špičunak rock slope in Croatia. Discontinuity mapping was conducted utilising manual and semi-automated methods. Manual mapping was done in open-source software CloudCompare, while semi-automated mapping was done using Discontinuity Set Extractor and two CloudCompare plug-ins, qFacet Fast Marching and qFacet Kd-Tree algorithm. Significant differences were observed between the methods in terms of the number of identified discontinuity planes, sets, mean orientation values, and weighted densities associated with specific sets. Based on the mapping results, three-dimensional rockfall susceptibility maps were generated. The 3D rockfall susceptibility assessment employed a Kinematic Hazard Index (KHI) for planar, wedge, and flexural toppling failure mechanisms, which determines the percentage of discontinuity planes that meet the geometrical conditions specific to each type of failure. The findings underscore that the mapping results greatly affect the 3D rockfall susceptibility assessment, impacting the identification of potential rockfall source areas. The study emphasizes the importance of integrating manual and semi-automated mapping for reliable 3D rockfall susceptibility assessment. Additionally, this study evaluated the effect of varying the number of discontinuity orientation input data on rockfall susceptibility by comparing nine scenarios, each involving a reduction in the number of discontinuity orientation data. The results indicate that accurate discontinuity mapping is more critical than the sheer number of mapped discontinuities for reliable rockfall susceptibility assessment. Therefore, prioritizing the precise determination of discontinuity set numbers and their associated weighted densities is essential for reliable susceptibility evaluations.

Problem-based learning and the integration of sustainable development goals

PurposeThis study explores how problem-based learning (PBL) programs can address Sustainable Development Goals (SDGs) via the higher education (HE) curriculum, teaching materials and relevant assessments, supporting learning at scale for HE institutions.Design/methodology/approachEmploying SDGs and their indicators as the coding framework, our two-phase study evaluates the curriculum and teaching materials of seven PBL programs at a leading higher education institution (HEI). The first phase involved a content analysis to assess the degree of sustainability integration in 156 relevant courses. The second phase applied a semi-automated mapping protocol to analyze learning and teaching materials in 120 relevant courses.FindingsThe school aligns with 17 SDGs (100%), covering 94 indicators (55.62%). On average, each program within the school addresses over ten of these goals and incorporates more than 24 associated indicators. However, the study reveals an imbalance in the incorporation of SDGs, with some goals not yet deeply and comprehensively embedded in the curriculum. While there is a substantial focus on sustainability theories, the practical implications of SDGs in emerging countries, particularly through case studies and assessments, require significant enhancement.Practical implicationsMapping SDGs allows HEIs to identify strengths and gaps in SDG integration, thereby improving the PBL approach to enhance student work readiness in sustainability-focused careers.Originality/valueThrough the lens of transformative learning theory, this study provides evidence of SDG integration into PBL curricula. It highlights a mapping methodology that enables HEIs to evaluate their sustainability readiness in curriculum, teaching materials and relevant assessments.

Giving gully detection a HAND – Testing the scalability and transferability of a semi-automated object-orientated approach to map permanent gullies

Gully erosion can incur on- and off-site impacts with severe environmental and socio-economic consequences. Semi-automated mapping provides a means to map gullies systematically and without bias, providing information on their location and extent. If used temporally, semi-automated mapping can be used to quantify soil loss and identify soil loss source areas. The information can be used to identify mitigation strategies and test the efficacy thereof. We develop, describe, and test a novel semi-automated mapping workflow, gHAND, based on the distinct topographic landform features of a gully to enhance transferability to different climatic regions. Firstly, topographic heights of a Digital Elevation Model are normalised with reference to the gully channel thalweg to extract gully floor elements, and secondly, slope are calculated along the direction of flow to determine gully wall elements. As the gHAND workflow eliminates the need to define kernel thresholds that are sensitive towards gully size, it is more scalable than kernel-based methods. The workflow is rigorously tested at different gully geomorphic scales, in contrasting geo-environments, and compared to benchmark methods explicitly developed for region-specific gullies. Performance is similar to benchmark methods (variance between 1.4 % and 14.8 %). Regarding scalability, gHAND produced under- and over-estimation errors below 30.6 % and 16.1 % for gullies with planimetric areas varying between 1421.6 m2 and 355403.7 m2, without editing the workflow. Although the gHAND workflow has limitations, most markedly the requirement of manually digitising gully headcuts, it shows potential to be further developed to reliably map gullies of small- to large-scales in different geo-environments.

The geomorphology of Ireland’s continental shelf

ABSTRACT The Irish Shelf Seabed Geomorphological Map (ISSGM) (v2023) presented here, is the first high-resolution geomorphological map of the entire Irish continental shelf. This large-scale mapping exercise took advantage of the vast INFOMAR multibeam echosounder dataset, and used a protocol of semi-automated mapping techniques to accurately and rapidly extract seabed features. All previous mapping efforts and existing literature on the Irish shallow shelf geomorphology have also been collated and integrated in the map, critically evaluating the previous interpretations. An internationally standardised classification scheme was adopted, aligning the ISSGM (v2023) to other international geomorphological work. At a national level, this detailed geomorphological digital map is intended primarily as a resource to better inform multiple offshore activities and management of the marine environment. The map also acts as a baseline for future studies in marine geomorphology, as it identifies gaps in the knowledge and highlights areas of contentious interpretation that require further work. The map is available online on the Irish Marine Atlas (https://atlas.marine.ie – Geology Theme).

DeepMapScaler: a workflow of deep neural networks for the generation of generalised maps

ABSTRACT The automation of map generalization has been an important research subject for decades but is not fully solved yet. Deep learning techniques are designed for various image generation tasks, so one may think that it would be possible to apply these techniques to cartography and train a holistic model for end-to-end map generalization. On the contrary, we assume that map generalization is a task too complex to be learnt with a unique model. Thus, in this article, we propose to resort to past research on map generalization and to separate map generalization into simpler sub-tasks, each of which can be more easily resolved by a deep neural network. Our main contribution is a workflow of deep models, called DeepMapScaler, which achieves a step-by-step topographic map generalization from detailed topographic data. First, we implement this workflow to generalize topographic maps containing roads, buildings, and rivers at a medium scale (1:50k) from a detailed dataset. The results of each step are quantitatively and visually evaluated. Then the generalized images are compared with the generalization performed using a holistic model for an end-to-end map generalization and a traditional semi-automatic map generalization process. The experiment shows that the workflow approach is more promising than the holistic model, as each sub-task is specialized and fine-tuned accordingly. However, the results still do not reach the quality level of the semi-automatic traditional map generalization process, as some sub-tasks are more complex to handle with neural networks.

Semiautomatic Mapping of Center Pivot Irrigated Areas Using Sentinel-2 Images and GEOBIA Approach

Image analysis and feature extraction of remoted sensing data are significant for mapping irrigated agriculture areas as a source of information to improve water management and agricultural planning. This paper presents an image segmented base approach GEOBIA (Geographic Object-Based Image Analysis) to extract irrigated areas by Center Pivot Irrigation System (CPIS). This study suggests a semi-automated recognition of circular patterns for the mapping of irrigated regions by center pivots, using Sentinel -2 MSI images, 10 meters spatial resolution. A set of images from different seasons, humid and dry are used to maximize de CPIS’s occurrence. A multiresolution segmentation method was applied, and a large number of segment-based shape features was extracted and used as input to a feature selection procedure (shape descriptors: Area; Compactness; Circularity Factor; Length/Width; Radius of smallest enclosing ellipse; and Roundness). In addition, another shape descriptor “Circularity Factor” was developed in this research and played an important role during preliminaries classification processes. The accuracy assessment of preliminaries classifications has validated used the Circularity Factor together with the other chosen shape descriptors to reach better results to CPIS’s detection. Furthermore, 86.23% of the CPIS mapped in the classification process is in accordance with the ground truth map. This methodology can be used to map large areas in a relatively short time and provides a tool for monitoring irrigated areas.

Semi-automatic mapping of shallow landslides using free Sentinel-2 images and Google Earth Engine

Abstract. The global availability of Sentinel-2 data and the widespread coverage of cost-free and high-resolution images nowadays give opportunities to map, at a low cost, shallow landslides triggered by extreme events (e.g. rainfall, earthquakes). Rapid and low-cost shallow landslide mapping could improve damage estimations, susceptibility models and land management. This work presents a two-phase procedure to detect and map shallow landslides. The first is a semi-automatic methodology allowing for mapping potential shallow landslides (PLs) using Sentinel-2 images. The PL aims to detect the most affected areas and to focus on them an high-resolution mapping and further investigations. We create a GIS-based and user-friendly methodology to extract PL based on pre- and post-event normalised difference vegetation index (NDVI) variation and geomorphological filtering. In the second phase, the semi-automatic inventory was compared with a benchmark landslide inventory drawn on high-resolution images. We also used Google Earth Engine scripts to extract the NDVI time series and to make a multi-temporal analysis. We apply this procedure to two study areas in NW Italy, hit in 2016 and 2019 by extreme rainfall events. The results show that the semi-automatic mapping based on Sentinel-2 allows for detecting the majority of shallow landslides larger than satellite ground pixel (100 m2). PL density and distribution match well with the benchmark. However, the false positives (30 % to 50 % of cases) are challenging to filter, especially when they correspond to riverbank erosions or cultivated land.

Differential impact of isolated topographic bumps on ice sheet flow and subglacial processes

Abstract. Topographic highs (“bumps”) across glaciated landscapes have the potential to temporarily slow ice sheet flow or, conversely, accelerate ice flow through subglacial strain heating and meltwater production. Isolated bumps of variable size across the deglaciated landscape of the Cordilleran Ice Sheet (CIS) of Washington State present an opportunity to study the influence of topographic highs on ice–bed interactions and ice flow organization. This work utilizes semi-automatic mapping techniques of subglacial bedforms to characterize the morphology of streamlined subglacial bedforms including elongation, surface relief, and orientation, all of which provide insight into subglacial processes during post-Last Glacial Maximum deglaciation. We identify a bump-size threshold of several cubic kilometers – around 4.5 km3 – in which bumps larger than this size will consistently and significantly disrupt both ice flow organization and subglacial sedimentary processes, which are fundamental to the genesis of streamlined subglacial bedforms. Additionally, sedimentary processes are persistent and well developed downstream of bumps, as reflected by enhanced bedform elongation and reduced surface relief, likely due to increased availability and production of subglacial sediment and meltwater. While isolated topography plays a role in disrupting ice flow, larger bumps have a greater disruption to ice flow organization, while bumps below the identified threshold seem to have little effect on ice and subglacial processes. The variable influence of isolated topographic bumps on ice flow of the CIS has significant implications for outlet glaciers of the Greenland Ice Sheet (GrIS) due to similarities in regional topography, where local bumps are largely unresolved.

Exploring the Use of Orthophotos in Google Earth Engine for Very High-Resolution Mapping of Impervious Surfaces: A Data Fusion Approach in Wuppertal, Germany

Germany aims to reduce soil sealing to under 30 hectares per day by 2030 to address negative environmental impacts from the expansion of impervious surfaces. As cities adapt to climate change, spatially explicit very high-resolution information about the distribution of impervious surfaces is becoming increasingly important for urban planning and decision-making. This study proposes a method for mapping impervious surfaces in Google Earth Engine (GEE) using a data fusion approach of 0.9 m colour-infrared true orthophotos, digital elevation models, and vector data. We conducted a pixel-based random forest (RF) classification utilizing spectral indices, Grey-Level Co-occurrence Matrix texture features, and topographic features. Impervious surfaces were mapped with 0.9 m precision resulting in an Overall Accuracy of 92.31% and Kappa-Coefficient of 84.62%. To address challenges posed by high-resolution imagery, we superimposed the RF classification results with land use data from Germany’s Authoritative Real Estate Cadastre Information System (ALKIS). The results show that 25.26% of the city of Wuppertal is covered by impervious surfaces coinciding with a government-funded study from 2020 based on Sentinel-2 Copernicus data that defined a proportion of 25.22% as built-up area. This demonstrates the effectiveness of our method for semi-automated mapping of impervious surfaces in GEE to support urban planning on a local to regional scale.

Exploratory Mapping of Blue Ice Regions in Antarctica Using Very High-Resolution Satellite Remote Sensing Data

Mapping spatiotemporal changes in the distribution of blue ice regions (BIRs) in Antarctica requires repeated, precise, and high-resolution baseline maps of the blue ice extent. This study demonstrated the design and application of a newly-developed semi-automatic method to map BIRs in the Antarctic environment using very high-resolution (VHR) WorldView-2 (WV-2) satellite images. We discussed the potential of VHR satellite data for the mapping of BIRs in the Antarctic environment using a customized normalized-difference blue-ice index (NDBI) method devised using yellow, green, and near-infrared spectral bands of WV-2 data. We compared the viability of the newly developed customized NDBI approach against state-of-the-art target detection (TD), spectral processing (SP) and pixel-wise supervised (PSC) feature extraction (FE) approaches. Four semi-automatic FE approaches (three existing plus one newly developed) consisting of 16 standalone FE methods (12 existing + four customized) were evaluated using an extensive quantitative and comparative assessment for mapping BIRs in the vicinity of Schirmacher Oasis, on the continental Antarctic coastline. The results suggested that the customized NDBI approach gave a superior performance and the highest statistical stability when compared with existing FE techniques. The customized NDBI generally rendered the lowest level of misclassification (average RMSE = 654.48 ± 58.26 m2), followed by TD (average RMSE = 987.81 ± 55.05 m2), SP (average RMSE = 1327.09 ± 127.83 m2) and PSC (average RMSE = 2259.43 ± 115.36 m2) for mapping BIRs. Our results indicated that the use of the customized NDBI approach can greatly improve the semi-automatic mapping of BIRs in the Antarctic environment. This study presents the first refined map of distribution of BIRs around the Schirmacher Oasis. The total area of blue ice in the study area was estimated to be 106.875 km2, approximately 61% of the study area. The WV-2 derived BIR map area presented in this study locally refined the existing BIR map derived using Landsat Enhanced Thematic Mapper Plus (ETM+) and the Moderate Resolution Imaging Spectroradiometer (MODIS)-based mosaic of Antarctica (MOA) dataset by ~31% (~33.40 km2). Finally, we discussed the practical challenges and future directions in mapping BIRs across Antarctica.

Detection of geometric properties of discontinuities on the Špičunak rock slope (Croatia) using high-resolution 3D Point Cloud generated from Terrestrial Laser Scanning

Rock mass characterization is a very important part of engineering geological investigation. For a better understanding of the rock mass behaviour, it is crucially important to obtain as much as possible information about the discontinuity network, especially about orientation and the number of dominant discontinuity sets. The traditional methodology includes field mapping which dominantly produces a limited amount of data and consequently only a rough estimate about discontinuity network. To increase the number of measurements and to eliminate orientation bias, rock mass on the Špičunak rock slope in Gorski kotar, Croatia, was analysed using a combination of 3D Point Cloud and Textured Mesh Model generated from 3D Point Cloud by Poisson surface reconstruction. Both models were obtained from Terrestrial Laser Scanning. Two considerably different parts of a rock slope, with different weathering conditions and different degrees of fracturing were mapped. Discontinuities were mapped in the field and on the models using manual mapping techniques and semi-automated methods. Manual mapping on a 3D Point Cloud and Textured Mesh Model was done by Compass plugin and by Trace a polyline tool in Cloud Compare software version V2.12 and semi-automated mapping methods were done by Discontinuity Set Extractor and qFacet Fast Marching plugin for Cloud Compare software version V2.12. This study was used to show how the application of different methodologies, for the detection of geometric properties of discontinuities, influences the result. Statistical analyses were performed on the collected data to determine differences in the accuracy between the mapping techniques. Manual mapping on the 3D Point Cloud and high-resolution Textured Mesh Model showed good agreement with field measurements, apart from the higher number of discontinuities mapped by remote sensing methods. On the other hand, significant deviations were found between manual and semi-automated mapping techniques. Semiautomated methods did not correctly detect certain discontinuities, especially bedding planes that are perpendicular to a rock face. Also, semi-automated methods overestimate the number of discontinuity sets, especially in a highly weathered and highly fractured rock mass. These differences between methods can influence kinematic analysis results. Based on the results, an appropriate methodology was proposed to utilize the advantages of both manual and semiautomated methods. The proposed approach presents a powerful tool to accurately map and measure discontinuity orientation with results comparable to the field measurements.

A semi-automated, GIS-based framework for the mapping of supraglacial hydrology

AbstractSupraglacial drainage networks play an integral role in both glacier dynamics and run-off timing, and mapping them provides insight into their role in glacial systems. Here we present a reproducible approach for semi-automated mapping of supraglacial hydrologic features, which complements existing work in automated and manual mapping by providing clear definitions for identification of features. This framework uses a digital terrain model (DTM) to identify potential flow routes on the glacier surface, which are then classified using a set of standardized rules based on the DTM and an orthomosaic. We found that the normalized difference water index calculated from digital imagery was influenced by image brightness and introduce a new approach using average RGB values to correct for this. Using this framework we mapped supraglacial drainage networks at Nàłùdäy and Thores Glacier, Canada. The framework was easier to implement with high-resolution (0.5 m) imagery and DTMs, compared to data with lower resolution (10 m), due to the increased detail in topography and feature boundaries at high-resolution. Lower-resolution data captured larger streams (>2 pixels wide), however, indicating that the framework can still be used at this resolution. Mapping supraglacial hydrology using standardized methods opens possibilities for investigating many questions relating to changes in supraglacial hydrology over time.

Semi-automated mapping of occluded arterial segments in acute large vessel stroke from computed tomography angiography

Catheterisation of occluded artery is the most crucial step in the mechanical thrombectomy of large vessel occlusions. Being a blind procedure, potential major untoward events could be anticipated at this stage. In this study, we evaluated the feasibility of reconstruction of the occluded vascular segment from CT angiography, exploiting the attenuation difference between the clot and adjacent brain parenchyma. Twenty-five patients with large vessel occlusion who achieved TICI2B/3 recanalization were identified. The semi-automated reconstruction was done using an open-source 3D segmentation software by two observers. The generated arterial anatomy was categorized as congruent, if all the major arterial segments namely, internal carotid artery, M1 middle cerebral artery, bifurcation, and major divisions matched with post thrombectomy angiograms. The discrepancy of one or more than one arterial segment was classified as mild or total mismatch respectively. Congruent arterial mapping was possible in 88% and 92 % patients for observer 1 and observer 2 respectively, while mild mismatch was noted in two patients for both the observers. Mismatch mostly occurred in superior division for both observers(100% vs 66.6%). The interrater agreement was good (0.77) and the accuracy was not influenced by the length of the clot. The median time for reconstruction was 4 minutes for both the observers (p - 0.21). Delineation of the anatomy of the occluded major intracranial artery is possible and corresponds with the actual anatomy. It could be used as a guide during thrombectomy procedures.

A tool for mapping microglial morphology, morphOMICs, reveals brain-region and sex-dependent phenotypes

Environmental cues influence the highly dynamic morphology of microglia. Strategies to characterize these changes usually involve user-selected morphometric features, which preclude the identification of a spectrum of context-dependent morphological phenotypes. Here we develop MorphOMICs, a topological data analysis approach, which enables semiautomatic mapping of microglial morphology into an atlas of cue-dependent phenotypes and overcomes feature-selection biases and biological variability. We extract spatially heterogeneous and sexually dimorphic morphological phenotypes for seven adult mouse brain regions. This sex-specific phenotype declines with maturation but increases over the disease trajectories in two neurodegeneration mouse models, with females showing a faster morphological shift in affected brain regions. Remarkably, microglia morphologies reflect an adaptation upon repeated exposure to ketamine anesthesia and do not recover to control morphologies. Finally, we demonstrate that both long primary processes and short terminal processes provide distinct insights to morphological phenotypes. MorphOMICs opens a new perspective to characterize microglial morphology.

A Novel Model for the Semantic Enrichment of an Ontology Alignment System

In many applications, ontology alignment is a difficult challenge, and it is a major concern for interoperability and domain specialists in information systems. Although there are various methods for ontology alignment, most of them ignore ontological links such as subsumption and aggregation. Furthermore, traditional alignment methods provide little or no information about the underlying structure of the correspondences between ideas that they identify, limiting them to basic links between matched concepts. However, many actions, such as ontology mergers, ontology evolution, or data conversion, require more detailed information, such as the actual relationship type of correspondences matches or information about the cardinality of a correspondence (one-to-one or one-to-many). We employed an enrichment technique to build an upgrade to the present ontology alignment tool (Falcon AO++) that recognizes and adds more semantic information to a created ontology mapping in this study. The improved mapping now supports equal, is-a, inverse is-a, part-of, has-a, and related semantic connection types. To enable semi-automated mapping to correct and detect more sorts of correspondences, the enrichment technique leverages a variety of linguistic, structural, and background knowledge. As an outcome, more expressive mappings may be created. In terms of precision, recall, and f-measure, Falcon-AO++ and eFalcon-AO perform better by 18.1 percent, 20.2 percent, and 18.6 percent, respectively.

Mapping of ICD-O Tuples to OncoTree Codes Using SNOMED CT Post-Coordination.

Around 500,000 oncological diseases are diagnosed in Germany every year which are documented using the International Classification of Diseases for Oncology (ICD-O). Apart from this, another classification for oncology, OncoTree, is often used for the integration of new research findings in oncology. For this purpose, a semi-automatic mapping of ICD-O tuples to OncoTree codes was developed. The implementation uses a FHIR terminology server, pre-coordinated or post-coordinated SNOMED CT expressions, and subsumption testing. Various validations have been applied. The results were compared with reference data of scientific papers and manually evaluated by a senior pathologist, confirming the applicability of SNOMED CT in general and its post-coordinated expressions in particular as a viable intermediate mapping step. Resulting in an agreement of 84,00 % between the newly developed approach and the manual mapping, it becomes obvious that the present approach has the potential to be used in everyday medical practice.

Semi-Automatic Mapping Technique Using Snowballing to Support Massive Literature Searches in Software Engineering

Systematic literature reviews represent an important methodology in Evidence-Based Software Engineering. To define the methodological route in these type of studies, in which a review of quantitative and qualitative aspects of primary studies is carried out to summarize the existing information regarding a particular topic, researchers use protocols that guide the construction of knowledge from research questions. This article presents a process that uses forward Snowballing, which identifies the articles cited in the paper under study and the number of citations as inclusion criteria to complement systematic literature reviews. A process that relies on software tools was designed to apply the Snowballing strategy and to identify the most cited works and those who cite them. To validate the process, a review identified in the literature was used. After comparing the results, new works that were not taken into account but made contributions to the subject of study emerged. The citation index represents the number of times a publication has been referenced in other documents and is used as a mechanism to analyze, measure, or quantitatively assess the impact of said publication on the scientific community. The present study showed how applying Snowballing along with other strategies enables the emergence of works that may be relevant for an investigation given the citations rate. That is, implementing this proposal will allow updating or expanding systematic literature studies through the new works evidenced.

Semi-Automated Mapping of Complex-Terrain Mountain Glaciers by Integrating L-Band SAR Amplitude and Interferometric Coherence

Mapping the outlines of glaciers has primarily relied on the interpretation of satellite optical images. However, the accurate delineation of glaciers in complex terrain mountain regions remains challenging, mainly because the supraglacial debris-covered ablation zones and snow-covered accumulation zones often exhibit the same spectral properties as their adjacent grounds in optical images. This study presents a novel approach by exploring both the satellite synthetic aperture radar (SAR) amplitude and interferometric coherence to map mountain glaciers. This method explores the deviation of the glacier surface signal in the SAR time series to distinguish glacier ice from the surrounding stable ground. To this end, we explored the classifying capabilities of two indices from a set of SAR images, SAR interferometric coherence and amplitude deviation index (ADI), to determine glacier boundary. We found that the two indices complement each other for mapping glaciers. A ratio map based on ADI and SAR coherence (ACR) was then derived, from which the glacier outline was automatically tracked using a specified threshold, followed by manual modification. We validated this approach on two typical valley glaciers, the debris-covered Hailuogou Glacier and debris-free Mozigou Glacier, in Mount Gongga in the southeastern Tibetan Plateau. The results show that the proposed ACR criteria can significantly enhance the contrast between glaciers and their surroundings. By comparing our results with manually delineated glacier outlines from high-resolution cloud-free satellite optical imagery, we found that the misclassification rate and difference rate for our results were 2.6% and 4.2%, respectively. The approach presented in this study can be easily adapted to map the outlines of mountain glaciers worldwide efficiently and is useful for inferring glacier boundary changes in a climate warming context.

Classification of underwater photogrammetry data for temperate benthic rocky reef mapping

The fine characterization of the substrate is a baseline to thoroughly investigate the relations between organisms and their biotopes. Cutting edge spatial technologies now provide access to accurate information on biotopes and biocenoses both in terrestrial and in marine environments. Photogrammetry is one of them and has recently been applied in submarine environments especially in shallow clear water. In this study, we investigated the potential of photogrammetry to characterise benthic habitats in turbid environments. Although more challenging, turbid environments are more frequent in temperate marine coastal areas. We selected two rocky sites in the bay of Saint-Malo (Brittany, France), differentiated by their level of turbidity, one being a marine site exposed to natural tides (Buharats), while the other (Bizeux) is subjected to both natural tides and artificial currents created by the functioning of a hydroelectric dam. The different substrates observed were classified into eight classes at a centimetre resolution using photogrammetry-based spatial and multispectral predictors. The spatial benthic terrain predictors were derived from a digital surface model (DSM) at various spatial scales, and the multispectral predictors were retrieved from the red-green-blue (RGB, natural colours) orthomosaic imagery. An overall classification was computed for Buharats and Bizeux, with accuracies of 84.76% and 79.54% respectively, revealing a good quality of the substrate classification. The combination of RGB, DSM, and several spatial benthic terrain variables, with a pixel resolution of 5 and 10 mm, and a kernel size of 30, 60 and 90 pixels leads to the best benthic substrate classification (highest overall accuracy). At the class scale, producer's (PA) and user's (UA) accuracy showed that big boulders and field material were correctly distinguished. Small boulders and cobbles, having similar sizes, showed the lowest classification performances. This classification methodology provides new perspectives for mesoscale (100 m2 to 1 km2) semi-automatic mapping of the fine resolution (1 cm) relationship between benthic organisms and their substrate.

Coriolis effect recorded in Late Pleistocene Marine Isotope Stage 5e Bahamian aeolianites

Abstract The windward islands of the Lucayan Archipelago (Bahamas) form an Atlantic Ocean–facing transect spanning >950 km in length and 6° of latitude. The islands' topography is largely constructed from carbonate wind-blown dunes (i.e., aeolianites) deposited during the interglacial phases of the Late Pleistocene and Holocene. New digital elevation data from satellite radar interferometry (TanDEM-X German Earth observation satellite) enables a step change in the ability to map and quantify Bahamian aeolian landforms across the archipelago. A semi-automated mapping approach that leverages object-based image analysis yields a total aeolianite area of ~1674 km2 across Great Abaco, Eleuthera, Cat, San Salvador, Long, Crooked, Acklins, and Mayaguana islands (Bahamas) and the Turks and Caicos Islands. Longitudinal axis measurements from 747 Pleistocene parabolic dunes record increasing consistency of east-west orientation with decreasing latitude. Three U.S. National Data Buoy Center data buoys provided modern wind direction and velocity measurements (n = 730,933 of each) along this transect. Analysis of wind vectors (>P90 [90th percentile], n = 70,095) demonstrates increasing organization of easterlies at southern latitudes and an offset in directionality compared to formational winds of Pleistocene Marine Isotope Stage (MIS) 5e deposits. Southward trends of increasing wind strength and consistency reflect geostrophic flow driven by atmospheric circulation within the Hadley cell and right-hand deflection of the Coriolis effect in the Northern Hemisphere. We propose that the offset in directionality between dune axes and modern wind vectors is related to changes in latitudinal width of the Hadley cell from the Late Pleistocene (MIS 5e) to today. This data set is robust enough to serve as a benchmark against which future atmospheric circulation models can be compared.