Conventional Survey Methods Research Articles

Simplified Method for the Assessment of Siltation in Semiarid Reservoirs Using Satellite Imagery

The Brazilian semiarid region strongly depends on superficial reservoirs (one every 5 km 2 ) and hence is subject to the deleterious effects of siltation, which reduces water availability. This research proposed a method, simplified bathymetric surveying using remote sensing, for updating the morphological parameters of reservoirs. The study area was the Pentecoste reservoir (360 hm 3 ) in northeastern Brazil. The results were compared to the conventional bathymetric survey method, which demands more sampling points (235 compared to 1) and was assumed as reference. Siltation assessed through the proposed method was nearly twice as high as that observed through conventional surveys. The morphological parameters derived by both methods were used to assess the long-term water balance of the reservoir. The results show that the outflow diverged 30%, while the evaporated discharge and water availability diverged 10% between the methods. Therefore, in the conditions of the Brazilian semiarid region, the simplified method suffices to assess the water availability of reservoirs affected by silting.

Geo-Object-Based Soil Organic Matter Mapping Using Machine Learning Algorithms With Multi-Source Geo-Spatial Data

Soil is a complicated historical natural continuum that presents gradual changes in its properties and geographic area. Conventional soil survey and cartography methods on a macroscopic scale based on grids with a coarse resolution are inadequate for the rapid development of precision agriculture. The demand for soil mapping content and accuracy has increased as more convenient methods of acquiring multi-source geo-spatial data have been developed, and such data are commonly employed to extract basic mapping units and environmental variables in related algorithms. We employ geo-objects as basic units of soil property mapping, which are extracted from high-resolution remote sensing images using a convolutional neural network based learning algorithm. Multi-source geo-spatial data are transferred into each geo-object as environmental variables, and the relationships between soil properties and environmental variables are mined using powerful tree-based machine learning algorithms, including regressions with random forests and XGBoost. A data set that includes soil sample points and multi-source geo-spatial data is used to evaluate the effectiveness of the proposed method. The experimental results demonstrate that the method allows for better soil organic matter mapping than state-of-the-art interpolation-based and linear-regression-based methods. The proposed procedure has potential to be a general method for mapping other soil properties. Its advantages are embodied in the modeling of relatively miscellaneous data with implicitly associated non-linear relationships between soil properties and environmental variables. The spatial scale and accuracy of the finer maps capture more detailed characteristics of the soil properties and are applicable to the micro-domain fields required for refined soil mapping with small variations.

Insomnia severity index: a psychometric investigation among Saudi nurses.

Insomnia is the most prevalent sleep disorder, but it is widely untreated and under-diagnosed in Saudi Arabia. Moreover, no tool to screen insomnia has been validated in the Saudi population in general or nurses in particular. This study, therefore, assessed the psychometric validity of the Insomnia Severity Index (ISI) in Saudi nurses. A cross-sectional study with purposive sampling was performed with nurses (n= 134, age = 21-48years) from Al Majmaah, Saudi Arabia. Both conventional and online survey methods using the ISI, a brief measure of metacognition, and a socio-demographics questionnaire were employed. No ceiling or floor effects were found in the ISI total score (8.84 ± 5.07) or the factor scores, but the floor effect was found in the item scores. A two-factor model showed the best fit (Pclose .97, comparative fit index [CFI] 1.00, root mean square error of approximation [RMSEA] 0.00, non-significant χ2test, χ2/df 0.904). This model showed favorable configural, metric, scalar, and partial strict invariance across gender groups (CFI > .95, RMSEA < .05, χ2/df < 3, non-significant Δχ2, ΔCFI ≤ .01). The internal consistency was adequate (Cronbach's alpha = 0.75, 0.78 for the two factors of the ISI). The lack of correlations between the ISI scores and the scores of the brief measure of the metacognition favored its divergent validity. The ISI showed adequate psychometric validity for screening insomnia among Saudi nurses.

Twitter Analysis for Intelligent Transportation

Abstract The amount of data available online has grown enormously over the last decade as a result of the rapid growth of smartphone users and the availability of communication applications. Due to the anonymity and instantaneous nature of social media broadcasting compared to conventional attitudinal survey methods, social media mining is becoming popular for complementing traditional traffic detection methods due to its accessibility in reaching a large population and the opportunities for reflecting the true and immediate behaviour of participants for free. This study presents a framework for Arabic Twitter content analysis to gain transportation insight. The study is done with a dataset of more than 1 million tweets collected within 3 months. The proposed model comprises three main components: data acquisition, data analysis and the reverse geotagging scheme (RGS). The RGS tackles the problem of lack of location information in the tweets. Results show that 13% of the dataset reports traffic-related incidents with an overall precision of 55% and 87% for incidents identification prediction without and with reverse geotagging, respectively. This proves the efficiency of the developed analyser in identifying tweets on transportation and the potential of the RGS in defining the location of tweets with no registered location information.

Adaptation to climate change using indigenous weather forecasting systems in Borana pastoralists of southern Ethiopia

ABSTRACTIndigenous weather forecasting systems of Borana pastoralists are among the core elements of a Gada system that existed half a million years back and still serving as a powerful natural intelligence on adaptation to climatic hazards. The study was aimed to investigate the types of indigenous weather forecasting systems, mechanisms of climate information exchange, and how traditional forecasts have been integrated with contemporary forecasts to strengthen adaptation to climatic hazards in Borana pastoralists of southern Ethiopia. Conventional survey methods including participatory rural appraisal tools and factorial scoring technique were used for data collection and interpretation. This study indicated that four major indigenous weather forecasting systems were used by Borana pastoralists for centuries. These include Ayantu, Uchu, Waragu, and Arga-Dhageti. They varied in the kind of indicator used to predict weather events. Forecasting was mainly based on observation and unique analysis of celestial bodies, atmospheric variables, and biological features. Respondents indicated that Uchu and Ayantu systems were the most trusted and reliable sources of local climate information. Indigenous and contemporary forecasts are just different and could complement each other. Our results indicated that integrating indigenous and contemporary forecasting systems can foster the prediction efficiency and applicability of climate information. Borana pastoralists had established coping mechanisms that were performed in three phases: pre, during and post occurrence of predicted weather events; mainly aimed at improving their resilience to climatic shocks. Therefore, sustaining such sacred indigenous knowledge bank is vital, as it directly supports community-based disaster risk reduction programmes.

Using marine magnetic survey data to identify a gold ore-controlling fault: a case study in Sanshandao fault, eastern China

The Jiaodong Peninsula has the greatest concentration of gold ore in China and is characterized by altered tectonite-type gold ore deposits. This type of gold deposit is mainly formed in fracture zones and is strictly controlled by faults. Three major ore-controlling faults occur in the Jiaodong Peninsula—the Jiaojia, Zhaoping and Sanshandao faults; the former two are located on land and the latter is located near Sanshandao and its adjacent offshore area. The discovery of the world's largest marine gold deposit in northeastern Sanshandao indicates that the shallow offshore area has great potential for gold prospecting. However, as two ends of the Sanshandao fault extend to the Bohai Sea, conventional geological survey methods cannot determine the distribution of the fault and this is constraining the discovery of new gold deposits. To explore the southwestward extension of the Sanshandao fault, we performed a 1:25 000 scale marine magnetic survey in this region and obtained high-quality magnetic survey data covering 170 km2. Multi-scale edge detection and three-dimensional inversion of magnetic anomalies identify the characteristics of the southwestward extension of the Sanshandao fault and the three-dimensional distribution of the main lithologies, providing significant evidence for the deployment of marine gold deposit prospecting in the southern segment of the Sanshandao fault. Moreover, three other faults were identified in the study area and faults F2 and F4 are inferred as ore-controlling faults: there may exist other altered tectonite-type gold ore deposits along these two faults.

An analytical framework for estimating aquatic species density from environmental DNA.

Environmental DNA (eDNA) analysis of water samples is on the brink of becoming a standard monitoring method for aquatic species. This method has improved detection rates over conventional survey methods and thus has demonstrated effectiveness for estimation of site occupancy and species distribution. The frontier of eDNA applications, however, is to infer species density. Building upon previous studies, we present and assess a modeling approach that aims at inferring animal density from eDNA. The modeling combines eDNA and animal count data from a subset of sites to estimate species density (and associated uncertainties) at other sites where only eDNA data are available. As a proof of concept, we first perform a cross‐validation study using experimental data on carp in mesocosms. In these data, fish densities are known without error, which allows us to test the performance of the method with known data. We then evaluate the model using field data from a study on a stream salamander species to assess the potential of this method to work in natural settings, where density can never be known with absolute certainty. Two alternative distributions (Normal and Negative Binomial) to model variability in eDNA concentration data are assessed. Assessment based on the proof of concept data (carp) revealed that the Negative Binomial model provided much more accurate estimates than the model based on a Normal distribution, likely because eDNA data tend to be overdispersed. Greater imprecision was found when we applied the method to the field data, but the Negative Binomial model still provided useful density estimates. We call for further model development in this direction, as well as further research targeted at sampling design optimization. It will be important to assess these approaches on a broad range of study systems.

Do household surveys estimate tap water use accurately? Evidence from pressure-sensor based estimates in Coimbatore, India

Abstract Quantifying domestic water use at the household scale is crucial for any policy interventions towards ensuring adequate, equitable and safe water access. In developing country contexts, piped water supply is often one of several sources from which households access water and this is often unmetered. The most common approach to quantifying household water use from multiple sources is through household surveys. But there is no evidence that household surveys accurately estimate water use. This study utilized high-resolution pressure-sensor data as a reference to evaluate the effectiveness of conventional household survey methods through a sample of 82 households in Coimbatore city in South India. The pressure sensors produced detailed, continuous and accurate information on all sources of water accessed through the household storage infrastructure, but they were expensive and intrusive. Compared with pressure-sensor derived estimates of tap water use, household surveys alone fared very poorly. However, household surveys and well-designed water diaries of supply and pumping, coupled with simple one-time field measurements, emerged as a valid approach to quantifying household water use from taps under multiple source dependence.

Acquiring high-resolution topography and performing spatial analysis of loess landslides by using low-cost UAVs

The Loess Plateau is a region in China prone to frequent geological disasters, where thousands of loess landslides can be found. Conventional field survey methods are inadequate for the requirements of fine spatial analysis of landslides. Due to its numerous advantages (fast, efficient, low cost, safe, and able to acquire high-resolution data), structure from motion (SfM) technique to photogrammetric orientation of flights and modeling applied to photographs taken by unmanned aerial vehicles (UAVs) equipped with a camera has become a powerful new tool for the generation of high-resolution topography that has emerged in recent years, which has become a powerful new technique for acquiring high-resolution topographic data. In this study, we conducted nearly two months of field UAV surveys of loess landslides on the Loess Plateau, eventually established 3D digital models for 11 loess landslides, and produced high-resolution digital orthophoto maps (DOMs) and digital elevation models (DEMs). High-resolution spatial analysis of the loess landslides (mainly including characteristic parameter extraction, topography profile analysis, surface feature analysis, and hydrologic analysis) was performed using Agisoft PhotoScan, ArcGIS 10.2, Global Mapper 17, and Origin Pro 9.0. The UAV technique allows us to further understand the micro-level internal spatial and structural characteristics of loess landslides. Moreover, not only does it allow us to accurately measure the characteristic geometric parameters but also enables us to detect the surface details of loess landslides (e.g., textures, fissures, and micro-landforms). Manifestly, we can also deduce the original structural characteristics and possible inducement mechanism of landslides based on a combination of high-resolution data acquired by UAVs, proper ground surveys, and theoretical knowledge. In summary, the low-cost UAVs are highly and especially suitable for surveys and digital terrain analysis of landslides on the Loess Plateau with sparse vegetation.

A Seaglider-Integrated Digital Monitor for Bioacoustic Sensing

An acoustic Digital MONitor (DMON) has been integrated into a Seaglider autonomous underwater vehicle to serve as a general-use tool for passive acoustic sensing of marine mammal vocalizations. The system is being developed as a complement to conventional ship-based cetacean survey methods. The acoustic system includes three omnidirectional hydrophones, one located on centerline of the aft payload hatch and one on each wingtip. An onboard real-time detector has been implemented to record an audio sample if ambient noise has risen above a user-prescribed signal-to-noise ratio (SNR) threshold level. The data size and the number of detections are available in semi-real time, and the acoustic data are retrieved upon recovery of the instrument. Because the DMON system interfaces with the Seaglider firmware, the glider pilot has the capability to modify several operational parameters governing the collection of acoustic data while the glider is deployed to tailor the data recording to the desired mission objectives. This implementation is referred to as the Seaglider Customizable Sampling Configuration (SCSC) DMON and has recorded a wide variety of cetacean vocal activity offshore the Hawaiian Islands.

Predicting active-layer soil thickness using topographic variables at a small watershed scale.

Knowledge about the spatial distribution of active-layer (AL) soil thickness is indispensable for ecological modeling, precision agriculture, and land resource management. However, it is difficult to obtain the details on AL soil thickness by using conventional soil survey method. In this research, the objective is to investigate the possibility and accuracy of mapping the spatial distribution of AL soil thickness through random forest (RF) model by using terrain variables at a small watershed scale. A total of 1113 soil samples collected from the slope fields were randomly divided into calibration (770 soil samples) and validation (343 soil samples) sets. Seven terrain variables including elevation, aspect, relative slope position, valley depth, flow path length, slope height, and topographic wetness index were derived from a digital elevation map (30 m). The RF model was compared with multiple linear regression (MLR), geographically weighted regression (GWR) and support vector machines (SVM) approaches based on the validation set. Model performance was evaluated by precision criteria of mean error (ME), mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2). Comparative results showed that RF outperformed MLR, GWR and SVM models. The RF gave better values of ME (0.39 cm), MAE (7.09 cm), and RMSE (10.85 cm) and higher R2 (62%). The sensitivity analysis demonstrated that the DEM had less uncertainty than the AL soil thickness. The outcome of the RF model indicated that elevation, flow path length and valley depth were the most important factors affecting the AL soil thickness variability across the watershed. These results demonstrated the RF model is a promising method for predicting spatial distribution of AL soil thickness using terrain parameters.

Geochemical exploration for vertebrate fossils using field portable XRF

The Riversleigh World Heritage Area in Queensland contains a vast array of Oligocene-Pleistocene vertebrate, invertebrate and plant fossils. The existing suite of fossil deposits contains a number of temporal gaps in the faunal succession, and exploration is turning to large expanses of recently-discovered Cenozoic carbonates to the west and south of Riversleigh. Previous exploration for new deposits has been primarily based on visual detection of bone or tooth fragments in outcrops or by excavation of sites where lithofacies or mineralogy indicates potential host structures. This study examines the application of field-portable X-ray fluorescence spectrometry (fpXRF) to detecting lithogeochemical or mineralogical indicators of fossil fragments and host structures where visual indicators are absent or subtle. Elemental analysis of outcrops by fpXRF has permitted geochemical differentiation of Cenozoic from underlying Cambrian limestones using Sr/Ca and Mn/Ca ratios. Potentially productive depositional environments and structures such as caves and palaeo-channels can be mapped using various combinations of Ti, Zr, and other relatively immobile elements associated with heavy minerals. Detection of finely-divided vertebrate fossiliferous materials is also possible, using ratios of U, Zn and Pb against Ca, or simply by detecting elevated P. The provision of real-time lithogeochemical data by fpXRF offers potential to accelerate the current exploration program in the Riversleigh area, at regional to local scales, and the detection of important vertebrate fossil deposits otherwise overlooked using the conventional visual survey methods.

Mapping the spatio-temporal distribution of key vegetation cover properties in lowland river reaches, using digital photography.

The presence of vegetation in stream ecosystems is highly dynamic in both space and time. A digital photography technique is developed to map aquatic vegetation cover at species level, which has a very high spatial and a flexible temporal resolution. A digital single-lens reflex (DSLR) camera mounted on a handheld telescopic pole is used. The low-altitude (5m) orthogonal aerial images have a low spectral resolution (red-green-blue), high spatial resolution (∼1.9pixelscm-2, ∼1.3cm length) and flexible temporal resolution (monthly). The method is successfully applied in two lowland rivers to quantify four key properties of vegetated rivers: vegetation cover, patch size distribution, biomass and hydraulic resistance. The main advantages are that the method is (i) suitable for continuous and discontinuous vegetation covers, (ii) of very high spatial and flexible temporal resolution, (iii) relatively fast compared to conventional ground survey methods, (iv) non-destructive and (v) relatively cheap and easy to use, and (vi) the software is widely available and similar open source alternatives exist. The study area should be less than 10m wide, and the prevailing light conditions and water turbidity levels should be sufficient to look into the water. Further improvements of the image processing are expected in the automatic delineation and classification of the vegetation patches.

Qualitative simulation of bathymetric changes due to reservoir sedimentation: A Japanese case study.

Sediment-dynamics modeling is a useful tool for estimating a dam’s lifespan and its cost–benefit analysis. Collecting real data for sediment-dynamics analysis from conventional field survey methods is both tedious and expensive. Therefore, for most rivers, the historical record of data is either missing or not very detailed. Available data and existing tools have much potential and may be used for qualitative prediction of future bathymetric change trend. This study shows that proxy approaches may be used to increase the spatiotemporal resolution of flow data, and hypothesize the river cross-sections and sediment data. Sediment-dynamics analysis of the reach of the Tenryu River upstream of Sakuma Dam in Japan was performed to predict its future bathymetric changes using a 1D numerical model (HEC-RAS). In this case study, only annually-averaged flow data and the river’s longitudinal bed profile at 5-year intervals were available. Therefore, the other required data, including river cross-section and geometry and sediment inflow grain sizes, had to be hypothesized or assimilated indirectly. The model yielded a good qualitative agreement, with an R2 (coefficient of determination) of 0.8 for the observed and simulated bed profiles. A predictive simulation demonstrated that the useful life of the dam would end after the year 2035 (±5 years), which is in conformity with initial detailed estimates. The study indicates that a sediment-dynamic analysis can be performed even with a limited amount of data. However, such studies may only assess the qualitative trends of sediment dynamics.

Estimating Earthwork Volumes Through Use of Unmanned Aerial Systems

Unmanned aerial systems (UASs) and unmanned aerial vehicles (UAVs) have become increasingly attractive for numerous surveying applications in civil engineering, agriculture, and many other fields. The unmanned systems and vehicles are capable of performing photogrammetric data acquisition with equipped digital cameras that allows for converting images to highly precise, georeferenced three-dimensional models. However, more studies are needed to demonstrate practical applications of UAS systems and UAVs on construction sites. In this project, UAS systems and UAVs and digital photogrammetry technology are introduced to estimate the earthwork volume of a highway extension project. The georeferenced images were processed by the photogrammetry software, Pix4Dmapper, which is a tool for converting images into an accurate and applicable three-dimensional point cloud model. Progress models were created over the course of several weeks. The volume of earth was computed by comparing the point cloud of the progress models after model processing. To ensure reliability, the accuracy of the UAS and UAV photogrammetry was verified by comparison with conventional ground survey methods and the results from different flights. The project presents the feasibility and effectiveness of using UAS systems and UAVs in estimating earthwork volumes on the basis of the results of an accuracy test and the efficiency of the survey.

ИЗУЧЕНИЕ СОЦИАЛЬНЫХ ПРЕДСТАВЛЕНИЙ С ИСПОЛЬЗОВАНИЕМ МЕТОДА ВИНЬЕТОК: КОЛИЧЕСТВЕННЫЙ ПОДХОД

The article focuses on the prospects of creating vignettes as a new method in empirical sociology. It is a good alternative to the conventional mass survey methods. The article consists of a few sections differing by the focus. The vignette method is not popular among Russian scientists, but has a big history abroad. A wide range of problems can be solved by this method (e.g. the prospects for guardianship and its evaluation, international students’ adaptation to the educational system, social justice studies, market-ing and business research, etc.). The vignette method can be used for studying different problems including sensitive questions (e.g. HIV, drugs, psychological trauma, etc.), because it is one of the projective techniques. Projective techniques allow to obtain more reliable information, because the respondent projects one situation on the another, but at the same time responds to his own stimulus. The article considers advantages and disadvantages of the method. The authors provide information about the limitations of the method. The article presents the key principles for designing and developing the vignettes method depending on the research type. The authors provide examples of their own vignettes tested in the course of their own empirical research. The authors highlight the advantages of the logical-combinatorial approaches (especially the JSM method with its dichotomy) for the analysis of data in quantitative research. Also they consider another method of the analysis of the data that implies the technique of “steeping”, i.e. when the respondent gets new information step by step, which extends his previous knowledge.

INVESTIGATION OF HORIZONTAL AND VERTICAL CONTROLS ON KNUST CAMPUS

Controls are coordinated horizontal or vertical positional data for land and geographic information systems forming a framework to which surveys are started, referenced and adjusted. Controls on KNUST campus were established over three decades ago with new ones being added as and when t h e y a r e required. Conventional survey methods like trilateration, triangulation and traversing were used and are still being used for densification of controls. These approaches involve the use of low precision instruments such as analogue/optical theodolites and leveling equipment. Since the establishment of these controls, t h e y have not been investigated but t h e y are being used for p r o j e c t development. A modern method that uses satellite positioning techniques such as GPS is currently in operation and has numerous advantages in the establishment of control networks. GPS control surveys were carried-out on seven controls and ellipsoidal coordinates were obtained in the World Geodetic System 84 reference frame. The Cartesian coordinates were projected onto the Universal Transverse Mercator frame. A two dimensional conformal transformation was done using existing KNUST boundary coordinates to Ghana National coordinates based on the War Office ellipsoid. Precise Level routines were carried out on the seven controls for the computations of orthometric heights. The method of least squares adjustment, root mean square errors (RMSE), standard errors (SE) and residuals derived were used to analyse the differences in horizontal positions and heights of the controls. The linear displacement between the computed and the existing coordinates were within the range of 0.015m to 0.014m. The RMSE were 0.048 and 0.106, whiles the SE were also 0.057 and 0.125 for the northings and eastings respectively. The computed and existing heights differed between -0.075m and -0.004m with a mean downward movement of 0.011m. Keywords: Surveying; coordinates; control points; GPS; precise level

Analysis of an Unmanned Aerial Vehicle Monitoring System for Resurveying of Shipping Routes

Abstract The paper gives brief description of the conventional and innovative hydrography survey methods and constraints connected with the realization. Proposed hydrographic survey system based on the use of Unmanned Aerial and Maritime systems provides functionality to conduct hydrographic measurements and environment monitoring. System can be easily adapted to fulfil marine safety and security operations, e.g. intrusion threat monitoring, hazardous pollutions monitoring and prevention operations, icing conditions monitoring.

Next-generation freshwater bioassessment: eDNA metabarcoding with a conserved metazoan primer reveals species-rich and reservoir-specific communities.

Freshwater habitats are of high conservation value and provide a wide range of ecosystem services. Effective management requires regular monitoring. However, conventional methods based on direct observation or specimen collection are so invasive, expensive and labour-intensive that frequent monitoring is uncommon. Here, we test whether the evaluation of environmental DNA (eDNA) from water based on a simple protocol can be used for assessing biodiversity. We use universal metazoan primers for characterizing water eDNA across horizontal and vertical spatial dimensions in two reservoirs with known species diversity for two key taxa. eDNA obtained directly from 42 samples × 15 ml water (total = 630 ml) per reservoir yielded DNA signatures for more than 500 metazoan species, of which 105 could be identified to species/genus based on DNA barcodes. We show that eDNA can be used to assign each water sample to its reservoir of origin, and that eDNA outperforms conventional survey methods in single-sample richness comparisons, while revealing evidence for hundreds of unknown species that are undetected by conventional bioassessment methods. eDNA also confirms the presence of a recently discovered invasive snail species and provides evidence for the continued survival of a rare native species of goby not sighted in that habitat since 2007. eDNA thus promises to be a useful addition to the bioassessment toolbox for freshwater systems.

Underwater Towed Video: A Novel Method to Estimate Densities of Queen Conch (Lobatus gigas; Strombidae) Across Its Depth Range

Queen conch (Lobatus gigas) populations living deeper than 20 m are rarely studied, because of the limitations of conventional survey methods using divers [i.e., belt transect (BT), towed-diver]. Acrucial management goal for conch populations is to maintain adult densities at adequate levels to ensure reproduction, which is highly density dependent. Therefore, accurate estimates of adult conch densities, both in shallow and deep areas, are essential. The rapid technical progress of video systems has made it possible to develop new cost-effective ecological sampling tools, which can be used to survey areas previously hardly accessible. A lightweight towed video array was used, which was able to survey adult conch throughout the species entire depth range (ca. 0–60 m depth), in a safe and efficient manner. The towed video method (TVM) was compared with a conventional BT method using scuba divers, in its ability to identify adult live and dead conch. A series of intercalibration transects was conducted in a high-complexity (HC) and in a low-complexity (LC) habitat by having the towed video followed by a diver conducting a concurrent standard BT, covering the exact same surface area as the towed video. In both the HC and LC habitat, adult live queen conch had similar counts with both methods. Adult dead conch were not mistaken for live conch but were significantly underestimated with the towed video compared with the BT. The results validate the use of TVM as a reliable sampling tool to estimate densities of live adult conch in both HC and LC habitats throughout the species depth range.