Fieldwork Efficiency Research Articles

High-density analysis of surface wave profile imaging based on a multiple coverage common-midpoint signal-couple array

Surface wave exploration technology has been extensively used in the inspection of construction engineering quality and shallow surface surveys. To enhance the efficiency of surface wave exploration field acquisition and achieve high-precision and high-density surface wave profile imaging, a wireless distributed seismic surface wave signal acquisition system has been developed based on the principles of active source transient surface wave signal acquisition and dispersion curve calculation methods. For the purpose of achieving rapid multiple coverage signal acquisition and enhancing fieldwork efficiency, a method for rapidly configuring common-midpoint signal couples (CMCs) for multiple coverage common-shot signal acquisition has been devised, and a high-precision visualization method for dispersion curve calculation based on the CMC array has been formulated. When compared with the multichannel analysis of the surface wave method under identical conditions, the CMC array can effectively enhance surface wave dispersion curve survey station density and lateral resolution, thereby enabling high-density analysis of surface wave profile imaging. Through model analysis and field examples related to construction quality detection, including foundation compactness and earth and rock mixture compactness, it has been demonstrated that this method offers significant advantages in terms of high accuracy, high density, and a wide application range. These advantages greatly enhance the efficiency of surface wave exploration and the accuracy of profile imaging for the construction of engineering projects.

Insights for the Drop-off/Pick-up Method to Improve Data Collection

Mail and telephone surveys are becoming increasingly expensive and unreliable, while internet-based surveys raise issues of geographic representation and other matters of authenticity. The Drop-Off/Pick-Up (DOPU) method is an alternative which can elicit higher response rates and reduce non-response bias issues. DOPU involves dropping off and picking up surveys in person and can yield high participation because personal interactions have been shown to stimulate norms of reciprocity. We share insights from our 2019 DOPU study of hydrocarbon energy export impacts in four communities that have experienced oil-by-rail transportation and related disasters, with surveys collected in two metropolitan and two rural communities in the U.S. Midwest and Pacific Northwest. We organize and present a suite of novel and established recommendations suitable for both scholarly and community-based researchers and practitioners to strengthen community support, improve fieldwork efficiency, increase response rates, and reduce costs in future DOPU studies.

A Methodological Framework for Free and Open-Source UAV-Based Archaeological Research

AbstractFull-coverage pedestrian survey to record cultural features on unexplored archaeological landscapes is costly in terms of time, money, and personnel. Over the past two decades, researchers have implemented remote sensing and landscape data collection techniques using unmanned aerial vehicles (UAVs) to combat some of these burdens, but the initial cost of equipment, software, and processing power has hindered the ubiquitous implementation of UAV technology as an accessible companion tool to traditional archaeological survey. This article presents a free and open-source, technology-independent analytical framework for the collection and processing of UAV images to produce high-resolution digital terrain models limited only by the equipment available to the researcher. Results from the free and open-source protocol are directly compared to those produced using proprietary software to illustrate the capabilities of freely available data processing tools for UAV-collected images. By replicating the methods outlined here, researchers should be able to identify and target areas of interest to increase fieldwork efficiency, decrease costs of implementing this technology, and produce high-resolution digital terrain models to conduct spatial analyses that pursue a deeper understanding of cultural landscapes.

The application of Unmanned Aerial Vehicles (UAVs) to estimate above-ground biomass of mangrove ecosystems

Mangrove ecosystems are targeted for many conservation and rehabilitation efforts due to their ability to store large amounts of carbon in their living biomass and soil. Traditional methods to monitor above-ground biomass (AGB) rely on on-ground measurements, which are expensive, labour intensive and cover small spatial scales. Structure from Motion and Multi-View Stereo reconstructions from Unmanned Aerial Vehicles imagery (UAV-SfM) have the potential to increase fieldwork efficiency by providing a greater amount of spatial information in less time. However, there is still a need to assess the ability of UAV-SfM to retrieve structural information of mangrove forests, which could pose challenges in areas of high forest complexity and density.In this study we successfully used UAV-SfM data to estimate height, canopy diameter and AGB of natural and rehabilitated mangrove forests across two regions of the southeastern coast of Australia. We used a variable window filter algorithm to detect trees with an 80% detection rate when considering the top canopy. Individual tree canopy segmentation was performed using a marker-controlled watershed segmentation with two sets of constraining markers: treetops and a minimum height below which a pixel is not considered part of a tree.Direct comparison with on-ground measurements at the regional level showed no significant difference in tree height and AGB medians when only top canopy was considered. Similarly, median canopy diameters were not significantly different in natural areas of both regions, but significant differences were found in rehabilitated areas. UAV-SfM estimates of AGB were on average 15% lower in natural areas and 10% higher in rehabilitated areas when compared to on-ground measurements and followed a strong linear relationship close to the ideal one-to-one relationship.Additionally, we performed a cost-benefit analysis of the two methodologies. UAV-SfM methods can save almost AU$ 50,000 per ha when compared to on-ground measurements and become cost-effective (based on total costs) after just 15 days of surveys. The methods described in this study open the possibility for easily repeatable, low-cost UAV-SfM surveys for local managers by providing a faster, more cost-effective approach for monitoring mangrove forests over larger areas than traditional on-ground surveys while maintaining forest inventory data accuracy in both natural and rehabilitated mangrove forests.

Design of intelligent detection system for high voltage circuit breaker based on functional integration

Since there are various preventive test items for high voltage circuit breaker, in this paper, a function-integrated hardware is put forward to reduce the height and wiring times of the test personnel and improve the field work efficiency. Firstly, we comprehensively analyze the electrical test requirements for high voltage circuit breaker. Then we integrate multiple detection projects into one system, taking advantage of the fact that each test project can be merged. These test projects include tests of dielectric loss of circuit breaker, capacitance value, circuit resistance, direct resistance of switching coil, mechanical characteristic, closing resistance and closing time as well as insulation resistance and AC withstand voltage of auxiliary control circuit. Next, we configure the required detection items and relevant parameters before the test. Finally, we complete the whole process, which requires connection and disconnection for only once and will automatically finish all project detection, test data collection and intelligent analysis item by item.

Economical drone mapping for archaeology: Comparisons of efficiency and accuracy

In the last few years Unpiloted Aerial Vehicles (UAVs), or drones, have been widely adopted by archaeologists as an important tool for archaeological survey, excavation recording, and heritage site management. As the technology has improved and costs plummeted, it has become possible to record increasingly large areas at high resolution. Now that drones are a common part of the archaeological toolkit, there is increasing interest in affordable ways to improve accuracy and survey efficiency in the field. This paper presents quantifiable results comparing multiple strategies for drone data collection from a local test site in New Hampshire, as well as a pair of examples of deploying such systems in the field. Results demonstrate low-cost methods using DIY-style drones and Post Processed Kinematic GNSS data recording can increase fieldwork efficiency and produce high-resolution ortho-imagery with better than decimeter accuracy without the need for ground control. These will be critical improvements for archaeologists working with limited budgets or with limited access to sites.

Modeling the effect of quota sampling on online fieldwork efficiency: An analysis of the connection between uncertainty and sample usage

Market, Opinion and Social Research is increasingly relying on non-probabilistic online panels as data sources and quota sampling as the default sampling method. Quota sampling applied to online panels requires discarding participants to ensure that the final sample match the target population distribution. This article analyzes how different features of a quota sample (such as the sample size, number, and types of quotas) impact the number of participants that must be discarded during the data collection (fieldwork efficiency). Both analytical models and simulation have been used for this purpose. Finally, we show how uncertainty about participants relates to fieldwork efficiency, providing practical recommendations in pursuing this goal.

Alternative methods for selecting web survey samples

Probability-based sampling is the gold standard for general population surveys. However, when interested in more specific populations (e.g., consumers of a particular brand), a lot of research uses data from non-probability-based online panels. This article investigates different ways to select a sample in an opt-in panel: without previous information, using profiling information, or using passive data from a tracker installed on the panelists’ devices. Moreover, it investigates the effect of sending the survey closer to the “moment-of-truth,” which is expected to reduce memory limitations in recall questions. Using additional information (profiling or passive) to select the sample leads to clear improvements in terms of levels of participation and fieldwork efficiency, but not in terms of data quality (measured by the proportion of don’t know answers and the length of answers to open narrative questions) or accuracy (measured by comparing the answers to 14 questions to an external source of information). Doing the survey closer to the “moment-of-truth” further improves the fieldwork efficiency; however, there are still many challenges to implement true “in-the-moment” surveys. We also observed differences across the different samples in respondents’ socio-demographic characteristics and in the survey evaluation.

Space-time clusters for early detection of grizzly bear predation.

Accurate detection and classification of predation events is important to determine predation and consumption rates by predators. However, obtaining this information for large predators is constrained by the speed at which carcasses disappear and the cost of field data collection. To accurately detect predation events, researchers have used GPS collar technology combined with targeted site visits. However, kill sites are often investigated well after the predation event due to limited data retrieval options on GPS collars (VHF or UHF downloading) and to ensure crew safety when working with large predators. This can lead to missing information from small‐prey (including young ungulates) kill sites due to scavenging and general site deterioration (e.g., vegetation growth). We used a space–time permutation scan statistic (STPSS) clustering method (SaTScan) to detect predation events of grizzly bears (Ursus arctos) fitted with satellite transmitting GPS collars. We used generalized linear mixed models to verify predation events and the size of carcasses using spatiotemporal characteristics as predictors. STPSS uses a probability model to compare expected cluster size (space and time) with the observed size. We applied this method retrospectively to data from 2006 to 2007 to compare our method to random GPS site selection. In 2013–2014, we applied our detection method to visit sites one week after their occupation. Both datasets were collected in the same study area. Our approach detected 23 of 27 predation sites verified by visiting 464 random grizzly bear locations in 2006–2007, 187 of which were within space–time clusters and 277 outside. Predation site detection increased by 2.75 times (54 predation events of 335 visited clusters) using 2013–2014 data. Our GLMMs showed that cluster size and duration predicted predation events and carcass size with high sensitivity (0.72 and 0.94, respectively). Coupling GPS satellite technology with clusters using a program based on space–time probability models allows for prompt visits to predation sites. This enables accurate identification of the carcass size and increases fieldwork efficiency in predation studies.

Combining data from multiple sources to design a raptor census - the first national survey of the Montagu’s Harrier Circus pygargus in Poland

SummaryThe effective conservation management of vulnerable taxa requires up-to-date evaluation of population size. Montagu’s Harrier Circus pygargus is a farmland raptor of high conservation concern and threatened by agricultural intensification. However, within many European countries, including Poland, the status of this species remains unknown or questionable and information on its breeding is incomplete or imprecise. Here, we estimate the size of the national population of the Montagu’s Harrier and argue that using data from multiple sources may help to design national bird surveys and better contribute to identifying population trends. We built a predictive model based on a presence-absence data obtained by volunteer-based citizen-science projects conducted in Poland during 2000–2012. Afterwards, from the set of 10 km x 10 km squares of high predicted habitat suitability, 100 sampling plots were randomly chosen and regularly surveyed by experienced ornithologists in 2013 and 2014. The evaluation of fieldwork efficiency by the double-observer approach allowed detectability to be estimated and accounted for while estimating population size. We estimated the Polish Montagu’s Harrier population at almost 3,400 breeding pairs (95% CI: 2,700–4,300), thus constituting 20% of the European Union (EU) population. Furthermore, we showed that public-gathered data originating from multiple sources offered great potential for regular surveys to obtain large-scale estimates of population size.

A generalized algebraic difference approach allows an improved estimation of aboveground biomass dynamics of Cunninghamia lanceolata and Castanopsis sclerophylla forests

A generalized algebraic difference approach (GADA) developed in this study improved the estimation of aboveground biomass dynamics of Cunninghamia lanceolata (Lamb.) Hook and Castanopsis sclerophylla (Lindl.) Schott forests. This could significantly improve the fieldwork efficiency for dynamic biomass estimation without repeated measurements. The estimation of biomass growth dynamics and stocks is a fundamental requirement for evaluating both the capability and potential of forest carbon sequestration. However, the biomass dynamics of Cunninghamia lanceolata and Castanopsis sclerophylla using the generalized algebraic difference approach (GADA) model has not been made to date. This study aimed to quantify aboveground biomass (AGB, including stem, branch and leaf biomass) dynamics and AGB increment in C. lanceolata and C. sclerophylla forests by combining a GADA for diameter prediction with allometric biomass models. A total of 12 plots for a C. lanceolata plantation and 11 plots for a C. sclerophylla forest were selected randomly from a 100 m × 100 m systematic grid placed over the study area. GADA model was developed based on tree ring data for each stand. GADA models performed well for diameter prediction and successfully predicted AGB dynamics for both stands. The mean AGB of the C. lanceolata stand ranged from 69.4 ± 7.7 Mg ha−1 in 2010 to 102.5 ± 11.4 Mg ha−1 in 2013, compared to 136.9 ± 7.0 Mg ha−1 in 2010 to 154.8 ± 8.0 Mg ha−1 in 2013 for C. sclerophylla. The stem was the main component of AGB stocks and production. Significantly higher production efficiency (stem production/leaf area index) and AGB increment was observed for C. lancolata compared to C. sclerophylla. Dynamic GADA models could overcome the limitations posed by within-stand competition and limited biometric data, can be applied to study AGB dynamics and AGB increment, and contribute to improving our understanding of net primary production and carbon sequestration dynamics in forest ecosystems.

Direct derivation of maize plant and crop height from low-cost time-of-flight camera measurements.

BackgroundIn agriculture, information about the spatial distribution of crop height is valuable for applications such as biomass and yield estimation, or increasing field work efficiency in terms of fertilizing, applying pesticides, irrigation, etc. Established methods for capturing crop height often comprise restrictions in terms of cost and time efficiency, flexibility, and temporal and spatial resolution of measurements. Furthermore, crop height is mostly derived from a measurement of the bare terrain prior to plant growth and measurements of the crop surface when plants are growing, resulting in the need of multiple field campaigns. In our study, we examine a method to derive crop heights directly from data of a plot of full grown maize plants captured in a single field campaign. We assess continuous raster crop height models (CHMs) and individual plant heights derived from data collected with the low-cost 3D camera Microsoft® Kinect® for Xbox One™ based on a comprehensive comparison to terrestrial laser scanning (TLS) reference data.ResultsWe examine single measurements captured with the 3D camera and a combination of the single measurements, i.e. a combination of multiple perspectives. The quality of both CHMs, and individual plant heights is improved by combining the measurements. R2 of CHMs derived from single measurements range from 0.48 to 0.88, combining all measurements leads to an R2 of 0.89. In case of individual plant heights, an R2 of 0.98 is achieved for the combined measures (with R2 = 0.44 for the single measurements). The crop heights derived from the 3D camera measurements comprise an average underestimation of 0.06 m compared to TLS reference values.ConclusionWe recommend the combination of multiple low-cost 3D camera measurements, removal of measurement artefacts, and the inclusion of correction functions to improve the quality of crop height measurements. Operating low-cost 3D cameras under field conditions on agricultural machines or on autonomous platforms can offer time and cost efficient tools for capturing the spatial distribution of crop heights directly in the field and subsequently to advance agricultural efficiency and productivity. More general, all processes which include the 3D geometry of natural objects can profit from low-cost methods producing 3D geodata.Electronic supplementary materialThe online version of this article (doi:10.1186/s13007-016-0150-6) contains supplementary material, which is available to authorized users.

Can encouraging respondents to contact interviewers to make appointments reduce fieldwork effort? Evidence from a randomized experiment in the UK

One of the main components of survey costs is interviewer call attempts associated with making contact. This paper describes an experiment conducted on a U.K. household panel study, which sought to evaluate whether an “early-bird” approach whereby participants are encouraged to contact their interviewer before fieldwork began in order to set up an appointment could increase fieldwork efficiency by reducing the number of calls required. This approach has been successfully used on the National Longitudinal Study of Youth 1979 cohort for some time but has not been evaluated experimentally. Our experiment involved two treatment groups: one group was promised a modest financial incentive (£5 per participant) to take up the “early-bird” offer and complete an interview, and the other received an appeal to their altruistic tendencies that emphasized that being an “early bird” would make their interviewer's life easier. A parallel experiment sought to evaluate the impact of differential standard incentives on response. The early-bird take-up rate was higher for the incentivized group (10 percent compared with 6 percent for the non-incentivized group) and was highest when combined with the higher standard incentive rate (17 percent). Offering both an early-bird incentive and the higher standard incentive did increase overall fieldwork efficiency, as measured by calls required per completed case, but the modest take-up rates meant that the overall impact was fairly minimal. The paper also finds indicative evidence that the early-bird offer, if sufficiently incentivized, could potentially have a beneficial impact on response rates.

Increasing Fieldwork Efficiency Through Prespecified Appointments

Responsive survey designs may attempt to tailor contact attempts to selected units based on available information about the units. Cross-sectional surveys often lack sufficient information for such tailoring, especially at the beginning of the field period. In panel surveys, on the other hand, information from prior waves exists, and such information can be used to refine attempts to make contact or elicit cooperation. However, existing findings regarding the effectiveness of such information are confounded with interviewers' and respondents' behaviors. This research note reports results from a randomized field experiment that tested the use of prior wave contact information to increase fieldwork efficiency in a face-to-face survey. A random subset of respondents to the Medical Expenditure Panel Survey Household Component was informed via postcard about a prespecified interview appointment. The date and time of the appointment were based on information from the prior wave interview date. Such date assignment significantly reduced the number of actions needed to achieve an interview in the treatment group compared to the control group, reducing the number of hours worked in the field by 4 percent.

Augmented reality-based computational fieldwork support for equipment operations and maintenance

This paper describes the development of an Augmented Reality (AR)-based equipment Operations and Maintenance (O&M) fieldwork support application to improve efficiency at the site and the experimental evaluation of the application. The application consists of an AR-based interface for intuitive GUI and an O&M information model developed with various types of O&M specific information obtained through observing tradespeople's fieldwork activities, and those from Computerized Maintenance Management System (CMMS) and Building Automation System (BAS). In addition, the BACnet protocol is used to get sensor-derived operation data in real time from BAS. A series of experiments was conducted to quantitatively measure improvement in equipment O&M fieldwork efficiency by using a software prototype of the application. The results show that with the application the subjects saved, on average, 51% of time spent at task when they located target areas and 8% of time at task while obtaining sensor-based performance data from BAS.

Double sampling for stratification for the monitoring of sparse tree populations: the example of Populus euphratica Oliv. forests at the lower reaches of Tarim River, Southern Xinjiang, China

Desertification is a pressing issue in the dry Tarim River basin, which is under anthropogenic stresses. In this study, double sampling for stratification (DSS) is employed to inventory Populus euphratica Oliv. forests in the lower reaches of the Tarim River Basin in Xinjiang, China. The two objectives were evaluating DSS as a sampling technique for monitoring desertification and generating baseline information for permanent observation. Here, DSS consists of two phases: in phase 1, crown cover is observed on a large sample of plots on a high resolution satellite image, and these photo-plots are stratified into five crown cover strata. Phase 2 is a stratified random sample from these photo-plots and the sampled plots are field observed. Approximately 32% of the study area is without P. euphratica trees. As expected, estimated mean poplar tree density and basal area increase with crown cover. DSS takes advantages of stratification (fieldwork efficiency and statistical precision) without the need for a priori strata delineation. It proves feasible for inventory the sparse poplar population and holds promise for the assessment of trees outside the forest, where density varies considerably and pre-stratification is intractable. It can be integrated into permanent observation systems for monitoring vegetation changes.

The status of breeding Barn Owls Tyto alba in the United Kingdom 1995–97

A national survey of breeding Barn Owls was undertaken between 1995 and 1997 using intensive fieldwork methods within a stratified sample of 1100 2 × 2-km survey squares selected at random from those available. Each year, fieldwork was divided into two sessions: one to locate potential nest-sites (winter session) and one to determine occupancy of these sites (summer session). Fieldworkers spent an average of 30 hours on fieldwork within each survey square. The survey produced national population estimates of 2830 (95% confidence intervals: 1952–3761) breeding pairs for 1995, 3967 (95% CI: 2785–5252) for 1996 and 3951 (95% CI: 2769–5214) for 1997. Analysis taking account of the poor coverage in certain regions of high Barn Owl density in 1995 suggests that a population estimate of 3480 would be more accurate for that year. Regional and temporal variations in estimates were examined and interpreted in relation to Barn Owl productivity and ecology. Validation of fieldwork efficiency was carried out within a random selection of the available survey tetrads, demonstrating that fieldworkers achieved a high degree of survey reliability. This paper provides a baseline population estimate and standardized, repeatable methods, allowing future population changes to be monitored effectively.

96/05638 Analysis of coal using scanning tunneling microscopy

This paper describes the development of an Augmented Reality (AR)-based equipment Operations and Maintenance (O&M) fieldwork support application to improve efficiency at the site and the experimental evaluation of the application. The application consists of an AR-based interface for intuitive GUI and an O&M information model developed with various types of O&M specific information obtained through observing tradespeople's fieldwork activities, and those from Computerized Maintenance Management System (CMMS) and Building Automation System (BAS). In addition, the BACnet protocol is used to get sensor-derived operation data in real time from BAS. A series of experiments was conducted to quantitatively measure improvement in equipment O&M fieldwork efficiency by using a software prototype of the application. The results show that with the application the subjects saved, on average, 51% of time spent at task when they located target areas and 8% of time at task while obtaining sensor-based performance data from BAS.