Data In Remote Locations Research Articles

Comparison of surface-wave techniques to estimate S- and P-wave velocity models from active seismic data

Abstract. The acquisition of seismic exploration data in remote locations presents several logistical and economic criticalities. The irregular distribution of sources and/or receivers facilitates seismic acquisition operations in these areas. A convenient approach is to deploy nodal receivers on a regular grid and to use sources only in accessible locations, creating an irregular source–receiver layout. It is essential to evaluate, adapt, and verify processing workflows, specifically for near-surface velocity model estimation using surface-wave analysis, when working with these types of datasets. In this study, we applied three surface-wave techniques (i.e., wavelength–depth (W/D) method, laterally constrained inversion (LCI), and surface-wave tomography (SWT)) to a large-scale 3D dataset obtained from a hard-rock site using the irregular source–receiver acquisition method. The methods were fine-tuned for the data obtained from hard-rock sites, which typically exhibit a low signal-to-noise ratio. The wavelength–depth method is a data transformation method that is based on a relationship between skin depth and surface-wave wavelength and provides both S- and P-wave velocity (Vs and Vp) models. We used Poisson's ratios estimated through the wavelength–depth method to constrain the laterally constrained inversion and surface-wave tomography and to retrieve both Vs and Vp also from these methods. The pseudo-3D Vs and Vp models were obtained down to 140 m depth over an area of approximately 900 × 1500 m2. The estimated models from the methods matched the geological information available for the site. A difference of less than 6 % was observed between the estimated Vs models from the three methods, whereas this value was 7.1 % for the retrieved Vp models. The methods were critically compared in terms of resolution and efficiency, which provides valuable insights into the potential of surface-wave analysis for estimating near-surface models at hard-rock sites.

Data Security in Cloud Computing

Due to the growing use of cloud services and the possible hazards involved with storing and processing sensitive data in remote locations, data security is a crucial concern in cloud computing. This literature review analyses the state of the art in data security research for cloud computing and emphasises the major discoveries, difficulties, and recommendations for the future. Encryption, access control, network security, physical security, security monitoring, data segregation, backup and disaster recovery, compliance, and safe development practises are just a few of the data security-related topics included in the assessment. The study notes that a problem is the size and quantity of the body of literature as well as the requirement to stay up with the continuously changing area. The need for thorough coverage, evaluation of source quality and reliability, and overcoming language and accessibility challenges are also mentioned as drawbacks. The review goes into further detail on issues including time limits, subjectivity in selection and interpretation, information overload, and integration and synthesis of findings. It is recommended that future research in data security for cloud computing put a particular emphasis on advanced encryption methods, secure data sharing and collaboration, privacy-preserving methods, cloud forensics, threat intelligence, machine learning, security assurance and auditing, blockchain and distributed ledger technologies, as well as user awareness and education. Data security in cloud computing may be further reinforced to secure sensitive data and guarantee the reliability of cloud services by solving these issues and making progress in the sector.

Applications of digital imaging and analysis in seabird monitoring and research

Rapid advances in digital imaging technology offer efficient and cost‐effective methods for measuring seabird abundance, breeding success, phenology, survival and diet. These methods can facilitate understanding of long‐term population trends, and the design and implementation of successful conservation strategies. This paper reviews the suitability of satellites, manned aircraft, unmanned aerial vehicles (UAVs), and fixed‐position, handheld and animal‐borne cameras for recording digital photographs and videos used to measure seabird demographic and behavioural parameters. It considers the disturbance impacts, accuracy of results obtained, cost‐effectiveness and scale of monitoring possible compared with ‘traditional’ fieldworker methods. Given the ease of collecting large amounts of imagery, image processing is an important step in realizing the potential of this technology. The effectiveness of manual, semi‐automated and automated image processing is also reviewed. Satellites, manned aircraft and UAVs have most commonly been used for population counts. Spatial resolution is lowest in satellites, limiting monitoring to large species and those with obvious signs of presence, such as penguins. Conversely, UAVs have the highest spatial resolution, which has allowed fine‐scale measurements of foraging behaviour. Time‐lapse cameras are more cost‐effective for collecting time‐series data such as breeding success and phenology, as human visits are only required infrequently for maintenance. However, the colony of interest must be observable from a single vantage point. Handheld, animal‐borne and motion‐triggered cameras have fewer cost‐effective uses but have provided information on seabird diet, foraging behaviour and nest predation. The last of these has been important for understanding the impact of invasive mammals on seabird breeding success. Advances in automated image analysis are increasing the suitability of digital photography and videography to facilitate and/or replace traditional seabird monitoring methods. Machine‐learning algorithms, such asPengbot, have allowed rapid identification of birds, although training requires thousands of pre‐annotated photographs. Digital imaging has considerable potential in seabird monitoring, provided that appropriate choices are available for both image capture technology and image processing. These technologies offer opportunities to collect data in remote locations and increase the number of sites monitored. The potential to include such solutions in seabird monitoring and research will develop as the technology evolves, which will be of benefit given funding challenges in monitoring and conservation.

The KoBoCollect for Research Data Collection and Management (An experience in Researching the Socio-Economic Impact of Blood Disease in Banana)

In the research field, smartphone began to be used for field data collection. One application that was used was KoBoCollect. This article shared the experience of using KoBoCollect in research on the socio-economic impact of blood diseases on banana in Sumba Island. The research was conducted by interviewing 64 banana farmers that spread proportionally in four regencies in Sumba Island. The use of KoBoCollect/toolbox made it easy to collect, save and manage research data. KoBoCollect/toolbox provided the advantages of conducting paperless research, able to record data in complex formats such as numeric data, descriptive data, photos, videos, sounds, coordinates and other data, dynamically making forms changes when conducting research, and displaying interactive applications. KoBoCollect can be run off-line, made it possible to collect field data in remote locations and no internet network. The research data was transmitted online so that the data tabulation process was automatic. Simple data analysis such as median values, mode, graphs and distribution maps of data collection were provided in KoBotoolbox. With KoBoCollect/toolbox, researchers quickly find out the results of the research, as in this research it was known that blood disease had an impact on the decrease in the banana population revealed by 81.54% of farmers.

Modeling visitor use on high elevation mountain trails: An example from Longs Peak in Rocky Mountain National Park, USA

Increasing use on mountain summits has both social and ecological implications. High numbers of visitors climbing mountain summits can be a safety issue, particularly in areas where terrain or elevation leads to queueing that may cause time delays. Estimating visitor use levels at site specific locations en route to summits is needed to understand the potential benefits and impacts of visitor use in these locations. However, it can be difficult to obtain reliable and robust data to estimate use and develop statistical relationships because of the remote and harsh climates on mountain summits, as well as the financial and personnel requirements involved to collect the data in remote locations. In 2015, data were collected on the higher stretches of the Keyhole Route on Longs Peak in Rocky Mountain National Park, USA (RMNP) to better understand use levels near the summit and to explore potential statistical relationships to trailhead use data that are relatively easy to collect. Strong statistical relationships from robust regression analyses were found between trailhead use counts and daily and hourly use totals on the “Homestretch” which is a final section of the Keyhole Route. Additionally, a strong statistical relationship was found between total daily use and maximum hourly use on the Homestretch. The results suggest that trailhead counts are an accurate and reliable means from which to estimate use levels on upper portions of the Keyhole route. Moreover, this research demonstrates the usefulness of an approach using proxy variables to estimate visitor use along remote peaks where data collection can be difficult. These types of data can elucidate various options and decisions for park management teams who are charged with deciding if and how to manage high use areas.

NOLS and Nutcrackers: The Motivations, Barriers, and Benefits Experienced by Outdoor Adventure Educators in the Context of a Citizen Science Project

Outdoor adventure education (OAE) organizations teach interpersonal and wilderness skills in outdoor settings and often include an explicit commitment to environmental learning. Because OAE organizations typically engage young adults in wilderness areas, citizen science projects in this context have the potential to generate data in remote locations and involve younger audiences in citizen science. The author engaged NOLS (formerly the National Outdoor Leadership School) in the Clark’s Nutcracker Project, a contributory citizen science project, to investigate the impacts of habitat decline on a high-elevation bird species in Wyoming. During the first season of the project, I used online questionnaires and semi-structured interviews to identify the motivations, benefits, and barriers experienced by participating NOLS instructors and administrators. I found that instructors were most often motivated to participate in the project as a means to improve their environmental studies curriculum. Similarly, I found that instructors most often benefitted from the project’s capacity to serve as a teaching tool by providing a focus for curriculum objectives or fostering increased student awareness and student buy-in. Time limitations, study complexity, disappointment over absence data, and concerns about student data quality were the most often identified barriers to participation. In light of these findings, I recommend that citizen science projects within the OAE context should be very easy to implement and align well with existing curricula. For maximum impact, potential projects should focus on a readily visible study subject, be defined by a compelling need, and ideally connect to students’ lives beyond the backcountry.

Harvesting-Aware Energy Management for Environmental Monitoring WSN

Wireless sensor networks can be used to collect data in remote locations, especially when energy harvesting is used to extend the lifetime of individual nodes. However, in order to use the collected energy most effectively, its consumption must be managed. In this work, forecasts of diurnal solar energies were made based on measurements of atmospheric pressure. These forecasts were used as part of an adaptive duty cycling scheme for node level energy management. This management was realized with a fuzzy logic controller that has been tuned using differential evolution. Controllers were created using one and two days of energy forecasts, then simulated in software. These controllers outperformed a human-created reference controller by taking more measurements while using less reserve energy during the simulated period. The energy forecasts were comparable to other available methods, while the method of tuning the fuzzy controller improved overall node performance. The combination of the two is a promising method of energy management.

Survey on public auditability to ensure data integrity in cloud storage

Cloud storage relieves the user from the local management of software and hardware by enabling high quality on demand storage services to store their data in remote locations. Storing the data in remote locations not only reduces the management overheads but also eliminates the user’s physical control over data storage and data security. The loss of physical control over data brings out various security issues such as data loss, tampering of data, data modification. The primary issue is to ensure the correctness of data stored in remote locations which can be resolved by enabling public auditing for cloud storage services. In public auditing, not only the user but anyone can verify the data correctness. The introduction of third-party auditor, who works on behalf of cloud user to verify data integrity helps to reduce user computation resources and cost. The key prerequisite for the public auditing protocol is to support dynamic data operations as data in cloud are dynamic in nature. Cloud is a multiuser environment, so the auditing protocol must scale well to handle multiple auditing processes simultaneously. This paper aims at an extensive survey which mainly outlines the requirements for cloud public auditability and compares varied public auditing protocols.

Two-dimensional thermal video analysis of offshore bird and bat flight

Thermal infrared video can provide essential information about bird and bat activity for risk assessment studies, but the analysis of recorded video can be time-consuming and may not extract all of the available information. Automated processing makes continuous monitoring over extended periods of time feasible, and maximizes the information provided by video. This is especially important for collecting data in remote locations that are difficult for human observers to access, such as proposed offshore wind turbine sites. We developed new processing algorithms for single camera thermal video that automate the extraction of two-dimensional bird and bat flight tracks, and that characterize the extracted tracks to support animal identification and behavior inference. The algorithms consist of video peak store followed by background masking and perceptual grouping to extract flight tracks. The extracted tracks are automatically quantified in terms that could then be used to infer animal taxonomy and possibly behavior, as described in the companion article from Cullinan, et al. [“Classification of birds and bats using flight tracks.” Ecological Informatics, 27:55–63]. The developed automated processing was evaluated using six video clips containing a total of 184 flight tracks. The detection rate was 81% and the false positive rate was 17%. In addition to describing the details of the algorithms, we suggest models for interpreting thermal imaging information.

PROVIDING TOTAL NOAA SCIENTIFIC SUPPORT TO THE USCG FOR REMOTE OIL SPILL LOCATIONS – THE M/V SELENDANG AYUINCIDENT IN ALASKA

ABSTRACT The NOAA Emergency Response Division (ERD aka Hazmat) provides a complete set of scientific assistance and support to the U.S. Coast Guard in response to an offshore oil spill. Historically NOAA National Weather Service (NWS) has provided the operational weather support component for ERD in the form of forecasts and observations. The dearth of conventional weather data in remote locations provide unique challenges for providing weather support for Hazmat events in locations such as the Aleutian Island Chain of Alaska. Weather support for Hazmat events in Alaska are further complicated during the storm season from October through March due to the frequency and intensity of storms in Alaska combined with the vast distances to reach the scene. Such was the case when the M/V Selendang Ayu grounded on Unalaska Island in the Aleutian Islands, 800 miles southwest of Anchorage, within the AOR of NWS Weather Forecast Office Anchorage. Unalaska Island has a handful of permanent observational platforms, all in the vicinity of Dutch Harbor. However, the M/V Selendang Ayu was foundering on the west side of the island, in a different meteorological and oceanographic regime. WFO Anchorage developed a plan that included siting a land-based weather station near the wreck, a specialized processing of Synthetic Aperture Radar Satellite (SARSat) passes, and a Selendang Ayu event web portal populated with tailored products for the event within 24 hours. Given the significance of the event within a highly vulnerable ecosystem, one of the first actions that the ERD Alaska Scientific Support Coordinator initiated was to exercise an agreement with the NWS to bring their Incident Meteorologist on scene as part of the NOAA Scientific Support Team. The NWS response was immediate and effective. Within a week the first Incident Meteorologist (IM) was on scene providing regional and localized weather reviews and forecasts for the IC Post as well as weather briefings on request for helo pilots and boat skippers. On scene IM support continued for the next two months. Weather support through the spring and summer was provided via phone and web by the Anchorage Forecast Office.

Assessment of a portable clinical blood analyzer during space flight

This study was designed to validate the utility of a commercial portable clinical blood analyzer (PCBA) in ground-based studies and on the space shuttle. Ionized calcium, pH, electrolytes, glucose, and hematocrit were determined. Results agreed well with those from traditional laboratory methods, and the PCBA demonstrated good between-day precision for all analytes. In-flight analysis of control samples revealed differences in one analyte (sodium). There were few changes in crew members' results during flight, and these were expected. Potassium increased in flight compared with before flight, and potassium, pH, and hematocrit decreased after flight. Ionized calcium was decreased in flight and on landing day. Changes during flight were likely related to sample collection technique. Postflight changes likely reflected the fluid redistribution that occurs after exposure to weightlessness. These data confirm that the PCBA is a reliable instrument for most analytes, and can provide important medical data in remote locations, such as orbiting spacecraft.