Field Crews Research Articles

The Model of the Armament And Military Equipment Repair System

The purpose of the study, the results of which are presented in the article, is to develop a mathematical model of the process of restoring weapons and military equipment (IWT), taking into account their losses due to combat and operational and technical reasons, as well as the production capabilities of repair and restoration bodies (RVOS) of the first and second levels. For the operational solution of the recovery system planning and managing tasks, it is necessary to have models that allow approximate assessment of the system effectiveness at various levels of management. The hypothesis of the study is to increase the efficiency of restoring weapons and military equipment using the forces and means of military repair bodies, field repair brigades (VRB) in the conditions of the operation, as well as the production capacities of enterprises of the local industrial economic base. As criteria for effectiveness evaluation, the indicators characterizing the combat capabilities of military formations for a certain period of military planning in peacetime and wartime are considered. Research methods are mathematical apparatus of the theory of queuing systems and differential equations of 'dynamics of averages', system analysis, comparative analysis, generalization, forecasting, and document analysis. The resulting model establishes a relationship between the input parameters and the output indicators of the recovery system, characterizing the serviceability of the IWT. In this case, the control parameter is a parameter that characterizes the ratio of the number of samples of military equipment repaired in the 1st-level RVR. Results: the developed model can be used for: analyzing the technical support system of troops; solving optimization problems of managing the technical support of troops: finding the optimal ratio of the number of samples of military equipment repaired by the first and second level RVOS; determining the optimal number of field crews for repairing military equipment while ensuring a given level of serviceability of military equipment and minimizing the cost of repairing military equipment.

Applications of geophysical methods in agriculture and their potential in Vietnam

Geophysical methods are very popular in Vietnam and have been applied for several decades in deep-earth investigations such as geological mapping, mineral resource searching, and especially oil and gas exploration. In the world, they have proven to be great tools in agriculture as well for soil characterization and monitoring thanks to their notable advantages including rapid data acquisition, large data coverage, high data density, non-destructive and inexpensive survey implementation. However, in Vietnam, the applications of geophysical methods in agriculture have received little attention probably due to the lack of suitable equipment and data processing techniques. This article gives an overview of popular geophysical methods being applied in agriculture in several countries to characterize and monitor soil properties such as moisture, salinity, density, texture, structure, porosity, etc. The main uses of each method are summarized, and relevant publications are given for reading recommendations with the aim of suggesting similar applications in Vietnam. Accordingly, Ground Penetrating Radar (GPR) and Electromagnetic Induction (EMI) are the most versatile with minimum field crew for data acquisition. They should be prioritized to try in Vietnamese agriculture. Since EMI equipment is not currently available in Vietnam, only a GPR test survey was implemented in the Agricultural Academy experimental field by the authors of Hanoi University of Mining and Geology. The preliminary result shows that the biggest challenge is to find reliable techniques to accurately infer soil properties from measured geophysical parameters, which have no explicit relationship with soil properties. Noise suppression is another problem that needs to be addressed to ensure sufficient data quality.

Service Restoration in the Medium Voltage Grid Minimizing the SAIDI Contribution After Primary Substation Failures

One of the most widely used reliability measures for the electric grid is the System Average Interruption Duration Index (SAIDI), i.e. how many minutes the average customer is without power per year. Primary substation failures may significantly increase SAIDI, since they affect a large number of customers. This may be avoided by improving the service restoration process, which requires solving complex non-convex combinatorial problems. Hence, this paper proposes an algorithm for smart, SAIDI-optimizing service restoration in meshed MV grids after primary substation failures. We first formulate service restoration as a Mixed-Integer Linear Programming (MILP) problem by using a linearization of the power flow equations that is proper for meshed grids and by applying exact Big M relaxations for linearizing other involved non-convexities. The decisions include among others the travel routes of the field crew and account for the grid security constraints. Then, we propose a low complexity heuristic iterative method that optimally solves the MILP problem.

The Burgess Shale lagerstätte at the Walcott Quarry, Yoho National Park, Canada

Abstract The Walcott Quarry was discovered in 1909 by the Smithsonian Institute's Charles Doolittle Walcott (1850–1927). The Cambrian Burgess Shale (505 Ma, Miaolingian) crops out in the quarry and the lagerstätte is the nexus of ongoing vigorous debate about fossil preservation (including taphonomy and diagenesis), taxonomy, classification, phylogeny, and the origin of phyla and baupläne. Smithsonian Institute's field crews collected from 1909–24, and the quarry was subsequently expanded by Harvard University (1930), the Canadian Geological Survey (1966–67), and the Royal Ontario Museum (1992–2000). Approximately 250 000 fossils, including soft-bodied forms, have been collected, making the Walcott Quarry with exposures of the Middle Cambrian Burgess Shale, a significant geoheritage site and an important representation of the Cambrian Explosion.

Proofing Field and Laboratory Species Identification Procedures Developed for the Non-Native Osmerid Species Wakasagi (Hypomesus nipponensis) Using SHERLOCK-Based Genetic Verification

Accurate species identification is critical to monitoring programs because mis-identifications can lead to incorrect assessments of population status and trends. In the San Francisco Estuary, efforts to monitor the imperiled osmerid Delta Smelt (Hypomesus transpacificus) using morphology can be challenging because of the presence of the similar-looking non-native osmerid Wakasagi (Hypomesus nipponensis). In 2017, the US Fish and Wildlife Service’s field office in Lodi implemented a two-stage verification process for Wakasagi to help prevent Delta Smelt from being mis-identified as Wakasagi. Under this process, Wakasagi are initially identified in the field, independently identified a second time by an experienced staff member in the laboratory, then stored on-site where they can be made available for future studies. Using the recently developed Specific High-sensitivity Enzymatic Reporter un-LOCKing (SHERLOCK) assay for Wakasagi, we evaluated how well verification protocols performed by genetically identifying a subset of Wakasagi collected during routine sampling between 2017 and 2021. Through this study, we found that the protocols have served as an effective quality control measure for over 4 years and across multiple surveys. With the development of field-deployable genetics tools such as SHERLOCK, genetic identification will likely play an increasingly important role in ecological monitoring. We expect that hybrid approaches that combine morphological identifications by trained field crew with application of field-based genetic tools may offer an effective and efficient approach to ensuring data accuracy in the future.

Transferability of a Mask R–CNN model for the delineation and classification of two species of regenerating tree crowns to untrained sites

Following harvest, monitoring reforestation success is a crucial component of sustainable management. In Alberta, Canada, like other jurisdictions, the efficiency of the current plot-based forest regeneration monitoring regime is challenged by the cost of accessibility and the declining availability of qualified field crews. Fine spatial resolution imagery and deep learning have been proposed as alternative monitoring tools and have proven successful under experimental conditions, yet how successfully models can be applied and transferred between a range of untrained sites and conditions remains unclear.In this research, we repurposed a mask region-based convolutional neural network (Mask R–CNN) model that was previously trained to delineate coniferous tree crowns to instead segment instances of two species of regenerating conifers. We transferred learned parameters by replacing original single-class labels with photo-interpreted species information and retraining a selection of the network's parameters. We assessed the transferability of the new model by testing on five untrained sites, representing a range of forest types and densities typical of reforestation in the region. Results yielded a mean average precision (mAP) of 72% and average class F1 scores of 69% and 78% for lodgepole pine (Pinus contorta) and white spruce (Picea glauca), respectively, demonstrating successful transferability. We then investigated an additional transfer learning scenario by iteratively adding data from four of the five sites to the training set while reserving data from the remaining site for testing. On average, this improved mAP by 5%, lodgepole pine F1 by 7%, and white spruce F1 by 3%, and demonstrated that trained models can be continuously improved as sufficiently representative data becomes available.

Technical note: High-density mapping of regional groundwater tables with steady-state surface nuclear magnetic resonance – three Danish case studies

Abstract. Groundwater is an essential part of the water supply worldwide, and the demands on this water source can be expected to increase in the future. To satisfy the need for resources and to ensure sustainable use of resources, increasingly detailed knowledge of groundwater systems is necessary. However, it is difficult to directly map groundwater with well-established geophysical methods as these are sensitive to both lithology and pore fluid. Surface nuclear magnetic resonance (SNMR) is the only method with a direct sensitivity to water, and it is capable of non-invasively quantifying water content and porosity in the subsurface. Despite these attractive features, SNMR has not been widely adopted in hydrological research, the main reason being an often-poor signal-to-noise ratio, which leads to long acquisition times and high uncertainty in terms of results. Recent advances in SNMR acquisition protocols based on a novel steady-state approach have demonstrated the capability of acquiring high-quality data much faster than previously possible. In turn, this has enabled high-density groundwater mapping with SNMR. We demonstrate the applicability of the new steady-state scheme in three field campaigns in Denmark, where more than 100 SNMR soundings were conducted with a depth of investigation of approximately 30 m. We show how the SNMR soundings enable us to track water level variations at the regional scale, and we demonstrate a high correlation between water levels obtained from SNMR data and water levels measured in boreholes. We also interpret the SNMR results jointly with independent transient electromagnetic (TEM) data, which allows us to identify regions with water bound in small pores. Field practice and SNMR acquisition protocols were optimized during the campaigns, and we now routinely measure high-quality data at 8 to 10 sites per day with a two-person field crew. Together, the results from the three surveys demonstrate that, with steady-state SNMR, it is now possible to map regional variations in water levels with high-quality data and short acquisition times.

Evaluation of a Team-Based Collection and Delivery Operation

The rise in the volume of e-commerce is adding increasing pressure on the logistics of parcel delivery. To improve the efficiency of their operations, the parcel industry in Japan is exploring team-based collection and delivery (TCD), whereby the sales driver (SD) hands out parcels to the field crews (FC), who subsequently deliver them to the door. However, the efficiency of TCD is still understudied. This study proposes a method for optimizing the delivery route for TCD and evaluates the efficiency of the ongoing operation. The TCD delivery problem focuses on minimizing the task completion time using parameters derived through surveys of the actual operations. Comparison between seven different methods show that the newly proposed method of fuzzy c-means clustering with a genetic algorithm outperforms the rest, rapidly computing sufficiently accurate results. Results suggest that the proposed optimal route reduces the total delivery time by up to 18.7%. However, the amount of time saved varies considerably by the area and the number of parcels delivered. Additional constraints for improving driver safety, the cost-benefit of increasing FCs, and the impact on the environmental cost are also considered. The proposed method also helps spread the workload and the travel time of the FCs more evenly, thus further reducing the total delivery time.

Observers are a key source of detection heterogeneity and biased occupancy estimates in species monitoring

Reliable assessments of population status and trends underpin conservation management efforts but are complicated by the fact that imperfect detection is ubiquitous in monitoring data. We explore the most commonly considered variables believed to influence detection probabilities, quantifying how they influence detectability and assessing how occupancy rates are impacted when a variable is ignored. To do so, we used data from two multi-species amphibian monitoring programmes, collected by volunteers and professional surveyors.Our results suggest that although detection rates varied substantially in relation to commonly considered factors such as seasonal and annual effects, ignoring these factors in the analysis of monitoring data had negligible effect on estimated occupancy rates. Variation among surveyors in detection probabilities turned out to be most important. It was high and failing to account for it led to occupancy being underestimated. Importantly, we identified that heterogeneity among observers was as high for professional surveyors as for volunteers, highlighting that this issue is not restricted to citizen-science monitoring.Occupancy modelling has greatly improved the reliability of inference from species monitoring data, yet capturing the relevant sources of variation remains a challenge. Our results highlight that variation among surveyors is a key source of heterogeneity, and that this issue is just as pertinent to data collected by experts as by volunteers. Detection heterogeneity should be accounted for when analysing monitoring data. Furthermore, efforts to increase training of field crews and collecting data to quantify differences between observer abilities are important to avoid biased inference resulting from unmodelled observer differences.

Risk-Averse Importance Sampling of Tree Attributes in High-Risk Forested Areas

Abstract This study develops the theory of risk-averse importance sampling and explains its potential application to forest inventory estimation through the use of a heuristic simulation. When the risk-producing elements of the landscape are known, a risk-averse sampling strategy can be created that results in fewer samples in high-risk areas. Our simulation shows that for certain high-risk populations, risk-averse importance sampling can be highly effective at reducing both risk to field crew members (requiring only 10% of the plot visits in the riskiest category) and sample variance relative to simple random sampling. The method is shown to be especially helpful when a population of values of interest decreases with increasing risk, with a reduction in mean square error (MSE) of 84% to 99% in these cases. The simulation also showed the opposite effect on MSE can be expected when values of interest increase with increasing risk. By increasing field crew safety, risk-averse importance sampling should also improve the frequency and accuracy of field observations, potentially leading to even bigger gains in estimate precision. We recommend risk-averse importance sampling any time hazardous conditions can result in a high number of missing observations and reasonably accurate characterizations of landscape risks can be developed.

Реализация веб-сервиса картографического мониторинга полевого этапа геологоразведочных работ с использованием открытого программного обеспечения

The author presents the results of a web service development aimed at implementing a conceptual model of field geophysical surveys mapping monitoring. The issues of adapting the open source software DBMS PostgreSQL and JavaScript library Leaflet for centralized data gathering, systematization, updating and cartographic visualization of the geological exploration’s field phase progress are considered. The web service was tested during the seismic acquisition at the license areas in the Russian Federation and the Republic of India. It was used as the main tool for spatial analysis of the field crews’ productivity and considering natural and anthropogenic objects that prevent the timely execution of planned volumes of topographic and geodetic and seismic surveys, as well as a means of communication between specialists and administrative decision making. The results of the approbation showed an increase in the efficiency of geological exploration works’ field phase cartographic support. The experience of using open source software, a systematic approach to forming the server space and storing information in the database presented in the article enables developing web-mapping of exploration work carried out simultaneously in several territories through different methods of geophysical exploration.

Autonomous Intelligent Logging Platform Enables Cost and Time Savings

_ This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper OTC 31149, “Sensor Ball: Autonomous, Intelligent Logging Platform,” by Erjola Buzi, Huseyin R. Seren, SPE, and Max Deffenbaugh, SPE, ASC, et al. The paper has not been peer reviewed. Copyright 2021 Offshore Technology Conference. Reproduced by permission. _ The complete paper describes a method of retrieving downhole data that is a practical and inexpensive alternative to wireline or slickline logging and permanently installed sensors. The autonomous logging platform, called the Sensor Ball, is a handheld, untethered logging tool that one person can deploy and recover from a pressurized well with no special equipment or crew. The Autonomous Logging Platform The tool is a battery-powered, self-deployed logging platform. A small dissolvable metal weight is attached to the housing magnetically and helps the free-fall of the tool in the well. Once a desired and programmed depth is reached, the tool releases the weight, and thus changes buoyancy and floats back to surface. Deployment and retrieval of the tool is safe and simple and requires only a wrench to open the cap of the wellhead but does not require cranes, logging trucks, lubricators, or blowout preventers. By sequentially opening and closing the cap, swab, and master valves, in just a few minutes, the untethered logging platform passes the wellhead section and begins traveling downhole. Retrieval is performed by reversing this process. As it travels down and up, the tool records temperature, pressure, and magnetic field data continuously in its internal memory. The recorded data are wirelessly retrieved once the tool is back at the surface. A lightweight atmospheric housing provides buoyancy and insulates the electronics from the well fluids. While optimally exposing temperature and pressure sensors, the small body mass of the housing minimizes the temperature distortion in the downhole environment. The tool is deployed and retrieved several times in the field. Downhole temperature, pressure, and magnetic field data are recorded for several hours. Without the need for field crew or personnel to stand by during the logging operation, rig-up and deployment times decrease from several hours to a few minutes.

Terrestrial gastropod species-specific responses to forest management: Implications for Parelaphostrongylus tenuis transmission to moose

Landscape management can influence the distribution, abundance, and diversity of the terrestrial gastropods that host known parasites of managed species of ungulates. Multiple taxa of terrestrial gastropods are important intermediate hosts in the lifecycle of the parasitic nematode Parelaphostrongylus tenuis, for which white-tailed deer (Odocoileus virginianus) are definitive hosts. Moose (Alces alces) become infected with P. tenuis when they incidentally ingest gastropod intermediate hosts, leading to morbidity and mortality. Populations of moose in Minnesota have declined and P. tenuis infection has been identified as a leading cause of mortality. We investigated the role of forest management disturbance on the terrestrial gastropod community, and specifically known intermediate host species of P. tenuis, on the Grand Portage Indian Reservation in northeastern Minnesota, USA, where moose are an important subsistence species to the Grand Portage Band of Lake Superior Chippewa. Field crews surveyed gastropods through timed searches of soil and litter, and opportunistic collections from browse and pellets of white-tailed deer and moose. We digested all identified gastropods to determine prevalence of P. tenuis infection. We examined gastropod community responses to management and forest cover type using multivariate regressions. We additionally used regressions to examine total gastropod richness and abundance, as well as P. tenuis intermediate host responses to cover type, soil moisture class, canopy cover, treatment, and years since treatment. Digestions detected no infected gastropods from the 621 identified specimens. Gastropod community assemblages differed with recent understory treatment, but no other predictors. Total gastropod abundance, richness, and host abundance (liberal definition, including Deroceras spp.) were lower in sites treated within the last five years. For known intermediate host taxa, we observed species-specific responses to forestry treatments through time. Specifically, Deroceras spp. recolonized sites post-treatment (0–30 years), Discus cronkhitei were higher in abundance immediately following treatment, and the Succinea ovalis group, along with pooled intermediate hosts, displayed no discernable patterns. Our results underscore the complexity of P. tenuis lifecycles and transmission dynamics to moose, the importance of management disturbance and disturbance frequency in regulating gastropod populations, and the potential of forest management treatments to reduce P. tenuis infection in moose.

Forensic archeology as a high‐impact practice

High-impact practices (HIPs) are educational modalities that focus on experiential and deep learning to affect student success in higher education, particularly among students matriculating from historically underserved communities. HIPs are designed to provide students with the intellectual and practical skills to succeed in an increasingly unstable global world beyond college. Utilizing a private-public partnership forensic archeological contract project, this paper examines how this venture employed a HIP-based contractor model that hired students as a professional archeological field crew and provided them with a living wage, transportation, and room and board. It also provided students without the means to participate in international fieldwork with the wherewithal to do so, supporting underserved students and diversity, equity, inclusion, and belonging (DEIB) initiatives. Utilizing this HIP-based contract model resulted in greater student investment and collaboration in a fieldwork situation more akin to the real world, where students learned to solve problems, communicate, and network in an international setting, resulting in new opportunities, such as professional jobs, and academic projects and publications. The paid contractor model ensured students with limited resources could participate, broadening the type of student who can receive this type of training, expanding diversity in forensic anthropology. These models are not limited to forensic archeological fieldwork; they can also be applied to forensic anthropology laboratory projects. Utilizing HIPs and employing a more equitable contractor model contributes to student professionalization, strengthens professional prospects beyond the university, and contributes to DEIB initiatives, all of which benefit forensic anthropology as a subdiscipline.

Measurement uncertainty in a national forest inventory: results from the northern region of the USA

Statistical confidence in estimates of timber volume, carbon storage, and other forest attributes depends, in part, on the uncertainty in field measurements. Surprisingly, measurement uncertainty is rarely reported, even though national forest inventories routinely repeat field measurements for quality assurance. We compared measurements made by field crews and quality assurance crews in the Forest Inventory and Analysis program of the U.S. Forest Service, using data from 2790 plots and 51 740 trees and saplings across the 24 states of the Northern Region. We characterized uncertainty in 12 national core tree-level variables; seven tree crown variables used in forest health monitoring; three variables describing seedlings; and 11 variables describing the site, such as elevation, slope, and distance from a road. Discrepancies in measurement were generally small but were higher for some variables requiring judgment, such as tree class, decay class, and cause of mortality. When scaled up to states, forest types, or the region, uncertainties in basal area, timber volume, and aboveground biomass were negligible. Understanding all sources of uncertainty is important to designing forest monitoring systems, managing the conduct of the inventory, and assessing the uncertainty of forest attributes required for making regional and national forest policy decisions.

The Pandemic: An Unprecedented Impact to Grid Operation [Guest Editorial

The impact of the COVID-19 pandemic has altered the ways and places people work. Government stay-at-home orders during the COVID-19 pandemic led to an average 4% decline in global electricity demand in 2020. The pandemic provided an exceptional opportunity to study the reliability and adaptability of power grid operation when electricity demand changed drastically across many parts of the globe. We started the preparation of this issue that centered around the pandemic theme in the spring of 2021 after the arrival of authorized vaccines. The goal of this special issue is to share the global practices and inherent challenges of grid operations and field crew staffing during this pandemic.

Leveraging Coiled Tubing Conveyance in an Integrated and Rigless Abandonment and Perforation Workflow

Summary In Ecuador, shutoff of an underperforming interval through plug and abandonment (P&A) and perforation of a new interval are traditionally completed with a combination of wireline (WL) and tubing conveyance. An alternative method using enhanced coiled tubing (CT) is presented here; it enables a rigless and efficient workflow that leverages real-time downhole data for on-the-fly optimization. The new workflow relies on CT-conveyed technologies without requiring any additional conveyance methods. CT delivered four different services to start the abandonment by anchoring a 7-in. cast-iron bridge plug (CIBP), complete the abandonment with a low-viscosity cement plug, simulate wellbore dynamics during nitrogen pumping to generate the required underbalanced conditions for perforating, and perforate with a 40-ft ballistic payload of 4 1/2-in. guns. Coupled with real-time downhole telemetry, the enhanced CT workflow provided critical downhole conditions, including fluid levels, accurate depth placement and control, bridge plug setting confirmation, underbalanced conditions, perforating head activation and detonation, and postperforation inflow monitoring. Compared with traditional methods, the enhanced CT workflow introduces several benefits toward completing P&A of old intervals and perforation of new ones. These benefits include enabling a rigless workover (WO) intervention, eliminating the need and cost of a WO rig, reducing operational duration by 13%, and potentially reducing asset footprint and field crews by 95 and 70%, respectively. Elimination of a WO rig reduces environmental impact and the number of personnel on location (i.e., risk). The workflow also extends the reach and efficiency of the service in horizontal wells, enables underbalanced perforation, and delivers actionable real-time downhole data. These data elevate traditional P&A workflows and create a step change in efficiency. First, they allow tracking key downhole parameters that help guarantee a reliable operation of each of the tools and services. Second, they provide insights into the actual downhole conditions throughout the intervention to enable the operator and the field crews to make on-the-fly decisions to deliver a safe and optimal service. Those decisions may include fine-tuning the prescribed treatment or extending the scope of the intervention by leveraging the CT’s pump-through capabilities to maximize well performance and meet, or exceed, the operator’s objectives. The innovative combination of real-time telemetry with abandonment and perforating technologies proved a step change in operational efficiency and range, fueled by the quantity and quality of data recorded during the operation. This case study also marks the first documented perforation with 4 1/2-in. guns with fiber-optic real-time downhole telemetry. Furthermore, the integrated, rigless solution provides operators with an opportunity to extend their WO activity pipeline and free up their WO fleet for other activities.

Aerial Branch Sampling to Detect Forest Pathogens

Diagnostic testing to detect forest pathogens requires the collection of physical samples from affected trees, which can be challenging in remote or rugged environments. As an alternative to traditional ground-based sampling at breast height by field crews, we examined the feasibility of aerially sampling and testing material collected from upper canopy branches using a small unoccupied aerial system (sUAS). The pathogen of interest in this study is Ceratocystis lukuohia, the fungal pathogen responsible for Ceratocystis wilt of ‘ōhi‘a, a vascular wilt disease which has caused widespread mortality to ‘ōhi‘a in native forests across the state of Hawai‘i. To characterize the minimum branch diameter needed to successfully detect the pathogen of interest in infected trees, we tested 63 branch samples (0.8–9.6 cm in diameter) collected from felled trees inoculated with C.lukuohia on Hawai‘i Island. Subsequently, we aerially sampled branches from ten symptomatic ‘ōhi‘a (Metrosideros polymorpha) trees using two different branch sampling systems, the Flying Tree Top Sampler from ETH Zurich and the new Kūkūau branch sampler system introduced in this work, producing 29 branch samples with a maximum diameter of 4.2 cm and length of >2 m. We successfully detected the target fungal pathogen from the collected branches and found that branch diameter, leaf presence and condition, as well as wood moisture content are important factors in pathogen detection in sampled branches. None of the smallest branch samples (those <1 cm in diameter) tested positive for C.lukuohia, while 77% of the largest diameter branch samples (5–10 cm) produced positive results. The Kūkūau branch sampler system is capable of retrieving branches up to 7 cm diameter, providing important capacity for pathogenic research requiring larger diameter samples for successful diagnostic testing. Inconclusive and/or non-detection laboratory results were obtained from sample materials that were either too desiccated or from a branch with asymptomatic leaves, suggesting there is an optimal temporal window for sampling.

UAV-Based Hyperspectral Imagery for Detection of Root, Butt, and Stem Rot in Norway Spruce

Numerous species of pathogenic wood decay fungi, including members of the genera Heterobasidion and Armillaria, exist in forests in the northern hemisphere. Detection of these fungi through field surveys is often difficult due to a lack of visual symptoms and is cost-prohibitive for most applications. Remotely sensed data can offer a lower-cost alternative for collecting information about vegetation health. This study used hyperspectral imagery collected from unmanned aerial vehicles (UAVs) to detect the presence of wood decay in Norway spruce (Picea abies L. Karst) at two sites in Norway. UAV-based sensors were tested as they offer flexibility and potential cost advantages for small landowners. Ground reference data regarding pathogenic wood decay were collected by harvest machine operators and field crews after harvest. Support vector machines were used to classify the presence of root, butt, and stem rot infection. Classification accuracies as high as 76% with a kappa value of 0.24 were obtained with 490-band hyperspectral imagery, while 29-band imagery provided a lower classification accuracy (~60%, kappa = 0.13).

Hybrid Reconnaissance Mission to the 30 October 2020 Aegean Sea Earthquake and Tsunami (Izmir, Turkey & Samos, Greece): Description of Data Collection Methods and Damage

On 30 October 2020, an earthquake of Mw 6.9 hit the Aegean coasts of Turkey and Greece. The epicentre was some 14 km northeast of Avlakia on Samos Island, and 25 km southwest of Seferihisar, Turkey, triggering also a tsunami. The event has been followed by >4,000 aftershocks up to Mw 5.2 The Earthquake Engineering Field Investigation Team (EEFIT) has immediately gathered a team to conduct a hybrid reconnaissance study, bringing together remote and field investigation techniques. The mission took place between 16 November and 17 December, inclusive of three sets of field study carried out by the field crews for building damage assessment in the affected areas in Turkey and Greece under the coordination of the remote team. The mission also aimed to assess the viability of alternative data sources for an appraisal of the future viability of hybrid missions. This paper summarises the mission setup and findings, and discusses the benefits of and difficulties encountered during this hybrid reconnaissance activity.