scholarly journals Forest Roads and Operational Wildfire Response Planning

Forests ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 110
Author(s):  
Matthew P. Thompson ◽  
Benjamin M. Gannon ◽  
Michael D. Caggiano
Keyword(s):  
Decision Support ◽  
Wildland Fire ◽  
Predictor Variable ◽  
Future Research ◽  
National Forest ◽  
Primary Control ◽  
Fire Control ◽  
Forest Roads ◽  
Forest Road ◽  
Response Planning

Supporting wildfire management activities is frequently identified as a benefit of forest roads. As such, there is a growing body of research into forest road planning, construction, and maintenance to improve fire surveillance, prevention, access, and control operations. Of interest here is how road networks directly support fire control operations, and how managers incorporate that information into pre-season assessment and planning. In this communication we briefly review and illustrate how forest roads relate to recent advances in operationally focused wildfire decision support. We focus on two interrelated products used on the National Forest System and adjacent lands throughout the western USA: potential wildland fire operational delineations (PODs) and potential control locations (PCLs). We use real-world examples from the Arapaho-Roosevelt National Forest in Colorado, USA to contextualize these concepts and illustrate how fire analytics and local fire managers both identified roads as primary control features. Specifically, distance to road was identified as the most important predictor variable in the PCL boosted regression model, and 82% of manager-identified POD boundaries aligned with roads. Lastly, we discuss recommendations for future research, emphasizing roles for enhanced decision support and empirical analysis.

Integrating social science research into wildland fire management

2014 ◽  
Vol 23 (4) ◽  
pp. 381-394 ◽  
Author(s):  
Michael Czaja ◽  
Stuart P. Cottrell
Keyword(s):  
Social Science ◽  
Prescribed Fire ◽  
Fire Management ◽  
Wildland Fire ◽  
Social Science Research ◽  
Science Research ◽  
Future Research ◽  
National Forest ◽  
Content Type ◽  
Wildland Fire Management

Purpose – Social science research is used to support the formulation of natural resource management decisions with accurate and timely information. Due to risk and potential impacts, this is important in wildland fire management. The purpose of this paper is to identify the respondent perceptions of a natural disturbance agent's impact on fire management in Colorado and Wyoming. Design/methodology/approach – The research methodology included a self-administered questionnaire completed by a random sample of respondents in three study locations adjacent to national forests. A quantitative analysis was conducted to identify attitudes about fuels management (prescribed fire) and beliefs about fire and fire management. Findings – Respondents viewed prescribed fire favorably and they understand the natural role of fire on the landscape. While results suggest respondents support management of forest conditions to decrease the effects of a wildfire, they do not feel that individuals have a right to expect their home to be protected from fire by land managers, nor do they agree with restricting home building near national forest land. Research limitations/implications – Future research should continue the longitudinal assessment of attitudes toward prescribed fires, incorporating respondent distance to the national forest or identifying respondents living within the wildland-urban interface. Originality/value – This paper illustrates how applied, social science research can meet the needs of agencies and public officials. Results of this paper have been presented to state and federal forestry officials, and members of an executive-level task force in Colorado studying wildfire insurance and forest health.

Decision support tools for oil spill response (OSR-DSTs): Approaches, challenges, and future research perspectives

2021 ◽  
Vol 167 ◽  
pp. 112313
Author(s):  
Zhaoyang Yang ◽  
Zhi Chen ◽  
Kenneth Lee ◽  
Edward Owens ◽  
Michel C. Boufadel ◽  
...  
Keyword(s):  
Decision Support ◽  
Oil Spill ◽  
Future Research ◽  
Decision Support Tools ◽  
Research Perspectives ◽  
Support Tools ◽  
Oil Spill Response

scholarly journals A Deep Learning Approach to Downscale Geostationary Satellite Imagery for Decision Support in High Impact Wildfires

Forests ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 294
Author(s):  
Nicholas F. McCarthy ◽  
Ali Tohidi ◽  
Yawar Aziz ◽  
Matt Dennie ◽  
Mario Miguel Valero ◽  
...  
Keyword(s):  
Deep Learning ◽  
Decision Support ◽  
Real Time ◽  
Forest Fires ◽  
Wildland Fire ◽  
Fire Spread ◽  
Low Earth Orbit ◽  
Practical Implementation ◽  
Spatiotemporal Resolution ◽  
Active Fire

Scarcity in wildland fire progression data as well as considerable uncertainties in forecasts demand improved methods to monitor fire spread in real time. However, there exists at present no scalable solution to acquire consistent information about active forest fires that is both spatially and temporally explicit. To overcome this limitation, we propose a statistical downscaling scheme based on deep learning that leverages multi-source Remote Sensing (RS) data. Our system relies on a U-Net Convolutional Neural Network (CNN) to downscale Geostationary (GEO) satellite multispectral imagery and continuously monitor active fire progression with a spatial resolution similar to Low Earth Orbit (LEO) sensors. In order to achieve this, the model trains on LEO RS products, land use information, vegetation properties, and terrain data. The practical implementation has been optimized to use cloud compute clusters, software containers and multi-step parallel pipelines in order to facilitate real time operational deployment. The performance of the model was validated in five wildfires selected from among the most destructive that occurred in California in 2017 and 2018. These results demonstrate the effectiveness of the proposed methodology in monitoring fire progression with high spatiotemporal resolution, which can be instrumental for decision support during the first hours of wildfires that may quickly become large and dangerous. Additionally, the proposed methodology can be leveraged to collect detailed quantitative data about real-scale wildfire behaviour, thus supporting the development and validation of fire spread models.

Influences of Stress on Interactions with Decision Support

2020 ◽  
Vol 64 (1) ◽  
pp. 1886-1890
Author(s):  
Kylie Litaker ◽  
Christopher B. Mayhorn
Keyword(s):  
Decision Support ◽  
Information Source ◽  
Negative Influence ◽  
Future Research ◽  
Physiological Measures ◽  
Task Motivation ◽  
Situational Stress ◽  
Before And After ◽  
Scanning Task ◽  
Source Of Information

People regularly interact with automation to make decisions. Research shows that reliance on recommendations can depend on user trust in the decision support system (DSS), the source of information (i.e. human or automation), and situational stress. This study explored how information source and stress affect trust and reliance on a DSS used in a baggage scanning task. A preliminary sample of sixty-one participants were given descriptions for a DSS and reported trust before and after interaction. The DSS gave explicit recommendations when activated and participants could choose to rely or reject the choice. Results revealed a bias towards self-reliance and a negative influence of stress on trust, particularly for participants receiving help from automation. Controlling for perceived reliability may have eliminated trust biases prior to interaction, while stress may have influenced trust during the task. Future research should address potential differences in task motivation and include physiological measures of stress.

scholarly journals Bridging Science and Practice-Importance of Stakeholders in the Development of Decision Support: Lessons Learned

2021 ◽  
Vol 13 (10) ◽  
pp. 5744
Author(s):  
Innocent K. Tumwebaze ◽  
Joan B. Rose ◽  
Nynke Hofstra ◽  
Matthew E. Verbyla ◽  
Daniel A. Okaali ◽  
...  
Keyword(s):  
Decision Support ◽  
Stakeholder Participation ◽  
Scientific Data ◽  
Lessons Learned ◽  
Future Research ◽  
Decision Support Tools ◽  
Local Data ◽  
Funding Sources ◽  
Sanitation And Hygiene ◽  
Support Tools

User-friendly, evidence-based scientific tools to support sanitation decisions are still limited in the water, sanitation and hygiene (WASH) sector. This commentary provides lessons learned from the development of two sanitation decision support tools developed in collaboration with stakeholders in Uganda. We engaged with stakeholders in a variety of ways to effectively obtain their input in the development of the decision support tools. Key lessons learned included: tailoring tools to stakeholder decision-making needs; simplifying the tools as much as possible for ease of application and use; creating an enabling environment that allows active stakeholder participation; having a dedicated and responsive team to plan and execute stakeholder engagement activities; involving stakeholders early in the process; having funding sources that are flexible and long-term; and including resources for the acquisition of local data. This reflection provides benchmarks for future research and the development of tools that utilize scientific data and emphasizes the importance of engaging with stakeholders in the development process.

scholarly journals Effects of forest roads on Ips sexdentatus infestation in black pine forest

2018 ◽  
Vol 6 (7) ◽  
pp. 828
Author(s):  
Gonca Ece Özcan ◽  
Korhan Enez ◽  
Burak Arıcak
Keyword(s):  
Bark Beetle ◽  
Bark Beetles ◽  
Forest Ecosystems ◽  
Significant Risk ◽  
Pine Forests ◽  
Slope Aspect ◽  
Black Pine ◽  
Forest Roads ◽  
Forest Road ◽  
Ips Sexdentatus

Forest roads are important transportation equipment through forested areas in the rugged, mountainous terrain of northern Turkey. Forest roads harm forest ecosystems due to both the manner in which they are established and how they are used afterwards. Damage to trees that occur during road construction through forests stresses trees, which facilitates outbreaks of bark beetle populations. Bark beetles are significant risk to the health and productivity of Turkish pine forests and to pine forests worldwide. In particular, Ips sexdentatus (Boerner) (Coleoptera, Curculionidae, Scolytinae) is a particularly destructive species of bark beetle in Turkish forests. Their damage to coniferous trees threatens the sustainability of the forest ecosystems. This study primarily aims to assess the intensity of damage that I. sexdentatus inflicts on Pinus nigra J.F.Arnold stands relative to several parameters: the distance to the nearest forest road, aspect (shady - sunny), slope (0–15% or >15%), and other stand characteristics. In this study, we show how damage by an I. sexdentatus infestation in pure black pine stands varies with distance to forest roads and in situ edaphic factors. We sampled 45 plots (400 m2 each), slope, aspect and distances to the nearest forest road was determined using ArcGIS software and the region’s road network overlays. Results showed that trees located within 100 m from the nearest forest road were the most severely damaged ones. The intensity of I. sexdentatus damage was about 16% in a hectare. Trees that were in 16–20 cm diameter class were damaged more often. I. sexdentatus damage did not show any significant correlation with the slope, aspect or degree of canopy closure.

scholarly journals University campuses can contribute to wildlife conservation in urbanizing regions: a case study from Nigeria

2020 ◽  
Vol 12 (13) ◽  
pp. 16736-16741
Author(s):  
Iliyasu Simon ◽  
Jennifer Che ◽  
Lynne Baker
Keyword(s):  
Habitat Use ◽  
Wildlife Conservation ◽  
Energy Use ◽  
Predictor Variable ◽  
Camera Traps ◽  
Future Research ◽  
Natural Habitats ◽  
University Campuses ◽  
Disturbed Areas ◽  
Cricetomys Gambianus

Globally, colleges and universities are increasingly mandating sustainability and environmental protection into their practices.  To date, such institutions have focused their efforts on recycling and energy-use reduction and less on the management and conservation of wildlife and wildlife habitats. However, in an increasingly urbanizing world, well-managed campuses can provide habitat and even refuge for wildlife species.  On the campus of a sustainability-minded university in Nigeria, we used camera traps to determine the presence of wildlife and used occupancy modeling to evaluate factors that influenced the detectability and habitat use of two mammals for which we had sufficient detections: White-tailed Mongoose Ichneumia albicauda and Gambian Rat Cricetomys gambianus.  Our intent was to gather baseline data on campus wildlife to inform future research and make recommendations for maintaining wildlife populations.  We detected wildlife primarily within less-disturbed areas that contained a designated nature area, and the presence of a nature area was the key predictor variable influencing habitat use.  No measured variables influenced detectability.  This study supports other research that highlights the importance of undisturbed or minimally disturbed natural habitats on university campuses for wildlife, especially in increasingly built-up and developed regions.  We recommend that institutions of higher education devote greater resources to making campuses wildlife-friendly and increase opportunities for students to engage in campus-based wildlife research and conservation and other sustainability-related programs. 

scholarly journals Machine Learning Models of COVID-19 Cases in the United States: A Study of Initial Lockdown and Reopen Regimes

2021 ◽  
Vol 11 (23) ◽  
pp. 11227
Author(s):  
Arnold Kamis ◽  
Yudan Ding ◽  
Zhenzhen Qu ◽  
Chenchen Zhang
Keyword(s):  
United States ◽  
Machine Learning ◽  
Additive Model ◽  
Regression Tree ◽  
Predictor Variable ◽  
The United States ◽  
Predictor Variables ◽  
Future Research ◽  
Machine Learning Methods ◽  
Variance Explained

The purpose of this paper is to model the cases of COVID-19 in the United States from 13 March 2020 to 31 May 2020. Our novel contribution is that we have obtained highly accurate models focused on two different regimes, lockdown and reopen, modeling each regime separately. The predictor variables include aggregated individual movement as well as state population density, health rank, climate temperature, and political color. We apply a variety of machine learning methods to each regime: Multiple Regression, Ridge Regression, Elastic Net Regression, Generalized Additive Model, Gradient Boosted Machine, Regression Tree, Neural Network, and Random Forest. We discover that Gradient Boosted Machines are the most accurate in both regimes. The best models achieve a variance explained of 95.2% in the lockdown regime and 99.2% in the reopen regime. We describe the influence of the predictor variables as they change from regime to regime. Notably, we identify individual person movement, as tracked by GPS data, to be an important predictor variable. We conclude that government lockdowns are an extremely important de-densification strategy. Implications and questions for future research are discussed.

scholarly journals Forest road and public purpose investment

2019 ◽  
Vol 61 (4) ◽  
pp. 278-283
Author(s):  
Ewa Katarzyna Czech
Keyword(s):  
Social Interest ◽  
Nature Management ◽  
Local Authorities ◽  
Forest Roads ◽  
Mutual Cooperation ◽  
Forest Road ◽  
Public Purpose ◽  
Legal Problems ◽  
Legal Science ◽  
Administrative Courts

Abstract The functioning of forest districts in Poland should be based on their mutual cooperation with local authorities in order to achieve social interest, one of the examples of which is construction or reconstruction of roads. Due to the fact that achieving mutual investments encounter real legal problems arising from underspecified and unclear concepts, an assessment should be made of whether the construction and reconstruction of forest roads is a public purpose and also answer, what is a forest and forest road within the meaning of the provisions of the Act. It is necessary to present views of legal science and jurisdiction of administrative courts. The judicial direction of administrative courts is not beneficial for achieving investments; it does not even take into account that one of the investors’ purposes – forest districts – is nature management. Presenting the contrary argumentation to judicature positions should help courts make a proper assessment in the interpretation of provisions.

IDENTIFICATION OF CURVATURE RADIUS FOR CURVED SECTIONS ON FOREST ROADS IN THE PROCESS OF UTILISATION

2021 ◽  
Vol 14(63) (1) ◽  
pp. 47-56
Author(s):  
Ihor RUDKO ◽  
Borys BAKAY ◽  
Abdullah AKAY ◽  
Vasyl BARYLIAK ◽  
Stanislav HORZOV
Keyword(s):  
Technical Information ◽  
Radius Of Curvature ◽  
Curvature Radius ◽  
Forest Roads ◽  
Forest Road ◽  
Advantages And Disadvantages ◽  
Natural Production ◽  
Angle Deviation ◽  
Road Projects ◽  
Selection Of

This article reviews the problem of measuring the actual radius of curvature for curved sections of existing forest roads, as forestry enterprises require reliable technical information about the current conditions of operated transport networks. It was identified that at this moment, a selection of methods are used for measuring the radii of horizontal curved sections of roads, which have certain advantages and disadvantages in specific natural production conditions. For calculating the radius of curvature for auto forest road projects it is recommended to apply the method of measured angles by chord angle deviation, which is sufficiently accurate for engineering purposes and does not require usage of special high-precision equipment and tools.

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