The integration of the terrestrial and airborne laser scanning technologies in the semi-automated process of retrieving selected trees and forest stand parameters Integração das tecnologias terrestre e aerotransportada de scanner laser no processo semi

The traditional forest inventory based usually on thousands of the circle plots (radius = 12.62m; area 500 sq m) set in regular network. On every inventory plot, the basic tree and forest stand parameters have to be collected using calliper and hypsometer or even human eye (i.e. crown closure) as well. The modern multifunctional forestry models requires more and more: dens and accurate data to deliver as fast as possible the precise information on the amount of wood stock or other selected forest stand and tree parameters. One of the promising remote sensing technologies is LiDAR collecting the 3D point cloud data. The TLS technology is very precise and fast but is limited to relatively small areas like forest inventory plot. The ALS is more focused on wide-area data collection. Both technologies are complementary, therefore it is a need for the fusion of those two sources of information to enhance the accuracy of tree parameters and enlarge the results for the wide forest areas with statistical models. Paper presents a method of the TLS and ALS point cloud registration and transformation to one coordinate system. The goal of the data fusion was the semi-automatic extraction of the trees selected parameter (height, DBH, basal area, crown closure, base of crown, 2D and 3D tree crown surface) of the TR2 transect in Niepolomice Forest (Krakow, Poland). The results showed that the big potential of the enhancement of height and crown closure or base of the crown exists. Resumo O inventário florestal tradicional baseia-se normalmente em milhares de parcelas circulares (raio = 12,62 m, área 500 m²) dispostas em uma malha regular. Em cada parcela do inventário, os parâmetros básicos da árvore e do povoamento devem sercoletados usando suta e hipsômetro ou até mesmo o olho humano (densidade de copa). Os modernos modelos florestais multifuncionais requerem cada vez mais: dados densos e acurados para gerar o mais rápido possível a informação precisa da quantidade de estoque de madeira ou outro parâmetro selecionado do povoamento e da árvore. Uma das tecnologias promissoras de sensoriamento remoto é o LiDAR coletando os dados da nuvem de pontos 3D. A tecnologia TLS é muito precisa e rápida mas limitada a áreas relativamente pequenas como as parcelas de inventários florestais. A ALS é mais focada na coleta de dados em grandes áreas. Ambas as tecnologias são complementares portanto, é necessário para a fusão das duas fontes de informação aumentar a acurácia dos parâmetros de árvore e ampliar os resultados para grandes áreas florestais com modelos estatísticos. O artigo apresenta um método de registro e transformação do TLS e nuvem de pontos do ALS para um sistema de coordenadas. O objetivo da fusão dos dados foi a extração semi automática de parâmetros selecionados de árvores (altura, DAP, área basal, densidade de copa, base da copa, área 2D e 3D da copa da árvore) do transecto TR2 da Floresta Niepolomice (Krakow, Polônia). Os resultados mostraram que o grande potencial do aprimoramento da altura e do densidade de copa ou da base da copa existe

Understanding stress and health through the use of visual metaphor.

Psychological stress has become a topical issue, however, research on public understanding of stress is scarce. Metaphors are useful in translating science to the public. This research programme aimed to (1) explore lay and scientific understanding of stress, (2) identify the possible discrepancies between these perspectives, (3) develop a set of visual metaphors to help reduce those discrepancies, and (4) evaluate the metaphors. Three related studies were conducted using a mixed-methods approach. Study 1 involved individual interviews with the lay public (N=26) and stress experts (N=7) to explore their understanding of stress. Thematic analysis showed three main differences between the two perspectives. Lay people were less aware of the direct path between stress and health, emphasised individual responsibility for stress and coping, and were less familiar with the notion of eustress. Study 2 further explored lay conceptualisation of stress and its links to health. Twenty-four workshop participants built metaphorical LEGO models of stress. Analysis of the models and their verbal descriptions revealed a set of interlinked metaphors. Study 3, an on-line framing experiment, determined whether metaphors can be a useful tool for communicating scientific knowledge of stress. Metaphors identified in study 2 were used to create metaphorical descriptions of stress that provided information to help address the discrepancies between public and scientific perspectives identified in study 1. To test the metaphors, 603 participants assigned to one of six groups (four experimental and two control) answered the same pre and post questions. The results confirmed that metaphors can improve lay understanding of stress. This research programme showed that stress is a broad and complex concept. The findings have the potential to improve public access to scientific knowledge, enhance public understanding of stress, promote well-designed policies regarding stress management, and facilitate early diagnosis and treatment of stress-related health problems

The engagement of citizen in the management of urban forests: the LIFE URBANGREEN experience in Krakow

How do we make the ecosystem services of urban green areas and their benefits against climate change visible in real-time and even more effective? The cities of Krakow (Poland) and Rimini (Italy), in conjunction with their technological and scientific partners, addressed these topics in the EU-project LIFE URBANGREEN (LIFE17 CCA/IT/000079). This project developed innovative tools to assist the green area managers in their daily work and tested the effectiveness of these tools in the parks and streets of Rimini and Kraków.To ensure a broad understanding of the LIFE URBANGREEN project, along with the promotion of the importance and values of urban greenery, communication activities played a crucial role in engaging citizens to these topics. The most relevant communication activities the project carried out were: -creating awareness on urban forests among the target audience; -calculating and understanding the value of ecosystem services provided by trees and green areas for the two analysed cities;-communicating the environmental benefits and the overall importance of trees to the citizen.An important communication channel developed within the project is the web portal “Trees of Krakow and their benefits” (https://krakow.lifeurbangreen.eu). Here citizens can consult the main green areas of the city and retrieve information including the benefits of these areas in terms of Carbon assimilation, sequestration and storage, air amelioration and ambient air cooling. The data displayed on the portal are calculated in real-time, based on the spatial database of trees of Krakow trees, daily updated during maintenance activities.The data on ecosystem services are based on new algorithms developed during the LIFE URBANGREEEN Project, which consider the tree species, their age and size, the current weather condition and transpiration coefficients developed by the scientific component of the project with measurements on hundreds of trees over a period of three years.Citizens showed great interest in the project activities. The Public Portals of Krakow and Rimini are registering high consultation numbers, also one year after the end of the LIFE URBANGREEN project. Since the environmental benefits served by urban trees are calculated dynamically and updated every night, the values represented reflect the actual situation of the two cities

Smart water management in urban forests: the approach of life urbangreen

Urban trees are exposed to increasing levels of stress due to extended droughts. This affects not only the health of the trees, but also the quantity of benefits which trees serve to the city environment. A tool to monitor the tree vigor, based on their characteristics, but also on meteorological data and on scientific parameters to estimate the transpiration rate, can be very effective to detect trees under stress and help maintainers with instructions on irrigation needs

The impact of collective trauma on mental health psychology practitioners' wellbeing: Insights gained from Covid-19

Objective This study aimed at investigating how the pandemic, a collective trauma experience, affected the mental health and wellbeing of Mental Health Psychology Practitioners (MHPPs), along with the strategies employed to maintain positive wellbeing. Method An exploratory, qualitative research approach was taken, and semi-structured interview data was collected from nine MHPPs and analysed thematically. Results Three main themes were identified, consisting of two subthemes each, ranging from experiences of vicarious traumatisation, personal vs. professional identity issues, through to the strategies participants employ to maintain their wellbeing. Conclusion The need for training focusing on collectively traumatic experiences was highlighted by this study’s results. The development of targeted interventions and comprehensive training programmes are essential, including modules on self-care, resilience-building, and maintaining professional boundaries, as they can help this group of practitioners be less susceptible to occupational risks, resulting in better outcomes for both practitioners and their clients

‘Trapped under a tonne of rubble’: Using LEGO® to explore conceptual metaphors of psychological stress

Qualitative research methods have recently gained substantial ground in psychology. However, creative methods of data collection are still underused. Here we share our experiences of using LEGO® as a visual qualitative methodology to elicit metaphors of psychological stress. We highlight the value of this method through showcasing some examples of a research project that used LEGO® in a workshop to enable in-depth exploration about the lay conceptualisation of stress. LEGO® is an excellent tool for externalising and communicating thoughts about abstract concepts such as stress and coping. It is easy to use, attractive to participants and provides opportunities for sharing experiences and having fun. From the researcher’s perspective, LEGO® enables collection of enriched data which can shed new light on the research topic. It can be a useful visual methodological tool for enhancing and empowering qualitative researchers in many areas of psycholog

‘Ask a hundred people, you get a hundred definitions’: A comparison of lay and expert understanding of stress and its associations with health

The understanding an individual holds about stress can influence their appraisal of it and have implications for subsequent health, yet knowledge of such understanding is scarce. This study explored discrepancies between lay and expert understanding of stress and links made between stress and health. Twenty-six lay members of the local community aged 18–62 years, and seven expert stress researchers, participated in individual semi-structured interviews. Thematic analysis of the two datasets was conducted separately, then findings compared to identify similarities and differences between lay and scientific understanding. Whilst many similarities were identified, we found three important discrepancies: (i) Lay participants demonstrated a strong awareness of the indirect effects of stress on health via health behaviours; (ii) compared to experts, lay participants showed less awareness of a direct path between stress and physical health; (iii) lay participants showed less understanding of social determinants of stress and collective measures for stress management that went beyond individual responsibility. Discrepancies identified serve to highlight potential misunderstandings in lay conceptualisation of stress and its links with health. These findings have potential to facilitate the work of practitioners who serve as intermediaries to translate scientific knowledge into therapeutic benefit, through improved awareness and communication surrounding stress understanding

The use of remotely sensed data and polish NFI plots for prediction of growing stock volume using different predictive methods

Forest growing stock volume (GSV) is an important parameter in the context of forest resource management. National Forest Inventories (NFIs) are routinely used to estimate forest parameters, including GSV, for national or international reporting. Remotely sensed data are increasingly used as a source of auxiliary information for NFI data to improve the spatial precision of forest parameter estimates. In this study, we combine data from the NFI in Poland with satellite images of Landsat 7 and 3D point clouds collected with airborne laser scanning (ALS) technology to develop predictive models of GSV. We applied an area-based approach using 13,323 sample plots measured within the second cycle of the NFI in Poland (2010–2014) with poor positional accuracy from several to 15 m. Four different predictive approaches were evaluated: multiple linear regression, k-Nearest Neighbours, Random Forest and Deep Learning fully connected neural network. For each of these predictive methods, three sets of predictors were tested: ALS-derived, Landsat-derived and a combination of both. The developed models were validated at the stand level using field measurements from 360 reference forest stands. The best accuracy (RMSE% = 24.2%) and lowest systematic error (bias% = −2.2%) were obtained with a deep learning approach when both ALS- and Landsat-derived predictors were used. However, the differences between the evaluated predictive approaches were marginal when using the same set of predictor variables. Only a slight increase in model performance was observed when adding the Landsat-derived predictors to the ALS-derived ones. The obtained results showed that GSV can be predicted at the stand level with relatively low bias and reasonable accuracy for coniferous species, even using field sample plots with poor positional accuracy for model development. Our findings are especially important in the context of GSV prediction in areas where NFI data are available but the collection of accurate positions of field plots is not possible or justified because of economic reasons

‘We Don’t Let It Build Up’: Relationship Satisfaction and Well-Being Among Equal-Sharing, Role-Reversed and Semi-Traditional Parents

This mixed-methods study examined couples’ relationship quality, satisfaction and well-being by comparing semi-traditional, equal-sharing and role-reversed couples. Quantitative analysis involved 2813 parents (1380 men, 1433 women) with at least one child aged 11 or under who were primary caregivers, primary breadwinners or equal-sharers. Qualitative analysis drew on 60 in-depth interviews with 10 couples from each of the groups. Semi-traditional couples reported lower relationship quality and positive affect compared to other arrangements. Equal-sharers and role-reversed couples were more likely to discuss their frustrations and make conscious attempts to resolve them. Women in semi-traditional arrangements had lower levels of relationship quality and life satisfaction than women in equal-sharing and role-reversed arrangements. They were also more likely to report disagreements and frustrations. Caregiving parents also expressed lower levels of self-esteem compared to parents in breadwinning and equal-sharing roles. Our findings highlight how different breadwinning and caring responsibilities can impact parents’ well-being and relationship

The use of remotely sensed data and polish NFI plots for prediction of growing stock volume using different predictive methods

Forest growing stock volume (GSV) is an important parameter in the context of forest resource management. National Forest Inventories (NFIs) are routinely used to estimate forest parameters, including GSV, for national or international reporting. Remotely sensed data are increasingly used as a source of auxiliary information for NFI data to improve the spatial precision of forest parameter estimates. In this study, we combine data from the NFI in Poland with satellite images of Landsat 7 and 3D point clouds collected with airborne laser scanning (ALS) technology to develop predictive models of GSV. We applied an area-based approach using 13,323 sample plots measured within the second cycle of the NFI in Poland (2010–2014) with poor positional accuracy from several to 15 m. Four different predictive approaches were evaluated: multiple linear regression, k-Nearest Neighbours, Random Forest and Deep Learning fully connected neural network. For each of these predictive methods, three sets of predictors were tested: ALS-derived, Landsat-derived and a combination of both. The developed models were validated at the stand level using field measurements from 360 reference forest stands. The best accuracy (RMSE% = 24.2%) and lowest systematic error (bias% = −2.2%) were obtained with a deep learning approach when both ALS-and Landsat-derived predictors were used. However, the differences between the evaluated predictive approaches were marginal when using the same set of predictor variables. Only a slight increase in model performance was observed when adding the Landsat-derived predictors to the ALS-derived ones. The obtained results showed that GSV can be predicted at the stand level with relatively low bias and reasonable accuracy for coniferous species, even using field sample plots with poor positional accuracy for model development. Our findings are especially important in the context of GSV prediction in areas where NFI data are available but the collection of accurate positions of field plots is not possible or justified because of economic reasons