Evaluation of a large-scale forest scenario model in heterogeneous forests: a case study for Switzerland

2006 ◽  
Vol 36 (3) ◽  
pp. 671-683 ◽  
Author(s):  
Esther Thürig ◽  
Mart-Jan Schelhaas
Keyword(s):  
Large Scale ◽  
Management Practices ◽  
Stand Age ◽  
Growing Stock ◽  
Country Level ◽  
Scenario Model ◽  
European Forest ◽  
Mortality Function ◽  
Site Classes

Large-scale forest scenario models are widely used to simulate the development of forests and to compare the carbon balance estimates of different countries. However, as site variability in the application area often exceeds the variability in the calibration area, model validation is important. The aim of this study was to evaluate the European Forest Information Scenario model (EFISCEN). As Switzerland exhibits high spatial and climatic diversity, it was taken as a case study. The model output was compared to measured data in terms of initialization, estimation of growing stock, stand age, increment, management, and natural mortality. Comparisons were done at the country level, but also for regions and site classes. The results showed that the initialization procedure of EFISCEN works well for Switzerland. Moreover, EFISCEN accurately estimated the observed growing stock at the country level. On a regional level, major differences occurred. In particular, distribution of the harvesting amounts, mortality, and age-class distribution deviated considerably from empirical values. For future model applications, we therefore propose to define the required harvesting level not per country, but to specify it for smaller regions. Moreover, the EFISCEN simulations should be improved by refining the mortality function and by incorporating more flexibility in forest management practices.

scholarly journals LANDSCAPE DESIGN FOR SUSTAINABILITY AND ECOSYSTEM SERVICES IN AN URBAN ENVIRONMENT: CASE STUDY OF TEHRAN AND HIS KAN RIVER

2020 ◽  
Author(s):  
Ilda Vagge ◽  
◽  
Gioia Maddalena Gibelli ◽  
Alessio Gosetti Poli ◽  
◽  
...  
Keyword(s):  
Ecosystem Services ◽  
Large Scale ◽  
Management Practices ◽  
Natural Capital ◽  
Landscape Design ◽  
Green Spaces ◽  
Small Scale ◽  
Design For Sustainability ◽  
Holistic Method

The authors, with the awareness that climate change affects and changes the landscape, wanted to investigate how these changes are occurring within the metropolitan area of Tehran. Trying to keep a holistic method that embraces different disciplines, reasoning from large scale to small scale, the authors tried to study the main problems related to water scarcity and loss of green spaces. Subsequently they dedicated themselves to the identification of the present and missing ecosystem services, so that they could be used in the best possible way as tools for subsequent design choices. From the analysis obtained, the authors have created a masterplan with the desire to ensure a specific natural capital, the welfare of ecosystem services, and at the same time suggest good water management practices. It becomes essential to add an ecological accounting to the economic accounting, giving dignity to the natural system and the ecosystem services that derive from it.

scholarly journals Prediction of Knowledge Management for Success of Franchise Hospitality in a Post-Pandemic Economy

2020 ◽  
Vol 12 (20) ◽  
pp. 8755
Author(s):  
Hsiu-Chin Hsieh ◽  
Xuan-Huynh Nguyen ◽  
Tien-Chin Wang ◽  
Jen-Yao Lee
Keyword(s):  
Knowledge Management ◽  
Large Scale ◽  
Management Practices ◽  
Business Failure ◽  
Direct Result ◽  
Business Climate ◽  
Global Business ◽  
Priority Weights ◽  
Novel Coronavirus

Due to its unpredictability, the novel coronavirus (COVID-19) pandemic has changed the global business climate and commercial management practices in unprecedented ways. As a direct result of the pandemic, the hospitality and tourism sectors have shut down, and business failure rates have occurred exponentially. The franchise hospitality industry has experienced significant impact and challenged a basic understanding of knowledge management (KM) implementation in the face of the COVID-19 outbreak. A strategic KM implementation practice can not only guide a large-scale operation, but also adjust an organization’s performance and competitiveness. The purpose of this study is to examine the influential criteria of success through effective KM implementation and to predict the probability of successful KM in a post-pandemic era. The conceptual framework for KM applies an analytic hierarchical prediction model reliant upon consistent fuzzy preference relations to assist the franchise hospitality sector’s consciousness of the influential criteria. An empirical case study is used to apply pairwise comparisons used to determine the priority weights and two possible outcomes. The case study will assist franchise organizations to analyze whether or not to implement KM, interdict application, or adopt revised actions. This assistance will enhance the success possibility of KM implementation within such a crisis environment. This study uses a case setting by assessing 15 franchises hospitality experts’ opinions in Taiwan relevant to KM implementation.

scholarly journals Expansion of US wood pellet industry points to positive trends but the need for continued monitoring

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Francisco X. Aguilar ◽  
Ashkan Mirzaee ◽  
Ronald G. McGarvey ◽  
Stephen R. Shifley ◽  
Dallas Burtraw
Keyword(s):  
Large Scale ◽  
Management Practices ◽  
Carbon Stocks ◽  
The European Union ◽  
Wood Fibers ◽  
Wood Pellets ◽  
Wood Pellet ◽  
Growing Stock ◽  
Dead Trees ◽  
The Us

Abstract Implementation of the European Union Renewable Energy Directive has triggered exponential growth in trading of pelletized wood fibers. Over 18 million tons of wood pellets were traded by EU member countries in 2018 of which a third were imported from the US. Concerns exist about negative impacts on US forests but systematic assessments are currently lacking. We assessed variability in fundamental attributes for timberland structure and carbon stocks within 123 procurement landscapes of wood pellet mills derived from over 38 thousand forest inventory plots in the eastern US from 2005 to 2017. We found more carbon stocks in live trees, but a fewer number of standing-dead trees, associated with the annual operation of large-scale wood pellet mills. In the US coastal southeast—where US pellet exports to the EU originate—there were fewer live and growing-stock trees and less carbon in soils with every year of milling operation than in the rest of the eastern US—which supplies the domestic market. Greater overlap of mills’ procurement areas exhibited discernible increments across selected carbon stocks. These trends likely reflect more intensive land management practices. Localized forest impacts associated with the wood pellet industry should continue to be monitored.

scholarly journals How Knowledge Management helped Knowledge Intensive Business Services in Surviving COVID-19 and Creating Resiliency for New Normal: A Case Study of a GRC Training Firm in Indonesia

2021 ◽  
Vol 1 (5) ◽  
pp. 47-54
Author(s):  
Ray Antonio
Keyword(s):  
Knowledge Management ◽  
Large Scale ◽  
Management Practices ◽  
Business Services ◽  
Case Study Methodology ◽  
New Normal ◽  
Knowledge Intensive Business Services ◽  
Knowledge Intensive ◽  
Business Sectors

Since early 2020, COVID-19 pandemic has attacked many business sectors in many countries. In Indonesia, the government reacts to this situation by issuing several regulations, one of which is the large-scale social restrictions (PSBB) regulation. This regulation affects many business sectors, including Knowledge Intensive Business Services (KIBS) sectors. KIBS sectors have been developing quickly, especially in developing countries like Indonesia. Knowledge plays a crucial part for KIBS firms as these firms depend heavily on their workers’ knowledge. In this study, Lembaga Pelatihan Kerja Mitra Kalyana Sejahtera (LPK MKS) is being used as the research object for conducting the research. LPK MKS is a Governance, Risk, and Compliance (GRC) training firm, which included as one of KIBS business sectors. This study uses case study methodology by focusing on obtaining deep understandings about the knowledge management practices in KIBS training firm. The author obtains all the necessary data through in-depth qualitative interviews and secondary data. From the collected and analysed data, LPK MKS has implemented all of the success factors for managing knowledge. While the implementation of leadership and ICT are more notable, the implementation in organisational infrastructure is still not ideal. Nonetheless, the overall implementations of knowledge management help the firm in surviving the COVID-19 pandemic era and creating resiliency to face the new normal condition.

Adding natural disturbances to a large-scale forest scenario model and a case study for Switzerland

2002 ◽  
Vol 167 (1-3) ◽  
pp. 13-26 ◽  
Author(s):  
M.J Schelhaas ◽  
G.J Nabuurs ◽  
M Sonntag ◽  
A Pussinen
Keyword(s):  
Large Scale ◽  
Natural Disturbances ◽  
Scenario Model

scholarly journals Global sales and operations planning: A multinational manufacturing company perspective

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0257572
Author(s):  
Marcelo Xavier Seeling ◽  
Tobias Kreuter ◽  
Luiz Felipe Scavarda ◽  
Antônio Márcio Tavares Thomé ◽  
Bernd Hellingrath
Keyword(s):  
Large Scale ◽  
Management Practices ◽  
Inductive Logic ◽  
Real Life ◽  
Global Perspective ◽  
Local Approach ◽  
Operations Planning ◽  
Manufacturing Company ◽  
Research Findings

The purpose of this paper is to analyse the global Sales and Operations Planning (S&OP) process and investigate the steps to support consolidated business planning in worldwide operations and large-scale supply chains. The paper conducts a case study at a multinational manufacturing company applying an abductive approach. It combines the deductive logic from theory and the inductive logic from field observation in an attempt to elaborate further on theory on global S&OP. The analysis is structured and guided by a novel framework for global S&OP, which is developed based on the theoretical background and the case study findings. The research findings characterise the S&OP process for global operations and identify challenges related to the need to synchronise the subsidiaries’ S&OP efforts worldwide to deal with different contingencies of these subsidiaries, and to manage and analyse a large amount of information gathered. The research reveals how the subsidiaries’ performance is analysed by top executives along the global S&OP process, feeding strategic initiatives in the organisation and identifying business opportunities like benchmarking among subsidiaries, synergies with other management practices, and global gains. This paper offers a novel investigation of the global steps on S&OP in a real-life setting, offering a well-documented characterisation of the process that goes beyond the traditional local approach. Moreover, it is the first study to reveal challenges and expected outcomes of such a global perspective for S&OP. The theoretical advancements of S&OP research offered herein aid scholars, opening avenues for middle-range theorising, highlighting the cross-disciplinary nature of the domain, and discussing the use of concepts from related disciplines like Economics, Psychology, and Information Systems. The research findings can also assist executives, especially from multinational manufacturers, in their efforts to consolidate global planning.

scholarly journals Appraisal of the Sentinel-1 & 2 use in a large-scale wildfire assessment: A case study from Portugal’s fires of 2017

2019 ◽  
Author(s):  
Alexander R. Brown ◽  
George Petropoulos ◽  
Konstantinos P. Ferentinos
Keyword(s):  
Forest Fires ◽  
Large Scale ◽  
Burn Severity ◽  
Support Vector ◽  
Burnt Area ◽  
Vector Machines ◽  
European Forest ◽  
Burnt Areas ◽  
Sentinel 2

The recent launch of Sentinel missions offers a unique opportunity to assess the impacts of wildfires at higher spatial and spectral resolution provided by those Earth Observing systems. Herein, an assessment of the Sentinel-1 & 2 to map burnt areas has been conducted. Initially the use of Sentinel-2 solely was explored, and then in combination with Sentinel-1 and derived radiometric indices. As a case study, the large wildfire occurred in Pedrógão Grande, Portugal in 2017 was used. Burnt area estimates from the European Forest Fires Information System (EFFIS) were used as reference. Burnt area was delineated using the Maximum Likelihood (ML) and Support Vector Machines (SVMs) classifiers, and two multi-index methods. Following this, burn severity was assessed using SVMs and Artificial Neural Networks (ANNs), again for both standalone Sentinel-2 data and in combination with Sentinel-1 and spectral indices. Soil erosion predictions were evaluated using the Revised Universal Soil Loss Equation (RUSLE) model. The effect of the land cover derived from CORINE operational product was also evaluated across the burnt area and severity maps. SVMs produced the most accurate burnt area map, resulting a 94.8% overall accuracy and a Kappa coefficient of 0.90. SVMs also achieved the highest accuracy in burn severity levels estimation, with an overall accuracy of 77.9% and a kappa of 0.710. From an algorithmic perspective, implementation of the techniques applied herein, is based on EO imagery analysis provided nowadays globally at no cost. It is also robust and adaptable, being potentially integrated with other high EO data available. All in all, our study contributes to the understanding of Mediterranean landscape dynamics and corroborates the usefulness of Sentinels data in wildfire studies.

scholarly journals Appraisal of the Sentinel-1 & 2 use in a large-scale wildfire assessment: A case study from Portugal's fires of 2017

2020 ◽  
Author(s):  
Alexander R. Brown ◽  
George Petropoulos ◽  
Konstantinos P. Ferentinos
Keyword(s):  
Large Scale ◽  
Kappa Coefficient ◽  
Support Vector ◽  
Spectral Indices ◽  
Burnt Area ◽  
Vector Machines ◽  
European Forest ◽  
Burnt Areas ◽  
Sentinel 2

The recent launch of Sentinel missions offers a unique opportunity to assess the impacts of wildfires at higherspatial and spectral resolution provided by those Earth Observing (EO) systems. Herein, an assessment of theSentinel-1 & 2 to map burnt areas has been conducted. Initially the use of Sentinel-2 solely was explored, andthen in combination with Sentinel-1 and derived radiometric indices. As a case study, the large wildfire occurredin Pedrógão Grande, Portugal in 2017 was used. Burnt area estimates from the European Forest FiresInformation System (EFFIS) were used as reference. Burnt area was delineated using the Maximum Likelihood(ML) and Support Vector Machines (SVMs) classifiers, and two multi-index methods. Following this, burn severitywas assessed using SVMs and Artificial Neural Networks (ANNs), again for both standalone Sentinel-2 dataand in combination with Sentinel-1 and spectral indices. Soil erosion predictions were evaluated using theRevised Universal Soil Loss Equation (RUSLE) model. The effect of the land cover derived from CORINE operationalproduct was also evaluated across the burnt area and severity maps. SVMs produced the most accurateburnt area map, resulting a 94.8% overall accuracy and a Kappa coefficient of 0.90. SVMs also achieved thehighest accuracy in burn severity levels estimation, with an overall accuracy of 77.9% and a kappa of 0.710.From an algorithmic perspective, implementation of the techniques applied herein, is based on EO imageryanalysis provided nowadays globally at no cost. It is also robust and adaptable, being potentially integrated withother high EO data available. All in all, our study contributes to the understanding of Mediterranean landscapedynamics and corroborates the usefulness of Sentinels data in wildfire studies.

scholarly journals The challenges of the coming mass vaccination and exit strategy in prevention and control of COVID-19, a modelling study

2020 ◽  
Author(s):  
Biao Tang ◽  
Peiyu Liu ◽  
Jie Yang ◽  
Jianhong Wu ◽  
Xiao Yanni ◽  
...  
Keyword(s):  
Vaccination Coverage ◽  
Prevention And Control ◽  
Large Scale ◽  
Real Data ◽  
Vaccination Program ◽  
Vaccination Rates ◽  
Country Level ◽  
And Control ◽  
Subsequent Wave

AbstractWith success in the development of COVID-19 vaccines, it is urgent and challenging to analyse how the coming large-scale vaccination in the population and the growing public desire of relaxation of non-pharmaceutical interventions (NPIs) interact to impact the prevention and control of the COVID-19 pandemic. Using mathematical models, we focus on two aspects: 1) how the vaccination program should be designed to balance the dynamic exit of NPIs; 2) how much the vaccination coverage is needed to avoid a second wave of the epidemics when the NPIs exit in stages. We address this issue globally, and take six countries--China, Brazil, Indonesia, Russia, UK, and US—in our case study. We showed that a dynamic vaccination program in three stages can be an effective approach to balance the dynamic exit of the NPIs in terms of mitigating the epidemics. The vaccination rates and the accumulative vaccination coverage in these countries are estimated by fitting the model to the real data. We observed that the required effective vaccination coverages are greatly different to balance the dynamic exit of NPIs in these countries, providing a quantitative criterion for the requirement of an integrative package of NPIs. We predicted the epidemics under different vaccination rates for these countries, and showed that the vaccination can significantly decrease the peak value of a future wave. Furthermore, we found that a lower vaccination coverage can result in a subsequent wave once the NPIs exit. Therefore, there is a critical (minimum) vaccination coverage, depending on effectiveness of NPIs to avoid a subsequent wave. We estimated the critical vaccination coverages for China, Brazil, and Indonesia under different scenarios. In conclusion, we quantitatively showed that the dynamic vaccination program can be the effective approach to supplement or even eventually replace NPIs in mitigating the epidemics and avoiding future waves, and we suggest that country level-based exit strategies of the NPIs should be considered, according to the possible quarantine rate and testing ability, and the accessibility, affordability and efficiency of the vaccines.

scholarly journals Regional aspects of modelling burned areas in Europe

2016 ◽  
Vol 25 (8) ◽  
pp. 811 ◽  
Author(s):  
Andrey Krasovskii ◽  
Nikolay Khabarov ◽  
Mirco Migliavacca ◽  
Florian Kraxner ◽  
Michael Obersteiner
Keyword(s):  
Large Scale ◽  
European Countries ◽  
Dramatic Improvement ◽  
Fire Emissions ◽  
Burned Areas ◽  
Country Level ◽  
Fire Modelling ◽  
European Forest ◽  
Recent Version ◽  
Good Agreement

This paper presents a series of improvements to the quantitative modelling of burned areas in Europe under historical climate. The Standalone Fire Model (SFM) based on a state-of-the-art large scale mechanistic fire modelling algorithm is used to reproduce historical burned areas reported in the two publicly available datasets – European Forest Fire Information System (EFFIS) and Global Fire Emissions Database (GFED). The most recent versions of these sources allow a broader validation of SFM’s modelled burned areas at a country level. Our analysis is carried out for the years 2000–2008 for 17 European countries utilising both EFFIS and GFED datasets for model benchmarking. We suggest improving the original model by modifying the fire probability function reflecting fuel moisture. This modification allows for a dramatic improvement of accuracy in modelled burned areas for a range of European countries. We also explore in detail a pixel-level parametrisation of firefighting efficiency in SFM along with modifications of the biomass map. In comparison with the aggregated country-level approach, the advantages of the finer calibration are quite minor for the most recent version of the GFED dataset. Overall, the annual burned areas modelled by this improved SFM version are in good agreement with historical observations.

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