Environmental systems modelling with respect to the future

2006 ◽  
pp. 226-233
Author(s):  
A. Farkas
Keyword(s):  
Environmental Systems ◽  
The Future ◽  
Systems Modelling

Esri Association With Open Source

2018 ◽  
pp. 73-96
Author(s):  
Faridedin Cheraghi
Keyword(s):  
Information Systems ◽  
Open Source ◽  
Neutral Position ◽  
Geospatial Information ◽  
Systems Research ◽  
Environmental Systems ◽  
The Future ◽  
Long Time ◽  
Geospatial Information Systems ◽  
Research Institute

Everyone involved in geospatial information systems has heard of Environmental Systems Research Institute (Esri)company. Most people have tried ArcGIS software at least for one time. Esri has been the pioneer in this industry for a long time; it also defines the future of geospatial trends. In this chapter, the author adopts a neutral position to discuss the relation of Esri and open-source community. They cover almost every aspect where Esri and open source co-occur. Even the latest achievement of Esri, which is R-bridge, is discussed here. Going into the details of everything is not the goal of the chapter; however, a minimum description is provided for each section. Proper references are given to the reader for further study.

scholarly journals A modeler's guide to studying the resilience of social-technical-environmental systems

2021 ◽  
Author(s):  
Lea Tamberg ◽  
Jobst Heitzig ◽  
Jonathan Donges
Keyword(s):  
Sustainability Science ◽  
Specific Context ◽  
Response Options ◽  
Modelling Framework ◽  
Environmental Systems ◽  
Systems Modelling ◽  
Systematic Development ◽  
Research Questions ◽  
Adverse Influence ◽  
Modelling Process

<p>The concept of `resilience' is increasingly being applied in the study of social-technical-environmental systems in Earth system and sustainability science. However, the diversity of resilience concepts and a certain (sometimes intended) openness of proposed definitions can lead to misunderstandings and impede their application to systems modelling. We propose an approach that aims to ease communication as well as to support systematic development of research questions and models in the context of resilience. It can be applied independently of the modelling framework or underlying theory of choice. At the heart of this guideline is a checklist consisting of four questions to be answered: (i) Resilience of what? (ii) Resilience regarding what? (iii) Resilience against what? (iv) Resilience how? We refer to the answers to these resilience questions as the "system", the "sustainant", the "adverse influence", and the "response options". The term `sustainant' is a neologism describing the feature of the system (state, structure, function, pathway etc.) that should be maintained (or restored quickly enough) in order to call the system resilient.<br>The use of this proposed guideline is demonstrated for two application examples: fisheries, and the Amazon rainforest. The examples illustrate the diversity of possible answers to the checklist's questions as well as their benefits in structuring the modelling process. The guideline supports the modeller in communicating precisely what is actually meant by `resilience' in a specific context. This combination of freedom and precision could help to advance the resilience discourse by building a bridge between those demanding unambiguous definitions and those stressing the benefits of generality and flexibility of the resilience concept. </p>

Integrating Systems Modelling and Data Science

2016 ◽  
Vol 5 (1) ◽  
pp. 1-16 ◽  
Author(s):  
Erik Pruyt
Keyword(s):  
Big Data ◽  
System Dynamics ◽  
Data Science ◽  
Modelling And Simulation ◽  
System Dynamics Modelling ◽  
The Future ◽  
Systems Modelling ◽  
Dynamics Modelling

Although System Dynamics modelling is sometimes referred to as data-poor modelling, it often is –or could be– applied in a data-rich manner. However, more can be done in the era of ‘big data'. Big data refers here to situations with much more available data than was until recently manageable. The field of data science makes big(ger) data manageable. This paper provides a perspective on the future of System Dynamics with a prominent place for bigger data and data science. It discusses different approaches for dealing with bigger data. It reviews methods, techniques and tools for dealing with bigger data in System Dynamics, and sheds light on the modelling phases for which data science is most useful. Finally, it provides several examples of current applications in which big data, data science, and System Dynamics modelling and simulation are being merged.

The future of agri-environmental systems

2009 ◽  
pp. 180-195
Author(s):  
John Warren ◽  
Clare Lawson ◽  
Kenneth Belcher
Keyword(s):  
Environmental Systems ◽  
The Future

scholarly journals Marketing mechanisms in the activity of the regional innovation ecosystem

2021 ◽  
Vol 295 ◽  
pp. 01002
Author(s):  
Darya Lanskaya ◽  
Vladimir Ermolenko ◽  
Irina Mironova ◽  
Marina Todika ◽  
Anastasia Yakovlenko
Keyword(s):  
Life Cycle ◽  
Customer Satisfaction ◽  
Marketing Mix ◽  
Global Competition ◽  
Regional Innovation ◽  
Innovation Ecosystem ◽  
Stable Position ◽  
Environmental Systems ◽  
The Future ◽  
Marketing Methods

The paper examines marketing problems in the activity of the innovative ecosystem of the region, the main directions of world trends in the field of innovation. The study is aimed at adapting traditional marketing methods to the specifics of the innovation market in the context of conflicting global competition in order to achieve a stable position of innovative subjects in the market of innovations. The factors that determine the life cycle of innovative ecosystems and the reasons for the very modest results of their activities are identified. The evolution of the content of the marketing mix is considered and the future of innovation is associated with marketing transformations towards customer satisfaction and retention in the innovation market. Marketing in environmental systems has a multi-circuit and multi-layer configuration structure, focused on all the special actors of the innovation ecosystem.

scholarly journals Editorial: The inaugural issue of Socio-Environmental Systems Modelling (SESMO)

2020 ◽  
Vol 1 ◽  
pp. 16399
Author(s):  
Anthony Jakeman ◽  
Ioannis Athanasiadis ◽  
Marjolijn Haasnoot ◽  
Marco Janssen ◽  
Alexey Voinov
Keyword(s):  
Environmental Systems ◽  
Systems Modelling
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