Crop Protection Online—Weeds: A Case Study for Agricultural Decision Support Systems

2016 ◽  
pp. 303-320 ◽  
Author(s):  
Mette Sønderskov ◽  
Per Rydahl ◽  
Ole M. Bøjer ◽  
Jens Erik Jensen ◽  
Per Kudsk
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Crop Protection

Decision Support Systems in Crop Protection

1994 ◽  
Vol 23 (4) ◽  
pp. 281-285 ◽  
Author(s):  
Jonathan D. Knight ◽  
John D. Mumford
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Crop Protection ◽  
Expert Advice ◽  
Management Decision ◽  
Sufficient Information ◽  
Record Keeping ◽  
Pests And Diseases ◽  
The Right

All farmers and growers have at some time faced the decision of whether to control a pest in their crop. In order to make the correct decision the farmer needs access to, and an understanding of, sufficient information relevant to such pest problems. Decision support systems are able to help farmers make these difficult decisions by providing information in an easily understandable and quickly accessed form. The increasing use of computers by farmers for record-keeping and business management is putting the hardware necessary for the implementation of these systems onto more and more farms. The scarcity of expert advice, increasingly complex decisions and reduced economic margins all increase the importance of making the right pest management decision at the right time. It is against this background that decision support systems have an important role to play in the fight against losses caused by pests and diseases.

scholarly journals Designing Decision Support Systems with Interdisciplinary, International Teams: A Case Study of the Environment, Vulnerability, Decision, Technology Model

2020 ◽  
Author(s):  
Seamus Lombardo ◽  
Jack Reid ◽  
Katlyn Turner ◽  
Mulan Jiang ◽  
David Lagomasino ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems

scholarly journals Inclusive Design of Earth Observation Decision Support Systems for Environmental Governance: A Case Study of Lake Nokoué

2021 ◽  
Vol 3 ◽  
Author(s):  
Ufuoma Ovienmhada ◽  
Fohla Mouftaou ◽  
Danielle Wood
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Earth Observation ◽  
Inclusive Design ◽  
Observation Data ◽  
Climate Data ◽  
Technology Design ◽  
Data Services

Earth Observation (EO) data can enhance understanding of human-environmental systems for the creation of climate data services, or Decision Support Systems (DSS), to improve monitoring, prediction and mitigation of climate harm. However, EO data is not always incorporated into the workflow for decision-makers for a multitude of reasons including awareness, accessibility and collaboration models. The purpose of this study is to demonstrate a collaborative model that addresses historical power imbalances between communities. This paper highlights a case study of a climate harm mitigation DSS collaboration between the Space Enabled Research Group at the MIT Media Lab and Green Keeper Africa (GKA), an enterprise located in Benin. GKA addresses the management of an invasive plant species that threatens ecosystem health and economic activities on Lake Nokoué. They do this through a social entrepreneurship business model that aims to advance both economic empowerment and environmental health. In demonstrating a Space Enabled-GKA collaboration model that advances GKA's business aims, this study first considers several popular service and technology design methods and offer critiques of each method in terms of their ability to address inclusivity in complex systems. These critiques lead to the selection of the Systems Architecture Framework (SAF) as the technology design method for the case study. In the remainder of the paper, the SAF is applied to the case study to demonstrate how the framework coproduces knowledge that would inform a DSS with Earth Observation data. The paper offers several practical considerations and values related to epistemology, data collection, prioritization and methodology for performing inclusive design of climate data services.

Prevention of landfill pollution by multicriteria spatial decision support systems (MC-SDSS): development, implementation, and case study

2018 ◽  
Vol 25 (9) ◽  
pp. 8415-8431 ◽  
Author(s):  
Afshin Khoshand ◽  
Ali Hasani Bafrani ◽  
Mohammad Zahedipour ◽  
Seyed Ahmad Mirbagheri ◽  
Majid Ehtehsami
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Spatial Decision Support ◽  
Spatial Decision Support Systems

Rule-Based Ontology Decision Model

2016 ◽  
pp. 271-291
Keyword(s):  
Decision Support ◽  
Decision Support Systems ◽  
Decision Process ◽  
Support Systems ◽  
Rule Based ◽  
The Matrix ◽  
Markov Decision ◽  
Minimization Technique ◽  
Complex Decision

In chapter 7, we examined some selected case study applications of some decision support systems. Those considered were the matrix-based used in determining labour cost, sub-chaining method, linear regression, optimization (i.e. minimization) technique and Markov decision process. As earlier discussed, our focus will be on rule-based decision support systems. This is because rule-based systems are more encompassing and can easily be employed to deal with complex decision about construction activities. Hence in this chapter, an overview of rule-based decision system will be examined.

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