scholarly journals GEOSPATIAL ASSESSMENT OF HUMAN-WILDLIFE-ENVIRONMENT INTERACTIONS FOR SPATIAL DECISION SUPPORT

2021 ◽  
Vol XLIII-B4-2021 ◽  
pp. 281-285
Author(s):  
M. Madden ◽  
M. Karidozo ◽  
W. Langbauer ◽  
F. Osborn ◽  
A. Presotto ◽  
...  
Keyword(s):  
Decision Support ◽  
Climatic Factors ◽  
Spatial Decision Support ◽  
African Elephants ◽  
Resource Managers ◽  
Access To Water ◽  
Global Concern ◽  
Spatio Temporal ◽  
Conservation Organizations ◽  
Victoria Falls

Abstract. Human-Elephant Conflict (HEC) is a global concern that requires geospatial data collection, analysis and geovisualization for decision support and mitigation. Bull African elephants, (Loxodonata africana), are often responsible for breaking fences, raiding crops and causing economic hardship in local communities in Botswana, Zimbabwe and Zambia. Methods for monitoring and understanding elephant movements are needed to mitigate conflict, find ways for coexistence and secure the future of Africa’s elephant populations. Researchers from academia and conservation organizations are partnering with decision makers and scientists of the Zimbabwe Department of National Park and Wild Life Management (PWMA) to track the movement of 15 bull elephants in the general area of Victoria Falls to analyse spatio-temporal patterns of elephant behaviour related to climatic factors, habitat conditions and changing land uses. Spatial decision support for local famers, resource managers and planners will assist in avoiding agricultural expansion and urban development that coincides with elephant corridors and access to water resources.

Flexible Spatial Decision-Making and Support

2011 ◽  
pp. 614-636
Author(s):  
Shan Gao ◽  
David Sundaram
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Spatial Decision Support ◽  
Spatial Decision Support Systems ◽  
Location Allocation ◽  
Information Tools ◽  
Spatial Decision Making ◽  
Spatio Temporal

Spatial decision-making is a key aspect of human behaviour. Spatial decision support systems support spatial decision-making processes by integrating required information, tools, models and technology in a user-friendly manner. While current spatial decision support systems fulfil their specific objectives, they fail to address many of the requirements for effective spatial problem solving, as they are inflexible, complex to use and often domain-specific. This research blends together several relevant disciplines to overcome the problems identified in various areas of spatial decision support. We proposed a generic spatial decision-making process and a domain-independent spatial decision support system (SDSS) framework and architecture to support the process. We also developed a flexible SDSS to demonstrate an environment in which decision makers can utilize various tools and explore different scenarios to derive a decision. The use of the system is demonstrated in a number of real scenarios across location, allocation, routing, layout, and spatio-temporal problems.

Flexible Spatial Decision-Making and Support

2010 ◽  
pp. 532-555
Author(s):  
Shan Gao ◽  
David Sundaram
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Spatial Decision Support ◽  
Spatial Decision Support Systems ◽  
Location Allocation ◽  
Information Tools ◽  
Spatial Decision Making ◽  
Spatio Temporal

Spatial decision-making is a key aspect of human behaviour. Spatial decision support systems support spatial decision-making processes by integrating required information, tools, models and technology in a user-friendly manner. While current spatial decision support systems fulfil their specific objectives, they fail to address many of the requirements for effective spatial problem solving, as they are inflexible, complex to use and often domain-specific. This research blends together several relevant disciplines to overcome the problems identified in various areas of spatial decision support. We proposed a generic spatial decision-making process and a domain-independent spatial decision support system (SDSS) framework and architecture to support the process. We also developed a flexible SDSS to demonstrate an environment in which decision makers can utilize various tools and explore different scenarios to derive a decision. The use of the system is demonstrated in a number of real scenarios across location, allocation, routing, layout, and spatio-temporal problems.

Flexible Spatial Decision-Making and Support

2011 ◽  
pp. 153-183 ◽  
Author(s):  
Shan Gao ◽  
David Sundaram
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support Systems ◽  
Support Systems ◽  
Spatial Decision Support ◽  
Spatial Decision Support Systems ◽  
Location Allocation ◽  
Information Tools ◽  
Spatial Decision Making ◽  
Spatio Temporal

Spatial decision-making is a key aspect of human behaviour. Spatial decision support systems support spatial decision-making processes by integrating required information, tools, models and technology in a user-friendly manner. While current spatial decision support systems fulfil their specific objectives, they fail to address many of the requirements for effective spatial problem solving, as they are inflexible, complex to use and often domain-specific. This research blends together several relevant disciplines to overcome the problems identified in various areas of spatial decision support. We proposed a generic spatial decision-making process and a domain-independent spatial decision support system (SDSS) framework and architecture to support the process. We also developed a flexible SDSS to demonstrate an environment in which decision makers can utilize various tools and explore different scenarios to derive a decision. The use of the system is demonstrated in a number of real scenarios across location, allocation, routing, layout, and spatio-temporal problems.

Spatial Decision Support for Gas Pipe Maintenance

2006 ◽  
Vol 15 (2-3) ◽  
pp. 161-179
Author(s):  
Kathrin Kirchner ◽  
Johannes Ruhland
Keyword(s):  
Decision Support ◽  
Spatial Decision Support

Seabird bycatch vulnerability in pelagic longline fisheries based on modelling of a long-term dataset

2021 ◽  
pp. 1-16
Author(s):  
CAN ZHOU ◽  
NIGEL BROTHERS
Keyword(s):  
Capture Event ◽  
Retrieval Rate ◽  
Competitive Environments ◽  
Global Concern ◽  
Competitive Species ◽  
Spatio Temporal ◽  
Longline Fisheries ◽  
Pelagic Longline

Summary The incidental mortality of seabirds in fisheries remains a serious global concern. Obtaining unbiased and accurate estimates of bycatch rates is a priority for seabird bycatch mitigation and demographic research. For measuring the capture risk of seabird interactions in fisheries, the rate of carcass retrieval from hauled gear is commonly used. However, reliability can be limited by a lack of direct capture observations and the substantial pre-haul bycatch losses known to occur, meaning incidence of seabird bycatch is underestimated. To solve this problem, a new measure (bycatch vulnerability) that links an observed interaction directly to the underlying capture event is proposed to represent the capture risk of fishery interactions by seabirds. The new measure is not affected by subsequent bycatch loss. To illustrate how to estimate and analyse bycatch vulnerability, a case study based on a long-term dataset of seabird interactions and capture confirmation is provided. Bayesian modelling and hypothesis testing were conducted to identify important bycatch risk factors. Competition was found to play a central role in determining seabird bycatch vulnerability. More competitive environments were riskier for seabirds, and larger and thus more competitive species were more at risk than smaller sized and less competitive species. Species foraging behaviour also played a role. On the other hand, no additional effect of physical oceanic condition and spatio-temporal factors on bycatch vulnerability was detected. Bycatch vulnerability is recommended as a replacement for the commonly used bycatch rate or carcass retrieval rate to measure the capture risk of an interaction. Combined with a normalized contact rate, bycatch vulnerability offers an unbiased estimate of seabird bycatch rate in pelagic longline fisheries.

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