Using basic geographic information systems functionality to support sustainable forest management decision making and post-decision assessments

Treesearch

Ronald E. McRoberts; R. James Barbour; Krista M. Gebert; Greg C. Liknes; Mark D. Nelson; Dacia M. Meneguzzo; et al.

2006-01-01

Sustainable management of natural resources requires informed decision making and post-decision assessments of the results of those decisions. Increasingly, both activities rely on analyses of spatial data in the forms of maps and digital data layers. Fortunately, a variety of supporting maps and data layers rapidly are becoming available. Unfortunately, however, user-...

Assessing Sustainability of Coral Reef Ecosystem Services using a Spatially-Explicit Decision Support Tool

EPA Science Inventory

Forecasting and communicating the potential outcomes of decision options requires support tools that aid in evaluating alternative scenarios in a user-friendly context and that highlight variables relevant to the decision options and valuable stakeholders. Envision is a GIS-base...

Application of GIS in foreign direct investment decision support system

NASA Astrophysics Data System (ADS)

Zhou, Jianlan; Sun, Koumei

2007-06-01

It is important to make decisions on how to attract foreign direct investment (FDI) to China and know how the inequality of FDI introduction by locational different provinces. Following background descriptions on China's FDI economic environments and FDI-related policies, this paper demonstrates the uses of geographical information system (GIS) and multi-criterion decision-making (MCDM) framework in solving a spatial multi-objective problem of evaluating and ranking China's provinces for FDI introduction. It implements a foreign direct investment decision support system, which reveals the main determinants of FDI in China and gives some results of regional geographical analysis over spatial data.

Publically accessible decision support system of the spatially referenced regressions on watershed attributes (SPARROW) model and model enhancements in South Carolina

Treesearch

Celeste Journey; Anne B. Hoos; David E. Ladd; John W. brakebill; Richard A. Smith

2016-01-01

The U.S. Geological Survey (USGS) National Water Quality Assessment program has developed a web-based decision support system (DSS) to provide free public access to the steady-stateSPAtially Referenced Regressions On Watershed attributes (SPARROW) model simulation results on nutrient conditions in streams and rivers and to offer scenario testing capabilities for...

Uncertainty management, spatial and temporal reasoning, and validation of intelligent environmental decision support systems

USGS Publications Warehouse

Sànchez-Marrè, Miquel; Gilbert, Karina; Sojda, Rick S.; Steyer, Jean Philippe; Struss, Peter; Rodríguez-Roda, Ignasi; Voinov, A.A.; Jakeman, A.J.; Rizzoli, A.E.

2006-01-01

There are inherent open problems arising when developing and running Intelligent Environmental Decision Support Systems (IEDSS). During daily operation of IEDSS several open challenge problems appear. The uncertainty of data being processed is intrinsic to the environmental system, which is being monitored by several on-line sensors and off-line data. Thus, anomalous data values at data gathering level or even uncertain reasoning process at later levels such as in diagnosis or decision support or planning can lead the environmental process to unsafe critical operation states. At diagnosis level or even at decision support level or planning level, spatial reasoning or temporal reasoning or both aspects can influence the reasoning processes undertaken by the IEDSS. Most of Environmental systems must take into account the spatial relationships between the environmental goal area and the nearby environmental areas and the temporal relationships between the current state and the past states of the environmental system to state accurate and reliable assertions to be used within the diagnosis process or decision support process or planning process. Finally, a related issue is a crucial point: are really reliable and safe the decisions proposed by the IEDSS? Are we sure about the goodness and performance of proposed solutions? How can we ensure a correct evaluation of the IEDSS? Main goal of this paper is to analyse these four issues, review some possible approaches and techniques to cope with them, and study new trends for future research within the IEDSS field.

Spatial decision support system to evaluate crop residue energy potential by anaerobic digestion.

PubMed

Escalante, Humberto; Castro, Liliana; Gauthier-Maradei, Paola; Rodríguez De La Vega, Reynel

2016-11-01

Implementing anaerobic digestion (AD) in energy production from crop residues requires development of decision tools to assess its feasibility and sustainability. A spatial decision support system (SDSS) was constructed to assist decision makers to select appropriate feedstock according to biomethanation potential, identify the most suitable location for biogas facilities, determine optimum plant capacity and supply chain, and evaluate associated risks and costs. SDSS involves a spatially explicit analysis, fuzzy multi-criteria analysis, and statistical and optimization models. The tool was validated on seven crop residues located in Santander, Colombia. For example, fique bagasse generates about 0.21millionm(3)CH4year(-1) (0.329m(3)CH4kg(-1) volatile solids) with a minimum profitable plant of about 2000tonyear(-1) and an internal rate of return of 10.5%. SDSS can be applied to evaluate other biomass resources, availability periods, and co-digestion potential. Copyright © 2016. Published by Elsevier Ltd.

SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING AND RISK ASSESSMENT (SLIDE PRESENTATION)

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

MEETING IN CHICAGO: SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING, AND ENVIRONMENTAL RISK ASSESSMENT

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

MEETING IN CZECH REPUBLIC: SADA: A FREEWARE DECISION SUPPORT TOOL INTEGRATING GIS, SAMPLE DESIGN, SPATIAL MODELING, AND RISK ASSESSMENT

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

Maritime Spatial Planning supported by systematic site selection: Applying Marxan for offshore wind power in the western Baltic Sea

PubMed Central

Dahl, Karsten; Mohn, Christian

2018-01-01

The development of offshore wind energy and other competing interests in sea space are a major incentive for designating marine and coastal areas for specific human activities. Maritime Spatial Planning (MSP) considers human activities at sea in a more integrated way by analysing and designating spatial and temporal distributions of human activities based on ecological, economic and social targets. However, specific tools supporting spatial decisions at sea incorporating all relevant sectors are rarely adopted. The decision support tool Marxan is traditionally used for systematic selection and designation of nature protection and conservation areas. In this study, Marxan was applied as a support tool to identify suitable sites for offshore wind power in the pilot area Pomeranian Bight / Arkona Basin in the western Baltic Sea. The software was successfully tested and scenarios were developed that support the sites indicated in existing national plans, but also show options for alternative developments of offshore wind power in the Pomeranian Bight / Arkona Basin area. PMID:29543878

Creating a spatial multi-criteria decision support system for energy related integrated environmental impact assessment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wanderer, Thomas, E-mail: thomas.wanderer@dlr.de; Herle, Stefan, E-mail: stefan.herle@rwth-aachen.de

2015-04-15

By their spatially very distributed nature, profitability and impacts of renewable energy resources are highly correlated with the geographic locations of power plant deployments. A web-based Spatial Decision Support System (SDSS) based on a Multi-Criteria Decision Analysis (MCDA) approach has been implemented for identifying preferable locations for solar power plants based on user preferences. The designated areas found serve for the input scenario development for a subsequent integrated Environmental Impact Assessment. The capabilities of the SDSS service get showcased for Concentrated Solar Power (CSP) plants in the region of Andalusia, Spain. The resulting spatial patterns of possible power plant sitesmore » are an important input to the procedural chain of assessing impacts of renewable energies in an integrated effort. The applied methodology and the implemented SDSS are applicable for other renewable technologies as well. - Highlights: • The proposed tool facilitates well-founded CSP plant siting decisions. • Spatial MCDA methods are implemented in a WebGIS environment. • GIS-based SDSS can contribute to a modern integrated impact assessment workflow. • The conducted case study proves the suitability of the methodology.« less

A GIS-based Spatial Decision Support System for environmentally valuable areas in the context of sustainable development of Poland

NASA Astrophysics Data System (ADS)

Kubacka, Marta

2013-04-01

The issue of spatial development, and thus proper environmental management and protection at naturally valuable areas is today considered a major hazard to the stability of the World ecological system. The increasing demand for areas with substantial environmental and landscape assets, incorrect spatial development, improper implementation of law as well as low citizen awareness bring about significant risk of irrevocable loss of naturally valuable areas. The elaboration of a Decision Support System in the form of collection of spatial data will facilitate solving complex problems concerning spatial development. The elaboration of a model utilizing a number of IT tools will boost the effectiveness of taking spatial decisions by decision-makers. Proper spatial data management becomes today a key element in management based on knowledge, namely sustainable development. Decision Support Systems are definied as model-based sets of procedures for processing data and judgments to assist a manager in his decision-making. The main purpose of the project was to elaborate the spatial decision support system for the Sieraków Landscape Park. A landscape park in Poland comprises a protected area due to environmental, historic and cultural values as well as landscape assets for the purpose of maintaining and popularizing these values in the conditions of sustainable development. It also defines the forms of protected area management and introduces bans concerning activity at these areas by means of the obligation to prepare and implement environmental protection plans by a director of the complex of landscape parks. As opposed to national parks and reserves, natural landscape parks are not the areas free from economic activity, thus agricultural lands, forest lands and other real properties located within the boundaries of natural landscape parks are subject to economic utilization Research area was subject to the analysis with respect to the implementation of investment actions consisting mainly in the agricultural economy. Versatile relief, diversified geological formations as well as the depth of depositing ground water and the risk of flooding have impact on diversified possibilities of the land use. Intensive agricultural economy at large field area and forestry constitute the major human activity at the area of the Park. The criteria which may be in the form of factors (e.g. soil with much agricultural suitability or very low slopes) or limitations (e.g. soils with little agricultural suitability, forest areas in close vicinity of water bodies) constitute the grounds for taking a decision on determining the areas for agricultural economy. The thesis presents the possibilities which Geographic Information Systems provide at the stage of taking spatial decisions at environmentally valuable areas. The pressure on environmentally valuable areas is growing all over the world and it may be assumed that spatial conflicts between the development of agricultural areas and the natural environment will intensify. Spatial planning is the best possibilities of reducing and mitigating this pressure. This process should take into consideration the provisions of the European Landscape Convention which is the basic instrument for landscape preservation and nature protection.

Toward the Modularization of Decision Support Systems

NASA Astrophysics Data System (ADS)

Raskin, R. G.

2009-12-01

Decision support systems are typically developed entirely from scratch without the use of modular components. This “stovepiped” approach is inefficient and costly because it prevents a developer from leveraging the data, models, tools, and services of other developers. Even when a decision support component is made available, it is difficult to know what problem it solves, how it relates to other components, or even that the component exists, The Spatial Decision Support (SDS) Consortium was formed in 2008 to organize the body of knowledge in SDS within a common portal. The portal identifies the canonical steps in the decision process and enables decision support components to be registered, categorized, and searched. This presentation describes how a decision support system can be assembled from modular models, data, tools and services, based on the needs of the Earth science application.

CHANGES SDSS: the development of a Spatial Decision Support System for analysing changing hydro-meteorological risk

NASA Astrophysics Data System (ADS)

van Westen, Cees; Bakker, Wim; Zhang, Kaixi; Jäger, Stefan; Assmann, Andre; Kass, Steve; Andrejchenko, Vera; Olyazadeh, Roya; Berlin, Julian; Cristal, Irina

2014-05-01

Within the framework of the EU FP7 Marie Curie Project CHANGES (www.changes-itn.eu) and the EU FP7 Copernicus project INCREO (http://www.increo-fp7.eu) a spatial decision support system is under development with the aim to analyse the effect of risk reduction planning alternatives on reducing the risk now and in the future, and support decision makers in selecting the best alternatives. The Spatial Decision Support System will be composed of a number of integrated components. The Risk Assessment component allows to carry out spatial risk analysis, with different degrees of complexity, ranging from simple exposure (overlay of hazard and assets maps) to quantitative analysis (using different hazard types, temporal scenarios and vulnerability curves) resulting into risk curves. The platform does not include a component to calculate hazard maps, and existing hazard maps are used as input data for the risk component. The second component of the SDSS is a risk reduction planning component, which forms the core of the platform. This component includes the definition of risk reduction alternatives (related to disaster response planning, risk reduction measures and spatial planning) and links back to the risk assessment module to calculate the new level of risk if the measure is implemented, and a cost-benefit (or cost-effectiveness/ Spatial Multi Criteria Evaluation) component to compare the alternatives and make decision on the optimal one. The third component of the SDSS is a temporal scenario component, which allows to define future scenarios in terms of climate change, land use change and population change, and the time periods for which these scenarios will be made. The component doesn't generate these scenarios but uses input maps for the effect of the scenarios on the hazard and assets maps. The last component is a communication and visualization component, which can compare scenarios and alternatives, not only in the form of maps, but also in other forms (risk curves, tables, graphs). The envisaged users of the platform are organizations involved in planning of risk reduction measures, and that have staff capable of visualizing and analysing spatial data at a municipal scale.

A web-based multicriteria evaluation of spatial trade-offs between environmental and economic implications from hydraulic fracturing in a shale gas region in Ohio.

PubMed

Liu, X; Gorsevski, P V; Yacobucci, M M; Onasch, C M

2016-06-01

Planning of shale gas infrastructure and drilling sites for hydraulic fracturing has important spatial implications. The evaluation of conflicting and competing objectives requires an explicit consideration of multiple criteria as they have important environmental and economic implications. This study presents a web-based multicriteria spatial decision support system (SDSS) prototype with a flexible and user-friendly interface that could provide educational or decision-making capabilities with respect to hydraulic fracturing site selection in eastern Ohio. One of the main features of this SDSS is to emphasize potential trade-offs between important factors of environmental and economic ramifications from hydraulic fracturing activities using a weighted linear combination (WLC) method. In the prototype, the GIS-enabled analytical components allow spontaneous visualization of available alternatives on maps which provide value-added features for decision support processes and derivation of final decision maps. The SDSS prototype also facilitates nonexpert participation capabilities using a mapping module, decision-making tool, group decision module, and social media sharing tools. The logical flow of successively presented forms and standardized criteria maps is used to generate visualization of trade-off scenarios and alternative solutions tailored to individual user's preferences that are graphed for subsequent decision-making.

New Interoperable Tools to Facilitate Decision-Making to Support Community Sustainability

EPA Science Inventory

Communities, regional planning authorities, regulatory agencies, and other decision-making bodies do not currently have adequate access to spatially explicit information crucial to making decisions that allow them to consider a full accounting of the costs, benefits, and trade-of...

Web-based GIS for collaborative planning and public participation: an application to the strategic planning of wind farm sites.

PubMed

Simão, Ana; Densham, Paul J; Haklay, Mordechai Muki

2009-05-01

Spatial planning typically involves multiple stakeholders. To any specific planning problem, stakeholders often bring different levels of knowledge about the components of the problem and make assumptions, reflecting their individual experiences, that yield conflicting views about desirable planning outcomes. Consequently, stakeholders need to learn about the likely outcomes that result from their stated preferences; this learning can be supported through enhanced access to information, increased public participation in spatial decision-making and support for distributed collaboration amongst planners, stakeholders and the public. This paper presents a conceptual system framework for web-based GIS that supports public participation in collaborative planning. The framework combines an information area, a Multi-Criteria Spatial Decision Support System (MC-SDSS) and an argumentation map to support distributed and asynchronous collaboration in spatial planning. After analysing the novel aspects of this framework, the paper describes its implementation, as a proof of concept, in a system for Web-based Participatory Wind Energy Planning (WePWEP). Details are provided on the specific implementation of each of WePWEP's four tiers, including technical and structural aspects. Throughout the paper, particular emphasis is placed on the need to support user learning throughout the planning process.

Relational Algebra in Spatial Decision Support Systems Ontologies.

PubMed

Diomidous, Marianna; Chardalias, Kostis; Koutonias, Panagiotis; Magnita, Adrianna; Andrianopoulos, Charalampos; Zimeras, Stelios; Mechili, Enkeleint Aggelos

2017-01-01

Decision Support Systems (DSS) is a powerful tool, for facilitates researchers to choose the correct decision based on their final results. Especially in medical cases where doctors could use these systems, to overcome the problem with the clinical misunderstanding. Based on these systems, queries must be constructed based on the particular questions that doctors must answer. In this work, combination between questions and queries would be presented via relational algebra.

Seismic slope-performance analysis: from hazard map to decision support system

USGS Publications Warehouse

Miles, Scott B.; Keefer, David K.; Ho, Carlton L.

1999-01-01

In response to the growing recognition of engineers and decision-makers of the regional effects of earthquake-induced landslides, this paper presents a general approach to conducting seismic landslide zonation, based on the popular Newmark's sliding block analogy for modeling coherent landslides. Four existing models based on the sliding block analogy are compared. The comparison shows that the models forecast notably different levels of slope performance. Considering this discrepancy along with the limitations of static maps as a decision tool, a spatial decision support system (SDSS) for seismic landslide analysis is proposed, which will support investigations over multiple scales for any number of earthquake scenarios and input conditions. Most importantly, the SDSS will allow use of any seismic landslide analysis model and zonation approach. Developments associated with the SDSS will produce an object-oriented model for encapsulating spatial data, an object-oriented specification to allow construction of models using modular objects, and a direct-manipulation, dynamic user-interface that adapts to the particular seismic landslide model configuration.

Spatially explicit decision support for selecting translocation areas for Mojave desert tortoises

USGS Publications Warehouse

Heaton, Jill S.; Nussear, Kenneth E.; Esque, Todd C.; Inman, Richard D.; Davenport, Frank; Leuteritz, Thomas E.; Medica, Philip A.; Strout, Nathan W.; Burgess, Paul A.; Benvenuti, Lisa

2008-01-01

Spatially explicit decision support systems are assuming an increasing role in natural resource and conservation management. In order for these systems to be successful, however, they must address real-world management problems with input from both the scientific and management communities. The National Training Center at Fort Irwin, California, has expanded its training area, encroaching U.S. Fish and Wildlife Service critical habitat set aside for the Mojave desert tortoise (Gopherus agassizii), a federally threatened species. Of all the mitigation measures proposed to offset expansion, the most challenging to implement was the selection of areas most feasible for tortoise translocation. We developed an objective, open, scientifically defensible spatially explicit decision support system to evaluate translocation potential within the Western Mojave Recovery Unit for tortoise populations under imminent threat from military expansion. Using up to a total of 10 biological, anthropogenic, and/or logistical criteria, seven alternative translocation scenarios were developed. The final translocation model was a consensus model between the seven scenarios. Within the final model, six potential translocation areas were identified.

A web-based spatial decision support system for spatial planning and governance in the Guangdong Province

NASA Astrophysics Data System (ADS)

Wu, Qitao; Zhang, Hong-ou; Chen, Fengui; Dou, Jie

2008-10-01

After three decades' rapid economic development, Guangdong province faces to thorny problems related to pollution, resource shortage and environmental deterioration. What is worse, the future accelerated development, urbanization and industrialization also comes at the cost of regional imbalance with economic gaps growing and the quality of life in different regions degrading. Development and Reform Commission of Guangdong Province (GDDRC) started a spatial planning project under the national frame in 2007. The prospective project is expected to enhance the equality of different regions and balance the economic development with environmental protection and improved sustainability. This manuscript presents the results of scientific research aiming to develop a Spatial Decision Support System (SDSS) for this spatial planning project. The system composes four modules include the User interface module (UIM), Spatial Analyze module (SAM), Database management module (DMM) and Help module (HM) base on ArcInfo, JSP/Servlet, JavaScript, MapServer, Visual C++ and Visual Basic technologies. The web-based SDSS provides a user-friendly tool for local decision makers, regional planners and other stakeholders in understanding and visualizing the different territorial dimensions of economic development against sustainable environmental and exhausted resources, and in defining, comparing and prioritizing specific territorially-based actions in order to prevent non-sustainable development and implement relevant politics.

SADA: Ecological Risk Based Decision Support System for Selective Remediation

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is freeware that implements terrestrial ecological risk assessment and yields a selective remediation design using its integral geographical information system, based on ecological and risk assessment inputs. Selective remediation ...

Opportunities and Strategies to Incorporate Ecosystem Services Knowledge and Decision Support Tools into Planning and Decision Making in Hawai`i

NASA Astrophysics Data System (ADS)

Bremer, Leah L.; Delevaux, Jade M. S.; Leary, James J. K.; J. Cox, Linda; Oleson, Kirsten L. L.

2015-04-01

Incorporating ecosystem services into management decisions is a promising means to link conservation and human well-being. Nonetheless, planning and management in Hawai`i, a state with highly valued natural capital, has yet to broadly utilize an ecosystem service approach. We conducted a stakeholder assessment, based on semi-structured interviews, with terrestrial ( n = 26) and marine ( n = 27) natural resource managers across the State of Hawai`i to understand the current use of ecosystem services (ES) knowledge and decision support tools and whether, how, and under what contexts, further development would potentially be useful. We found that ES knowledge and tools customized to Hawai`i could be useful for communication and outreach, justifying management decisions, and spatial planning. Greater incorporation of this approach is clearly desired and has a strong potential to contribute to more sustainable decision making and planning in Hawai`i and other oceanic island systems. However, the unique biophysical, socio-economic, and cultural context of Hawai`i, and other island systems, will require substantial adaptation of existing ES tools. Based on our findings, we identified four key opportunities for the use of ES knowledge and tools in Hawai`i: (1) linking native forest protection to watershed health; (2) supporting sustainable agriculture; (3) facilitating ridge-to-reef management; and (4) supporting statewide terrestrial and marine spatial planning. Given the interest expressed by natural resource managers, we envision broad adoption of ES knowledge and decision support tools if knowledge and tools are tailored to the Hawaiian context and coupled with adequate outreach and training.

Opportunities and strategies to incorporate ecosystem services knowledge and decision support tools into planning and decision making in Hawai'i.

PubMed

Bremer, Leah L; Delevaux, Jade M S; Leary, James J K; J Cox, Linda; Oleson, Kirsten L L

2015-04-01

Incorporating ecosystem services into management decisions is a promising means to link conservation and human well-being. Nonetheless, planning and management in Hawai'i, a state with highly valued natural capital, has yet to broadly utilize an ecosystem service approach. We conducted a stakeholder assessment, based on semi-structured interviews, with terrestrial (n = 26) and marine (n = 27) natural resource managers across the State of Hawai'i to understand the current use of ecosystem services (ES) knowledge and decision support tools and whether, how, and under what contexts, further development would potentially be useful. We found that ES knowledge and tools customized to Hawai'i could be useful for communication and outreach, justifying management decisions, and spatial planning. Greater incorporation of this approach is clearly desired and has a strong potential to contribute to more sustainable decision making and planning in Hawai'i and other oceanic island systems. However, the unique biophysical, socio-economic, and cultural context of Hawai'i, and other island systems, will require substantial adaptation of existing ES tools. Based on our findings, we identified four key opportunities for the use of ES knowledge and tools in Hawai'i: (1) linking native forest protection to watershed health; (2) supporting sustainable agriculture; (3) facilitating ridge-to-reef management; and (4) supporting statewide terrestrial and marine spatial planning. Given the interest expressed by natural resource managers, we envision broad adoption of ES knowledge and decision support tools if knowledge and tools are tailored to the Hawaiian context and coupled with adequate outreach and training.

Toward geodesign for watershed restoration on the Fremont-Winema National Forest, Pacific Northwest, USA

Treesearch

Keith Reynolds; Philip Murphy; Steven Paplanus

2017-01-01

Spatial decision support systems for forest management have steadily evolved over the past 20+ years in order to better address the complexities of contemporary forest management issues such as the sustainability and resilience of ecosystems on forested landscapes. In this paper, we describe and illustrate new features of the Ecosystem Management Decision Support (EMDS...

Development of spatial density maps based on geoprocessing web services: application to tuberculosis incidence in Barcelona, Spain.

PubMed

Dominkovics, Pau; Granell, Carlos; Pérez-Navarro, Antoni; Casals, Martí; Orcau, Angels; Caylà, Joan A

2011-11-29

Health professionals and authorities strive to cope with heterogeneous data, services, and statistical models to support decision making on public health. Sophisticated analysis and distributed processing capabilities over geocoded epidemiological data are seen as driving factors to speed up control and decision making in these health risk situations. In this context, recent Web technologies and standards-based web services deployed on geospatial information infrastructures have rapidly become an efficient way to access, share, process, and visualize geocoded health-related information. Data used on this study is based on Tuberculosis (TB) cases registered in Barcelona city during 2009. Residential addresses are geocoded and loaded into a spatial database that acts as a backend database. The web-based application architecture and geoprocessing web services are designed according to the Representational State Transfer (REST) principles. These web processing services produce spatial density maps against the backend database. The results are focused on the use of the proposed web-based application to the analysis of TB cases in Barcelona. The application produces spatial density maps to ease the monitoring and decision making process by health professionals. We also include a discussion of how spatial density maps may be useful for health practitioners in such contexts. In this paper, we developed web-based client application and a set of geoprocessing web services to support specific health-spatial requirements. Spatial density maps of TB incidence were generated to help health professionals in analysis and decision-making tasks. The combined use of geographic information tools, map viewers, and geoprocessing services leads to interesting possibilities in handling health data in a spatial manner. In particular, the use of spatial density maps has been effective to identify the most affected areas and its spatial impact. This study is an attempt to demonstrate how web processing services together with web-based mapping capabilities suit the needs of health practitioners in epidemiological analysis scenarios.

Development of spatial density maps based on geoprocessing web services: application to tuberculosis incidence in Barcelona, Spain

PubMed Central

2011-01-01

Background Health professionals and authorities strive to cope with heterogeneous data, services, and statistical models to support decision making on public health. Sophisticated analysis and distributed processing capabilities over geocoded epidemiological data are seen as driving factors to speed up control and decision making in these health risk situations. In this context, recent Web technologies and standards-based web services deployed on geospatial information infrastructures have rapidly become an efficient way to access, share, process, and visualize geocoded health-related information. Methods Data used on this study is based on Tuberculosis (TB) cases registered in Barcelona city during 2009. Residential addresses are geocoded and loaded into a spatial database that acts as a backend database. The web-based application architecture and geoprocessing web services are designed according to the Representational State Transfer (REST) principles. These web processing services produce spatial density maps against the backend database. Results The results are focused on the use of the proposed web-based application to the analysis of TB cases in Barcelona. The application produces spatial density maps to ease the monitoring and decision making process by health professionals. We also include a discussion of how spatial density maps may be useful for health practitioners in such contexts. Conclusions In this paper, we developed web-based client application and a set of geoprocessing web services to support specific health-spatial requirements. Spatial density maps of TB incidence were generated to help health professionals in analysis and decision-making tasks. The combined use of geographic information tools, map viewers, and geoprocessing services leads to interesting possibilities in handling health data in a spatial manner. In particular, the use of spatial density maps has been effective to identify the most affected areas and its spatial impact. This study is an attempt to demonstrate how web processing services together with web-based mapping capabilities suit the needs of health practitioners in epidemiological analysis scenarios. PMID:22126392

The role of low-spatial frequencies in lexical decision and masked priming.

PubMed

Boden, C; Giaschi, D

2009-04-01

Spatial frequency filtering was used to test the hypotheses that low-spatial frequency information in printed text can: (1) lead to a rapid lexical decision or (2) facilitate word recognition. Adult proficient readers made lexical decisions in unprimed and masked repetition priming experiments with unfiltered, low-pass, high-pass and notch filtered letter strings. In the unprimed experiments, a filtered target was presented for 105 or 400 ms followed by a pattern mask. Sensitivity (d') was lowest for the low-pass filtered targets at both durations with a bias towards a 'non-word' response. Sensitivity was higher in the high-pass and notch filter conditions. In the priming experiments, a forward mask was followed by a filtered prime then an unfiltered target. Primed words, but not non-words, were identified faster than unprimed words in both the low-pass and high-pass filtered conditions. These results do not support a unique role for low-spatial frequency information in either facilitating or making rapid lexical decisions.

Actionable Cultural Understanding for Support to Tactical Operations (ACUSTO): Toward a New Methodological Template for Spatial Decision Support System

DTIC Science & Technology

2009-05-01

gangs. Important aspects of these are the concept of micro locations, or “set space” where gangs tend to locate ( Tita et al. 2005) and patterns of...spatial diffusion of gang activity (Cohen and Tita 1999, Tita and Cohen 2004). A particularly promising approach is the combination of concepts from...matches their social interaction ( Tita 2007, Tita and Ridgeway 2007). An illustration of the incorporation of insights from a spatial analysis into

Forest climate change Vulnerability and Adaptation Assessment in Himalayas

NASA Astrophysics Data System (ADS)

Chitale, V. S.; Shrestha, H. L.; Agarwal, N. K.; Choudhurya, D.; Gilani, H.; Dhonju, H. K.; Murthy, M. S. R.

2014-11-01

Forests offer an important basis for creating and safeguarding more climate-resilient communities over Hindu Kush Himalayan region. The forest ecosystem vulnerability assessment to climate change and developing knowledge base to identify and support relevant adaptation strategies is realized as an urgent need. The multi scale adaptation strategies portray increasing complexity with the increasing levels in terms of data requirements, vulnerability understanding and decision making to choose a particular adaptation strategy. We present here how such complexities could be addressed and adaptation decisions could be either directly supported by open source remote sensing based forestry products or geospatial analysis and modelled products. The forest vulnerability assessment under climate change scenario coupled with increasing forest social dependence was studied using IPCC Landscape scale Vulnerability framework in Chitwan-Annapurna Landscape (CHAL) situated in Nepal. Around twenty layers of geospatial information on climate, forest biophysical and forest social dependence data was used to assess forest vulnerability and associated adaptation needs using self-learning decision tree based approaches. The increase in forest fires, evapotranspiration and reduction in productivity over changing climate scenario was observed. The adaptation measures on enhancing productivity, improving resilience, reducing or avoiding pressure with spatial specificity are identified to support suitable decision making. The study provides spatial analytical framework to evaluate multitude of parameters to understand vulnerabilities and assess scope for alternative adaptation strategies with spatial explicitness.

Semantic Metadata for Heterogeneous Spatial Planning Documents

NASA Astrophysics Data System (ADS)

Iwaniak, A.; Kaczmarek, I.; Łukowicz, J.; Strzelecki, M.; Coetzee, S.; Paluszyński, W.

2016-09-01

Spatial planning documents contain information about the principles and rights of land use in different zones of a local authority. They are the basis for administrative decision making in support of sustainable development. In Poland these documents are published on the Web according to a prescribed non-extendable XML schema, designed for optimum presentation to humans in HTML web pages. There is no document standard, and limited functionality exists for adding references to external resources. The text in these documents is discoverable and searchable by general-purpose web search engines, but the semantics of the content cannot be discovered or queried. The spatial information in these documents is geographically referenced but not machine-readable. Major manual efforts are required to integrate such heterogeneous spatial planning documents from various local authorities for analysis, scenario planning and decision support. This article presents results of an implementation using machine-readable semantic metadata to identify relationships among regulations in the text, spatial objects in the drawings and links to external resources. A spatial planning ontology was used to annotate different sections of spatial planning documents with semantic metadata in the Resource Description Framework in Attributes (RDFa). The semantic interpretation of the content, links between document elements and links to external resources were embedded in XHTML pages. An example and use case from the spatial planning domain in Poland is presented to evaluate its efficiency and applicability. The solution enables the automated integration of spatial planning documents from multiple local authorities to assist decision makers with understanding and interpreting spatial planning information. The approach is equally applicable to legal documents from other countries and domains, such as cultural heritage and environmental management.

Towards an integrated approach to natural hazards risk assessment using GIS: with reference to bushfires.

PubMed

Chen, Keping; Blong, Russell; Jacobson, Carol

2003-04-01

This paper develops a GIS-based integrated approach to risk assessment in natural hazards, with reference to bushfires. The challenges for undertaking this approach have three components: data integration, risk assessment tasks, and risk decision-making. First, data integration in GIS is a fundamental step for subsequent risk assessment tasks and risk decision-making. A series of spatial data integration issues within GIS such as geographical scales and data models are addressed. Particularly, the integration of both physical environmental data and socioeconomic data is examined with an example linking remotely sensed data and areal census data in GIS. Second, specific risk assessment tasks, such as hazard behavior simulation and vulnerability assessment, should be undertaken in order to understand complex hazard risks and provide support for risk decision-making. For risk assessment tasks involving heterogeneous data sources, the selection of spatial analysis units is important. Third, risk decision-making concerns spatial preferences and/or patterns, and a multicriteria evaluation (MCE)-GIS typology for risk decision-making is presented that incorporates three perspectives: spatial data types, data models, and methods development. Both conventional MCE methods and artificial intelligence-based methods with GIS are identified to facilitate spatial risk decision-making in a rational and interpretable way. Finally, the paper concludes that the integrated approach can be used to assist risk management of natural hazards, in theory and in practice.

ENVIRONMENTAL TECHNOLOGY VERIFICATION REPORT, ENVIRONMENTAL DECISION SUPPORT SOFTWARE, UNIVERSITY OF TENNESSEE RESEARCH CORPORATION, SPATIAL ANALYSIS AND DECISION ASSISTANCE (SADA)

EPA Science Inventory

The U.S. Environmental Protection Agency (EPA) has created the Environmental Technology Verification Program (ETV) to facilitate the deployment of innovative or improved environmental technologies through performance verification and dissemination of information. The goal of the...

Development of a spatial decision support system for flood risk management in Brazil that combines volunteered geographic information with wireless sensor networks

NASA Astrophysics Data System (ADS)

Horita, Flávio E. A.; Albuquerque, João Porto de; Degrossi, Lívia C.; Mendiondo, Eduardo M.; Ueyama, Jó

2015-07-01

Effective flood risk management requires updated information to ensure that the correct decisions can be made. This can be provided by Wireless Sensor Networks (WSN) which are a low-cost means of collecting updated information about rivers. Another valuable resource is Volunteered Geographic Information (VGI) which is a comparatively new means of improving the coverage of monitored areas because it is able to supply supplementary information to the WSN and thus support decision-making in flood risk management. However, there still remains the problem of how to combine WSN data with VGI. In this paper, an attempt is made to investigate AGORA-DS, which is a Spatial Decision Support System (SDSS) that is able to make flood risk management more effective by combining these data sources, i.e. WSN with VGI. This approach is built over a conceptual model that complies with the interoperable standards laid down by the Open Geospatial Consortium (OGC) - e.g. Sensor Observation Service (SOS) and Web Feature Service (WFS) - and seeks to combine and present unified information in a web-based decision support tool. This work was deployed in a real scenario of flood risk management in the town of São Carlos in Brazil. The evidence obtained from this deployment confirmed that interoperable standards can support the integration of data from distinct data sources. In addition, they also show that VGI is able to provide information about areas of the river basin which lack data since there is no appropriate station in the area. Hence it provides a valuable support for the WSN data. It can thus be concluded that AGORA-DS is able to combine information provided by WSN and VGI, and provide useful information for supporting flood risk management.

HIGH-RESOLUTION SPATIAL MODELING OF DAILY WEATHER ELEMENTS FOR A CATCHMENT IN THE OREGON CASCADE MOUNTAINS, UNITED STATES

EPA Science Inventory

High-quality, daily meteorological data at high spatial resolution are essential for a variety of hydrologic and ecological modeling applications that support environmental risk assessments and decision making. This paper describes the development, application, and assessment of ...

Heat and Health in a Changing Climate: Building a Decision Support Tool for California Public Health Officials

NASA Astrophysics Data System (ADS)

Steinberg, N.

2017-12-01

There is considerable interest in overlaying climate projections with social vulnerability maps as a mechanism for targeting community adaptation efforts. Yet the identification of relevant factors for adaptation- and resilience-based decisions remain a challenge. Our findings show that successful adaptation interventions are more likely when factors are grouped and spatially represented. By designing a decision-support tool that is focused on informing long-term planning to mitigate the public health impacts of extreme heat, communities can more easily integrate climate, land use, and population characteristics into local planning processes. The ability to compare risks and potential health impacts across census tracts may also position local practitioners to leverage scarce resources. This presentation will discuss the information gaps identified by planners and public health practitioners throughout California and illustrate the spatial variations of key health risk factors.

The Use of Spatial Data Infrastructure in Environmental Management:an Example from the Spatial Planning Practice in Poland.

PubMed

Zwirowicz-Rutkowska, Agnieszka; Michalik, Anna

2016-10-01

Today's technology plays a crucial role in the effective use of environmental information. This includes geographic information systems and infrastructures. The purpose of this research is to identify the way in which the Polish spatial data infrastructure (PSDI) supports policies and activities that may have an impact on the environment in relation to one group of users, namely urban planners, and their tasks concerning environmental management. The study is based on a survey conducted in July and August, 2014. Moreover, the authors' expert knowledge gained through urban development practice and the analysis of the environmental conservation regulations and spatial planning in Poland has been used to define the scope of environmental management in both spatial planning studies and spatial data sources. The research included assessment of data availability, infrastructure usability, and its impact on decision-making process. The results showed that the PSDI is valuable because it allows for the acquisition of data on environmental monitoring, agricultural and aquaculture facilities. It also has a positive impact on decision-making processes and improves numerous planners' activities concerning both the inclusion of environmental indicators in spatial plans and the support of nature conservation and environmental management in the process of working on future land use. However, even though the infrastructure solves certain problems with data accessibility, further improvements might be proposed. The importance of the SDI in environmental management is noticeable and could be considered from many standpoints: Data, communities engaged in policy or decision-making concerning environmental issues, and data providers.

REGIONAL VULNERABILITY ASSESSMENT (REVA) IMPROVING ENVIRONMENTAL DECISION MAKING THROUGH CLIENT PARTNERSHIPS

EPA Science Inventory

The Regional Vulnerability Assessment (ReV A) Program is an applied research program t,1at is focusing on using spatial information and model results to support environmental decision-making at regional- down to local-scales. Re VA has developed analysis and assessment methods to...

Implementation of marine spatial planning in shellfish aquaculture management: modeling studies in a Norwegian fjord.

PubMed

Filgueira, Ramon; Grant, Jon; Strand, Øivind

2014-06-01

Shellfish carrying capacity is determined by the interaction of a cultured species with its ecosystem, which is strongly influenced by hydrodynamics. Water circulation controls the exchange of matter between farms and the adjacent areas, which in turn establishes the nutrient supply that supports phytoplankton populations. The complexity of water circulation makes necessary the use of hydrodynamic models with detailed spatial resolution in carrying capacity estimations. This detailed spatial resolution also allows for the study of processes that depend on specific spatial arrangements, e.g., the most suitable location to place farms, which is crucial for marine spatial planning, and consequently for decision support systems. In the present study, a fully spatial physical-biogeochemical model has been combined with scenario building and optimization techniques as a proof of concept of the use of ecosystem modeling as an objective tool to inform marine spatial planning. The object of this exercise was to generate objective knowledge based on an ecosystem approach to establish new mussel aquaculture areas in a Norwegian fjord. Scenario building was used to determine the best location of a pump that can be used to bring nutrient-rich deep waters to the euphotic layer, increasing primary production, and consequently, carrying capacity for mussel cultivation. In addition, an optimization tool, parameter estimation (PEST), was applied to the optimal location and mussel standing stock biomass that maximize production, according to a preestablished carrying capacity criterion. Optimization tools allow us to make rational and transparent decisions to solve a well-defined question, decisions that are essential for policy makers. The outcomes of combining ecosystem models with scenario building and optimization facilitate planning based on an ecosystem approach, highlighting the capabilities of ecosystem modeling as a tool for marine spatial planning.

Modified Navigation Instructions for Spatial Navigation Assistance Systems Lead to Incidental Spatial Learning

PubMed Central

Gramann, Klaus; Hoepner, Paul; Karrer-Gauss, Katja

2017-01-01

Spatial cognitive skills deteriorate with the increasing use of automated GPS navigation and a general decrease in the ability to orient in space might have further impact on independence, autonomy, and quality of life. In the present study we investigate whether modified navigation instructions support incidental spatial knowledge acquisition. A virtual driving environment was used to examine the impact of modified navigation instructions on spatial learning while using a GPS navigation assistance system. Participants navigated through a simulated urban and suburban environment, using navigation support to reach their destination. Driving performance as well as spatial learning was thereby assessed. Three navigation instruction conditions were tested: (i) a control group that was provided with classical navigation instructions at decision points, and two other groups that received navigation instructions at decision points including either (ii) additional irrelevant information about landmarks or (iii) additional personally relevant information (i.e., individual preferences regarding food, hobbies, etc.), associated with landmarks. Driving performance revealed no differences between navigation instructions. Significant improvements were observed in both modified navigation instruction conditions on three different measures of spatial learning and memory: subsequent navigation of the initial route without navigation assistance, landmark recognition, and sketch map drawing. Future navigation assistance systems could incorporate modified instructions to promote incidental spatial learning and to foster more general spatial cognitive abilities. Such systems might extend mobility across the lifespan. PMID:28243219

Development of a GIService based on spatial data mining for location choice of convenience stores in Taipei City

NASA Astrophysics Data System (ADS)

Jung, Chinte; Sun, Chih-Hong

2006-10-01

Motivated by the increasing accessibility of technology, more and more spatial data are being made digitally available. How to extract the valuable knowledge from these large (spatial) databases is becoming increasingly important to businesses, as well. It is essential to be able to analyze and utilize these large datasets, convert them into useful knowledge, and transmit them through GIS-enabled instruments and the Internet, conveying the key information to business decision-makers effectively and benefiting business entities. In this research, we combine the techniques of GIS, spatial decision support system (SDSS), spatial data mining (SDM), and ArcGIS Server to achieve the following goals: (1) integrate databases from spatial and non-spatial datasets about the locations of businesses in Taipei, Taiwan; (2) use the association rules, one of the SDM methods, to extract the knowledge from the integrated databases; and (3) develop a Web-based SDSS GIService as a location-selection tool for business by the product of ArcGIS Server.

Design and implementation of a risk assessment module in a spatial decision support system

NASA Astrophysics Data System (ADS)

Zhang, Kaixi; van Westen, Cees; Bakker, Wim

2014-05-01

The spatial decision support system named 'Changes SDSS' is currently under development. The goal of this system is to analyze changing hydro-meteorological hazards and the effect of risk reduction alternatives to support decision makers in choosing the best alternatives. The risk assessment module within the system is to assess the current risk, analyze the risk after implementations of risk reduction alternatives, and analyze the risk in different future years when considering scenarios such as climate change, land use change and population growth. The objective of this work is to present the detailed design and implementation plan of the risk assessment module. The main challenges faced consist of how to shift the risk assessment from traditional desktop software to an open source web-based platform, the availability of input data and the inclusion of uncertainties in the risk analysis. The risk assessment module is developed using Ext JS library for the implementation of user interface on the client side, using Python for scripting, as well as PostGIS spatial functions for complex computations on the server side. The comprehensive consideration of the underlying uncertainties in input data can lead to a better quantification of risk assessment and a more reliable Changes SDSS, since the outputs of risk assessment module are the basis for decision making module within the system. The implementation of this module will contribute to the development of open source web-based modules for multi-hazard risk assessment in the future. This work is part of the "CHANGES SDSS" project, funded by the European Community's 7th Framework Program.

Environmental impact assessment of transportation projects: An analysis using an integrated GIS, remote sensing, and spatial modeling approach

NASA Astrophysics Data System (ADS)

El-Gafy, Mohamed Anwar

Transportation projects will have impact on the environment. The general environmental pollution and damage caused by roads is closely associated with the level of economic activity. Although Environmental Impact Assessments (EIAs) are dependent on geo-spatial information in order to make an assessment, there are no rules per se how to conduct an environmental assessment. Also, the particular objective of each assessment is dictated case-by-case, based on what information and analyses are required. The conventional way of Environmental Impact Assessment (EIA) study is a time consuming process because it has large number of dependent and independent variables which have to be taken into account, which also have different consequences. With the emergence of satellite remote sensing technology and Geographic Information Systems (GIS), this research presents a new framework for the analysis phase of the Environmental Impact Assessment (EIA) for transportation projects based on the integration between remote sensing technology, geographic information systems, and spatial modeling. By integrating the merits of the map overlay method and the matrix method, the framework analyzes comprehensively the environmental vulnerability around the road and its impact on the environment. This framework is expected to: (1) improve the quality of the decision making process, (2) be applied both to urban and inter-urban projects, regardless of transport mode, and (3) present the data and make the appropriate analysis to support the decision of the decision-makers and allow them to present these data to the public hearings in a simple manner. Case studies, transportation projects in the State of Florida, were analyzed to illustrate the use of the decision support framework and demonstrate its capabilities. This cohesive and integrated system will facilitate rational decisions through cost effective coordination of environmental information and data management that can be tailored to specific projects. The framework would facilitate collecting, organizing, analyzing, archiving, and coordinating the information and data necessary to support technical and policy transportation decisions.

Foundations for context-aware information retrieval for proactive decision support

NASA Astrophysics Data System (ADS)

Mittu, Ranjeev; Lin, Jessica; Li, Qingzhe; Gao, Yifeng; Rangwala, Huzefa; Shargo, Peter; Robinson, Joshua; Rose, Carolyn; Tunison, Paul; Turek, Matt; Thomas, Stephen; Hanselman, Phil

2016-05-01

Intelligence analysts and military decision makers are faced with an onslaught of information. From the now ubiquitous presence of intelligence, surveillance, and reconnaissance (ISR) platforms providing large volumes of sensor data, to vast amounts of open source data in the form of news reports, blog postings, or social media postings, the amount of information available to a modern decision maker is staggering. Whether tasked with leading a military campaign or providing support for a humanitarian mission, being able to make sense of all the information available is a challenge. Due to the volume and velocity of this data, automated tools are required to help support reasoned, human decisions. In this paper we describe several automated techniques that are targeted at supporting decision making. Our approaches include modeling the kinematics of moving targets as motifs; developing normalcy models and detecting anomalies in kinematic data; automatically classifying the roles of users in social media; and modeling geo-spatial regions based on the behavior that takes place in them. These techniques cover a wide-range of potential decision maker needs.

A new spatial multi-criteria decision support tool for site selection for implementation of managed aquifer recharge.

PubMed

Rahman, M Azizur; Rusteberg, Bernd; Gogu, R C; Lobo Ferreira, J P; Sauter, Martin

2012-05-30

This study reports the development of a new spatial multi-criteria decision analysis (SMCDA) software tool for selecting suitable sites for Managed Aquifer Recharge (MAR) systems. The new SMCDA software tool functions based on the combination of existing multi-criteria evaluation methods with modern decision analysis techniques. More specifically, non-compensatory screening, criteria standardization and weighting, and Analytical Hierarchy Process (AHP) have been combined with Weighted Linear Combination (WLC) and Ordered Weighted Averaging (OWA). This SMCDA tool may be implemented with a wide range of decision maker's preferences. The tool's user-friendly interface helps guide the decision maker through the sequential steps for site selection, those steps namely being constraint mapping, criteria hierarchy, criteria standardization and weighting, and criteria overlay. The tool offers some predetermined default criteria and standard methods to increase the trade-off between ease-of-use and efficiency. Integrated into ArcGIS, the tool has the advantage of using GIS tools for spatial analysis, and herein data may be processed and displayed. The tool is non-site specific, adaptive, and comprehensive, and may be applied to any type of site-selection problem. For demonstrating the robustness of the new tool, a case study was planned and executed at Algarve Region, Portugal. The efficiency of the SMCDA tool in the decision making process for selecting suitable sites for MAR was also demonstrated. Specific aspects of the tool such as built-in default criteria, explicit decision steps, and flexibility in choosing different options were key features, which benefited the study. The new SMCDA tool can be augmented by groundwater flow and transport modeling so as to achieve a more comprehensive approach to the selection process for the best locations of the MAR infiltration basins, as well as the locations of recovery wells and areas of groundwater protection. The new spatial multicriteria analysis tool has already been implemented within the GIS based Gabardine decision support system as an innovative MAR planning tool. Copyright © 2012 Elsevier Ltd. All rights reserved.

Development of a Spatial Decision Support System for Analyzing Changes in Hydro-meteorological Risk

NASA Astrophysics Data System (ADS)

van Westen, Cees

2013-04-01

In the framework of the EU FP7 Marie Curie ITN Network "CHANGES: Changing Hydro-meteorological Risks, as Analyzed by a New Generation of European Scientists (http://www.changes-itn.eu)", a spatial decision support system is under development with the aim to analyze the effect of risk reduction planning alternatives on reducing the risk now and in the future, and support decision makers in selecting the best alternatives. The SDSS is one of the main outputs of the CHANGES network, which will develop an advanced understanding of how global changes, related to environmental and climate change as well as socio-economical change, may affect the temporal and spatial patterns of hydro-meteorological hazards and associated risks in Europe; how these changes can be assessed, modeled, and incorporated in sustainable risk management strategies, focusing on spatial planning, emergency preparedness and risk communication. The CHANGES network consists of 11 full partners and 6 associate partners of which 5 private companies, representing 10 European countries. The CHANGES network has hired 12 Early Stage Researchers (ESRs) and is currently hiring 3-6 researchers more for the implementation of the SDSS. The Spatial Decision Support System will be composed of a number of integrated components. The Risk Assessment component allows to carry out spatial risk analysis, with different degrees of complexity, ranging from simple exposure (overlay of hazard and assets maps) to quantitative analysis (using different hazard types, temporal scenarios and vulnerability curves) resulting into risk curves. The platform does not include a component to calculate hazard maps, and existing hazard maps are used as input data for the risk component. The second component of the SDSS is a risk reduction planning component, which forms the core of the platform. This component includes the definition of risk reduction alternatives (related to disaster response planning, risk reduction measures and spatial planning) and links back to the risk assessment module to calculate the new level of risk if the measure is implemented, and a cost-benefit (or cost-effectiveness/ Spatial Multi Criteria Evaluation) component to compare the alternatives and make decision on the optimal one. The third component of the SDSS is a temporal scenario component, which allows to define future scenarios in terms of climate change, land use change and population change, and the time periods for which these scenarios will be made. The component doesn't generate these scenarios but uses input maps for the effect of the scenarios on the hazard and assets maps. The last component is a communication and visualization component, which can compare scenarios and alternatives, not only in the form of maps, but also in other forms (risk curves, tables, graphs). The envisaged users of the platform are organizations involved in planning of risk reduction measures, and that have staff capable of visualizing and analyzing spatial data at a municipal scale. This paper presents the main components of the SDSS and the overall design and plans for the user interface.

Improving the Slum Planning Through Geospatial Decision Support System

NASA Astrophysics Data System (ADS)

Shekhar, S.

2014-11-01

In India, a number of schemes and programmes have been launched from time to time in order to promote integrated city development and to enable the slum dwellers to gain access to the basic services. Despite the use of geospatial technologies in planning, the local, state and central governments have only been partially successful in dealing with these problems. The study on existing policies and programmes also proved that when the government is the sole provider or mediator, GIS can become a tool of coercion rather than participatory decision-making. It has also been observed that local level administrators who have adopted Geospatial technology for local planning continue to base decision-making on existing political processes. In this juncture, geospatial decision support system (GSDSS) can provide a framework for integrating database management systems with analytical models, graphical display, tabular reporting capabilities and the expert knowledge of decision makers. This assists decision-makers to generate and evaluate alternative solutions to spatial problems. During this process, decision-makers undertake a process of decision research - producing a large number of possible decision alternatives and provide opportunities to involve the community in decision making. The objective is to help decision makers and planners to find solutions through a quantitative spatial evaluation and verification process. The study investigates the options for slum development in a formal framework of RAY (Rajiv Awas Yojana), an ambitious program of Indian Government for slum development. The software modules for realizing the GSDSS were developed using the ArcGIS and Community -VIZ software for Gulbarga city.

Using an ecosystem service decision support tool to support ridge to reef management: An example of sediment reduction in west Maui, Hawaii

NASA Astrophysics Data System (ADS)

Falinski, K. A.; Oleson, K.; Htun, H.; Kappel, C.; Lecky, J.; Rowe, C.; Selkoe, K.; White, C.

2016-12-01

Faced with anthropogenic stressors and declining coral reef states, managers concerned with restoration and resilience of coral reefs are increasingly recognizing the need to take a ridge-to-reef, ecosystem-based approach. An ecosystem services framing can help managers move towards these goals, helping to illustrate trade-offs and opportunities of management actions in terms of their impacts on society. We describe a research program building a spatial ecosystem services-based decision-support tool, and being applied to guide ridge-to-reef management in a NOAA priority site in West Maui. We use multiple modeling methods to link biophysical processes to ecosystem services and their spatial flows and social values in an integrating platform. Modeled services include water availability, sediment retention, nutrient retention and carbon sequestration on land. A coral reef ecosystem service model is under development to capture the linkages between terrestrial and coastal ecosystem services. Valuation studies are underway to quantify the implications for human well-being. The tool integrates techniques from decision science to facilitate decision making. We use the sediment retention model to illustrate the types of analyses the tool can support. The case study explores the tradeoffs between road rehabilitation costs and sediment export avoided. We couple the sediment and cost models with trade-off analysis to identify optimal distributed solutions that are most cost-effective in reducing erosion, and then use those models to estimate sediment exposure to coral reefs. We find that cooperation between land owners reveals opportunities for maximizing the benefits of fixing roads and minimizes costs. This research forms the building blocks of an ecosystem service decision support tool that we intend to continue to test and apply in other Pacific Island settings.

The design and implementation of urban earthquake disaster loss evaluation and emergency response decision support systems based on GIS

NASA Astrophysics Data System (ADS)

Yang, Kun; Xu, Quan-li; Peng, Shuang-yun; Cao, Yan-bo

2008-10-01

Based on the necessity analysis of GIS applications in earthquake disaster prevention, this paper has deeply discussed the spatial integration scheme of urban earthquake disaster loss evaluation models and visualization technologies by using the network development methods such as COM/DCOM, ActiveX and ASP, as well as the spatial database development methods such as OO4O and ArcSDE based on ArcGIS software packages. Meanwhile, according to Software Engineering principles, a solution of Urban Earthquake Emergency Response Decision Support Systems based on GIS technologies have also been proposed, which include the systems logical structures, the technical routes,the system realization methods and function structures etc. Finally, the testing systems user interfaces have also been offered in the paper.

Prioritization of information using decision support systems for seismic risk in Bucharest city

NASA Astrophysics Data System (ADS)

Armas, Iuliana; Gheorghe, Diana

2014-05-01

Nowadays, because of the ever increasing volume of information, policymakers are faced with decision making problems. Achieving an objective and suitable decision making may become a challenge. In such situations decision support systems (DSS) have been developed. DSS can assist in the decision making process, offering support on how a decision should be made, rather than what decision should be made (Simon, 1979). This in turn potentially involves a huge number of stakeholders and criteria. Regarding seismic risk, Bucharest City is highly vulnerable (Mandrescu et al., 2007). The aim of this study is to implement a spatial decision support system in order to secure a suitable shelter in case of an earthquake occurrence in the historical centre of Bucharest City. In case of a seismic risk, a shelter is essential for sheltering people who lost their homes or whose homes are in danger of collapsing while people at risk receive first aid in the post-disaster phase. For the present study, the SMCE Module for ILWIS 3.4 was used. The methodology included structuring the problem by creating a decision tree, standardizing and weighting of the criteria. The results showed that the most suitable buildings are Tania Hotel, Hanul lui Manuc, The National Bank of Romania, The Romanian Commercial Bank and The National History Museum.

Watershed Management Optimization Support Tool (WMOST) v1: Theoretical Documentation

EPA Science Inventory

The Watershed Management Optimization Support Tool (WMOST) is a screening model that is spatially lumped with options for a daily or monthly time step. It is specifically focused on modeling the effect of management decisions on the watershed. The model considers water flows and ...

Hysteresis as an Implicit Prior in Tactile Spatial Decision Making

PubMed Central

Thiel, Sabrina D.; Bitzer, Sebastian; Nierhaus, Till; Kalberlah, Christian; Preusser, Sven; Neumann, Jane; Nikulin, Vadim V.; van der Meer, Elke; Villringer, Arno; Pleger, Burkhard

2014-01-01

Perceptual decisions not only depend on the incoming information from sensory systems but constitute a combination of current sensory evidence and internally accumulated information from past encounters. Although recent evidence emphasizes the fundamental role of prior knowledge for perceptual decision making, only few studies have quantified the relevance of such priors on perceptual decisions and examined their interplay with other decision-relevant factors, such as the stimulus properties. In the present study we asked whether hysteresis, describing the stability of a percept despite a change in stimulus property and known to occur at perceptual thresholds, also acts as a form of an implicit prior in tactile spatial decision making, supporting the stability of a decision across successively presented random stimuli (i.e., decision hysteresis). We applied a variant of the classical 2-point discrimination task and found that hysteresis influenced perceptual decision making: Participants were more likely to decide ‘same’ rather than ‘different’ on successively presented pin distances. In a direct comparison between the influence of applied pin distances (explicit stimulus property) and hysteresis, we found that on average, stimulus property explained significantly more variance of participants’ decisions than hysteresis. However, when focusing on pin distances at threshold, we found a trend for hysteresis to explain more variance. Furthermore, the less variance was explained by the pin distance on a given decision, the more variance was explained by hysteresis, and vice versa. Our findings suggest that hysteresis acts as an implicit prior in tactile spatial decision making that becomes increasingly important when explicit stimulus properties provide decreasing evidence. PMID:24587045

A Decision Support System for Optimum Use of Fertilizers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hoskinson, Reed Louis; Hess, John Richard; Fink, Raymond Keith

1999-07-01

The Decision Support System for Agriculture (DSS4Ag) is an expert system being developed by the Site-Specific Technologies for Agriculture (SST4Ag) precision farming research project at the INEEL. DSS4Ag uses state-of-the-art artificial intelligence and computer science technologies to make spatially variable, site-specific, economically optimum decisions on fertilizer use. The DSS4Ag has an open architecture that allows for external input and addition of new requirements and integrates its results with existing agricultural systems’ infrastructures. The DSS4Ag reflects a paradigm shift in the information revolution in agriculture that is precision farming. We depict this information revolution in agriculture as an historic trend inmore » the agricultural decision-making process.« less

A Decision Support System for Optimum Use of Fertilizers

DOE Office of Scientific and Technical Information (OSTI.GOV)

R. L. Hoskinson; J. R. Hess; R. K. Fink

1999-07-01

The Decision Support System for Agriculture (DSS4Ag) is an expert system being developed by the Site-Specific Technologies for Agriculture (SST4Ag) precision farming research project at the INEEL. DSS4Ag uses state-of-the-art artificial intelligence and computer science technologies to make spatially variable, site-specific, economically optimum decisions on fertilizer use. The DSS4Ag has an open architecture that allows for external input and addition of new requirements and integrates its results with existing agricultural systems' infrastructures. The DSS4Ag reflects a paradigm shift in the information revolution in agriculture that is precision farming. We depict this information revolution in agriculture as an historic trend inmore » the agricultural decision-making process.« less

Middle Mississippi River decision support system: user's manual

USGS Publications Warehouse

Rohweder, Jason J.; Zigler, Steven J.; Fox, Timothy J.; Hulse, Steven N.

2005-01-01

This user's manual describes the Middle Mississippi River Decision Support System (MMRDSS) and gives detailed examples on its use. The MMRDSS provides a framework to assist decision makers regarding natural resource issues in the Middle Mississippi River floodplain. The MMRDSS is designed to provide users with a spatially explicit tool for tasks, such as inventorying existing knowledge, developing models to investigate the potential effects of management decisions, generating hypotheses to advance scientific understanding, and developing scientifically defensible studies and monitoring. The MMRDSS also includes advanced tools to assist users in evaluating differences in complexity, connectivity, and structure of aquatic habitats among river reaches. The Environmental Systems Research Institute ArcView 3.x platform was used to create and package the data and tools of the MMRDSS.

The Wildland Fire Emissions Information System: Providing information for carbon cycle studies with open source geospatial tools

NASA Astrophysics Data System (ADS)

French, N. H.; Erickson, T.; McKenzie, D.

2008-12-01

A major goal of the North American Carbon Program is to resolve uncertainties in understanding and managing the carbon cycle of North America. As carbon modeling tools become more comprehensive and spatially oriented, accurate datasets to spatially quantify carbon emissions from fire are needed, and these data resources need to be accessible to users for decision-making. Under a new NASA Carbon Cycle Science project, Drs. Nancy French and Tyler Erickson, of the Michigan Technological University, Michigan Tech Research Institute (MTRI), are teaming with specialists with the USDA Forest Service Fire and Environmental Research Applications (FERA) team to provide information for mapping fire-derived carbon emissions to users. The project focus includes development of a web-based system to provide spatially resolved fire emissions estimates for North America in a user-friendly environment. The web-based Decision Support System will be based on a variety of open source technologies. The Fuel Characteristic Classification System (FCCS) raster map of fuels and MODIS-derived burned area vector maps will be processed using the Geographic Data Abstraction Library (GDAL) and OGR Simple Features Library. Tabular and spatial project data will be stored in a PostgreSQL/PostGIS, a spatially enabled relational database server. The browser-based user interface will be created using the Django web page framework to allow user input for the decision support system. The OpenLayers mapping framework will be used to provide users with interactive maps within the browser. In addition, the data products will be made available in standard open data formats such as KML, to allow for easy integration into other spatial models and data systems.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Graesser, Jordan B; Cheriyadat, Anil M; Vatsavai, Raju

The high rate of global urbanization has resulted in a rapid increase in informal settlements, which can be de ned as unplanned, unauthorized, and/or unstructured housing. Techniques for ef ciently mapping these settlement boundaries can bene t various decision making bodies. From a remote sensing perspective, informal settlements share unique spatial characteristics that distinguish them from other types of structures (e.g., industrial, commercial, and formal residential). These spatial characteristics are often captured in high spatial resolution satellite imagery. We analyzed the role of spatial, structural, and contextual features (e.g., GLCM, Histogram of Oriented Gradients, Line Support Regions, Lacunarity) for urbanmore » neighborhood mapping, and computed several low-level image features at multiple scales to characterize local neighborhoods. The decision parameters to classify formal-, informal-, and non-settlement classes were learned under Decision Trees and a supervised classi cation framework. Experiments were conducted on high-resolution satellite imagery from the CitySphere collection, and four different cities (i.e., Caracas, Kabul, Kandahar, and La Paz) with varying spatial characteristics were represented. Overall accuracy ranged from 85% in La Paz, Bolivia, to 92% in Kandahar, Afghanistan. While the disparities between formal and informal neighborhoods varied greatly, many of the image statistics tested proved robust.« less

Natural Hazard Susceptibility Assessment for Road Planning Using Spatial Multi-Criteria Analysis

NASA Astrophysics Data System (ADS)

Karlsson, Caroline S. J.; Kalantari, Zahra; Mörtberg, Ulla; Olofsson, Bo; Lyon, Steve W.

2017-11-01

Inadequate infrastructural networks can be detrimental to society if transport between locations becomes hindered or delayed, especially due to natural hazards which are difficult to control. Thus determining natural hazard susceptible areas and incorporating them in the initial planning process, may reduce infrastructural damages in the long run. The objective of this study was to evaluate the usefulness of expert judgments for assessing natural hazard susceptibility through a spatial multi-criteria analysis approach using hydrological, geological, and land use factors. To utilize spatial multi-criteria analysis for decision support, an analytic hierarchy process was adopted where expert judgments were evaluated individually and in an aggregated manner. The estimates of susceptible areas were then compared with the methods weighted linear combination using equal weights and factor interaction method. Results showed that inundation received the highest susceptibility. Using expert judgment showed to perform almost the same as equal weighting where the difference in susceptibility between the two for inundation was around 4%. The results also showed that downscaling could negatively affect the susceptibility assessment and be highly misleading. Susceptibility assessment through spatial multi-criteria analysis is useful for decision support in early road planning despite its limitation to the selection and use of decision rules and criteria. A natural hazard spatial multi-criteria analysis could be used to indicate areas where more investigations need to be undertaken from a natural hazard point of view, and to identify areas thought to have higher susceptibility along existing roads where mitigation measures could be targeted after in-situ investigations.

Natural Hazard Susceptibility Assessment for Road Planning Using Spatial Multi-Criteria Analysis.

PubMed

Karlsson, Caroline S J; Kalantari, Zahra; Mörtberg, Ulla; Olofsson, Bo; Lyon, Steve W

2017-11-01

Inadequate infrastructural networks can be detrimental to society if transport between locations becomes hindered or delayed, especially due to natural hazards which are difficult to control. Thus determining natural hazard susceptible areas and incorporating them in the initial planning process, may reduce infrastructural damages in the long run. The objective of this study was to evaluate the usefulness of expert judgments for assessing natural hazard susceptibility through a spatial multi-criteria analysis approach using hydrological, geological, and land use factors. To utilize spatial multi-criteria analysis for decision support, an analytic hierarchy process was adopted where expert judgments were evaluated individually and in an aggregated manner. The estimates of susceptible areas were then compared with the methods weighted linear combination using equal weights and factor interaction method. Results showed that inundation received the highest susceptibility. Using expert judgment showed to perform almost the same as equal weighting where the difference in susceptibility between the two for inundation was around 4%. The results also showed that downscaling could negatively affect the susceptibility assessment and be highly misleading. Susceptibility assessment through spatial multi-criteria analysis is useful for decision support in early road planning despite its limitation to the selection and use of decision rules and criteria. A natural hazard spatial multi-criteria analysis could be used to indicate areas where more investigations need to be undertaken from a natural hazard point of view, and to identify areas thought to have higher susceptibility along existing roads where mitigation measures could be targeted after in-situ investigations.

Development of a decision support system for tsunami evacuation: application to the Jiyang District of Sanya city in China

NASA Astrophysics Data System (ADS)

Hou, Jingming; Yuan, Ye; Wang, Peitao; Ren, Zhiyuan; Li, Xiaojuan

2017-03-01

Major tsunami disasters often cause great damage in the first few hours following an earthquake. The possible severity of such events requires preparations to prevent tsunami disasters or mitigate them. This paper is an attempt to develop a decision support system for rapid tsunami evacuation for local decision makers. Based on the numerical results database of tsunami disasters, this system can quickly obtain the tsunami inundation and travel time. Because numerical models are calculated in advance, this system can reduce decision-making time. Population distribution, as a vulnerability factor, was analyzed to identify areas of high risk for tsunami disasters. Combined with spatial data, this system can comprehensively analyze the dynamic and static evacuation process and identify problems that negatively impact evacuation, thus supporting the decision-making for tsunami evacuation in high-risk areas. When an earthquake and tsunami occur, this system can rapidly obtain the tsunami inundation and travel time and provide information to assist with tsunami evacuation operations.

Supporting NASA Facilities Through GIS

NASA Technical Reports Server (NTRS)

Ingham, Mary E.

2000-01-01

The NASA GIS Team supports NASA facilities and partners in the analysis of spatial data. Geographic Information System (G[S) is an integration of computer hardware, software, and personnel linking topographic, demographic, utility, facility, image, and other geo-referenced data. The system provides a graphic interface to relational databases and supports decision making processes such as planning, design, maintenance and repair, and emergency response.

PREDICTING RELATIVE RISK OF INVASION BY SALTCEDAR AND MUD SNAILS IN RIVER NETWORKS UNDER DIFFERENT SCENARIOS OF CLIMATE CHANGE AND DAM OPERATIONS IN THE WESTERN UNITED STATES

EPA Science Inventory

This synthetic, multi-scale approach will generate a sequence of spatially explicit maps that will provide science guidance to support strategic decision-making regarding the spatially-distributed risk of, and possible adaptation to, the spread of invasive species at local to ...

Evaluating critical uncertainty thresholds in a spatial model of forest pest invasion risk

Treesearch

Frank H. Koch; Denys Yemshanov; Daniel W. McKenney; William D. Smith

2009-01-01

Pest risk maps can provide useful decision support in invasive species management, but most do not adequately consider the uncertainty associated with predicted risk values. This study explores how increased uncertainty in a risk model’s numeric assumptions might affect the resultant risk map. We used a spatial stochastic model, integrating components for...

Forecasting the effects of land-use and climate change on wildlife communities and habitats in the lower Mississippi Valley

USGS Publications Warehouse

Faulkner, Stephen P.

2010-01-01

Landscape patterns and processes reflect both natural ecosystem attributes and the policy and management decisions of individual Federal, State, county, and private organizations. Land-use regulation, water management, and habitat conservation and restoration efforts increasingly rely on landscape-level approaches that incorporate scientific information into the decision-making process. Since management actions are implemented to affect future conditions, decision-support models are necessary to forecast potential future conditions resulting from these decisions. Spatially explicit modeling approaches enable testing of different scenarios and help evaluate potential outcomes of management actions in conjunction with natural processes such as climate change. The ability to forecast the effects of changing land use and climate is critically important to land and resource managers since their work is inherently site specific, yet conservation strategies and practices are expressed at higher spatial and temporal scales that must be considered in the decisionmaking process.

Enhancing User Customization through Novel Software Architecture for Utility Scale Solar Siting Software

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brant Peery; Sam Alessi; Randy Lee

2014-06-01

There is a need for a spatial decision support application that allows users to create customized metrics for comparing proposed locations of a new solar installation. This document discusses how PVMapper was designed to overcome the customization problem through the development of loosely coupled spatial and decision components in a JavaScript plugin architecture. This allows the user to easily add functionality and data to the system. The paper also explains how PVMapper provides the user with a dynamic and customizable decision tool that enables them to visually modify the formulas that are used in the decision algorithms that convert datamore » to comparable metrics. The technologies that make up the presentation and calculation software stack are outlined. This document also explains the architecture that allows the tool to grow through custom plugins created by the software users. Some discussion is given on the difficulties encountered while designing the system.« less

Uncertainty indication in soil function maps - transparent and easy-to-use information to support sustainable use of soil resources

NASA Astrophysics Data System (ADS)

Greiner, Lucie; Nussbaum, Madlene; Papritz, Andreas; Zimmermann, Stephan; Gubler, Andreas; Grêt-Regamey, Adrienne; Keller, Armin

2018-05-01

Spatial information on soil function fulfillment (SFF) is increasingly being used to inform decision-making in spatial planning programs to support sustainable use of soil resources. Soil function maps visualize soils abilities to fulfill their functions, e.g., regulating water and nutrient flows, providing habitats, and supporting biomass production based on soil properties. Such information must be reliable for informed and transparent decision-making in spatial planning programs. In this study, we add to the transparency of soil function maps by (1) indicating uncertainties arising from the prediction of soil properties generated by digital soil mapping (DSM) that are used for soil function assessment (SFA) and (2) showing the response of different SFA methods to the propagation of uncertainties through the assessment. For a study area of 170 km2 in the Swiss Plateau, we map 10 static soil sub-functions for agricultural soils for a spatial resolution of 20 × 20 m together with their uncertainties. Mapping the 10 soil sub-functions using simple ordinal assessment scales reveals pronounced spatial patterns with a high variability of SFF scores across the region, linked to the inherent properties of the soils and terrain attributes and climate conditions. Uncertainties in soil properties propagated through SFA methods generally lead to substantial uncertainty in the mapped soil sub-functions. We propose two types of uncertainty maps that can be readily understood by stakeholders. Cumulative distribution functions of SFF scores indicate that SFA methods respond differently to the propagated uncertainty of soil properties. Even where methods are comparable on the level of complexity and assessment scale, their comparability in view of uncertainty propagation might be different. We conclude that comparable uncertainty indications in soil function maps are relevant to enable informed and transparent decisions on the sustainable use of soil resources.

A discussion for integrating INSPIRE with volunteered geographic information (VGI) and the vision for a global spatial-based platform

NASA Astrophysics Data System (ADS)

Demetriou, Demetris; Campagna, Michele; Racetin, Ivana; Konecny, Milan

2017-09-01

INSPIRE is the EU's authoritative Spatial Data Infrastructure (SDI) in which each Member State provides access to their spatial data across a wide spectrum of data themes to support policy making. In contrast, Volunteered Geographic Information (VGI) is one type of user-generated geographic information where volunteers use the web and mobile devices to create, assemble and disseminate spatial information. There are similarities and differences between SDIs and VGI initiatives, as well as advantages and disadvantages. Thus, the integration of these two data sources will enhance what is offered to end users to facilitate decision makers and the wider community regarding solving complex spatial problems, managing emergency situations and getting useful information for peoples' daily activities. Although some efforts towards this direction have been arisen, several key issues need to be considered and resolved. Further to this integration, the vision is the development of a global integrated GIS platform, which extends the capabilities of a typical data-hub by embedding on-line spatial and non-spatial applications, to deliver both static and dynamic outputs to support planning and decision making. In this context, this paper discusses the challenges of integrating INSPIRE with VGI and outlines a generic framework towards creating a global integrated web-based GIS platform. The tremendous high speed evolution of the Web and Geospatial technologies suggest that this "super" global Geo-system is not far away.

A consumer guide: tools to manage vegetation and fuels.

Treesearch

David L. Peterson; Louisa Evers; Rebecca A. Gravenmier; Ellen Eberhardt

2007-01-01

Current efforts to improve the scientific basis for fire management on public lands will benefit from more efficient transfer of technical information and tools that support planning, implementation, and effectiveness of vegetation and hazardous fuel treatments. The technical scope, complexity, and relevant spatial scale of analytical and decision support tools differ...

Should different impact assessment instruments be integrated? Evidence from English spatial planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tajima, Ryo, E-mail: tajima.ryo@nies.go.jp; Fischer, Thomas B., E-mail: fischer@liverpool.ac.uk

This paper aims at providing empirical evidence to the question as to whether integration of different instruments is achieving its aim in supporting sustainable decision making, focusing on SEA inclusive sustainability appraisal (SA) and other impact assessments (IAs) currently used in English spatial planning. Usage of IAs in addition to SA is established and an analysis of the integration approach (in terms of process, output, and assessor) as well as its effectiveness is conducted. It is found that while integration enhances effectiveness to some extent, too much integration, especially in terms of the procedural element, appears to diminish the overallmore » effectiveness of each IA in influencing decisions as they become captured by the balancing function of SA. -- Highlights: ► The usage of different impact assessments in English spatial planning is clarified. ► The relationship between integration approach and effectiveness is analyzed. ► Results suggest that integration does not necessarily lead to more sustainable decisions. ► Careful consideration is recommended upon process integration.« less

Integrated Forecast-Decision Systems For River Basin Planning and Management

NASA Astrophysics Data System (ADS)

Georgakakos, A. P.

2005-12-01

A central application of climatology, meteorology, and hydrology is the generation of reliable forecasts for water resources management. In principle, effective use of forecasts could improve water resources management by providing extra protection against floods, mitigating the adverse effects of droughts, generating more hydropower, facilitating recreational activities, and minimizing the impacts of extreme events on the environment and the ecosystems. In practice, however, realization of these benefits depends on three requisite elements. First is the skill and reliability of forecasts. Second is the existence of decision support methods/systems with the ability to properly utilize forecast information. And third is the capacity of the institutional infrastructure to incorporate the information provided by the decision support systems into the decision making processes. This presentation discusses several decision support systems (DSS) using ensemble forecasting that have been developed by the Georgia Water Resources Institute for river basin management. These DSS are currently operational in Africa, Europe, and the US and address integrated water resources and energy planning and management in river basins with multiple water uses, multiple relevant temporal and spatial scales, and multiple decision makers. The article discusses the methods used and advocates that the design, development, and implementation of effective forecast-decision support systems must bring together disciplines, people, and institutions necessary to address today's complex water resources challenges.

Bioregional monitoring design and occupancy estimation for two Sierra Nevadan amphibian taxa

EPA Science Inventory

Land-management agencies need quantitative, statistically rigorous monitoring data, often at large spatial and temporal scales, to support resource-management decisions. Monitoring designs typically must accommodate multiple ecological, logistical, political, and economic objec...

Assessment of flood susceptible areas using spatially explicit, probabilistic multi-criteria decision analysis

NASA Astrophysics Data System (ADS)

Tang, Zhongqian; Zhang, Hua; Yi, Shanzhen; Xiao, Yangfan

2018-03-01

GIS-based multi-criteria decision analysis (MCDA) is increasingly used to support flood risk assessment. However, conventional GIS-MCDA methods fail to adequately represent spatial variability and are accompanied with considerable uncertainty. It is, thus, important to incorporate spatial variability and uncertainty into GIS-based decision analysis procedures. This research develops a spatially explicit, probabilistic GIS-MCDA approach for the delineation of potentially flood susceptible areas. The approach integrates the probabilistic and the local ordered weighted averaging (OWA) methods via Monte Carlo simulation, to take into account the uncertainty related to criteria weights, spatial heterogeneity of preferences and the risk attitude of the analyst. The approach is applied to a pilot study for the Gucheng County, central China, heavily affected by the hazardous 2012 flood. A GIS database of six geomorphological and hydrometeorological factors for the evaluation of susceptibility was created. Moreover, uncertainty and sensitivity analysis were performed to investigate the robustness of the model. The results indicate that the ensemble method improves the robustness of the model outcomes with respect to variation in criteria weights and identifies which criteria weights are most responsible for the variability of model outcomes. Therefore, the proposed approach is an improvement over the conventional deterministic method and can provides a more rational, objective and unbiased tool for flood susceptibility evaluation.

Design and implementation of spatial knowledge grid for integrated spatial analysis

NASA Astrophysics Data System (ADS)

Liu, Xiangnan; Guan, Li; Wang, Ping

2006-10-01

Supported by spatial information grid(SIG), the spatial knowledge grid (SKG) for integrated spatial analysis utilizes the middleware technology in constructing the spatial information grid computation environment and spatial information service system, develops spatial entity oriented spatial data organization technology, carries out the profound computation of the spatial structure and spatial process pattern on the basis of Grid GIS infrastructure, spatial data grid and spatial information grid (specialized definition). At the same time, it realizes the complex spatial pattern expression and the spatial function process simulation by taking the spatial intelligent agent as the core to establish space initiative computation. Moreover through the establishment of virtual geographical environment with man-machine interactivity and blending, complex spatial modeling, network cooperation work and spatial community decision knowledge driven are achieved. The framework of SKG is discussed systematically in this paper. Its implement flow and the key technology with examples of overlay analysis are proposed as well.

Involving the public in spatial decision making using Internet GIS

NASA Astrophysics Data System (ADS)

Liu, Zhengrong; Sheng, Grant; Wang, Lei

2006-10-01

Public participation is an integral part of legislation or decision making processes. Traditionally, public participation took place through face-to-face encounters such as public meetings and other fora. However, some important factors limiting the efficiency and effectiveness of this mode of public participation include: geographic separation of participants, scheduling and financial constraints in attending meetings, and limited duration of meetings. These led to the awareness that public participation requires new methods in order to achieve a better democratic decision making. On the other hand, GIS has in the past been accused of being an elitist technology, giving more power to those people already possessing it and depriving those, namely the general public, who more often lack such direct forms of information access. Public participation GIS (PPGIS) is emerging as a distinct subset of two previously separate activities: technology-based spatial analysis and participatory democracy. The paper considers both traditional methods and Internet-based technologies of public participation and argues that new Internet-based technologies have the potential to widen participation by using online spatial decision support systems. GIS and the Internet can be used together to provide the general public with a powerful mechanism for becoming more involved in decision problems. Provision of full access to spatial and non-spatial data, along with the appropriate tools with which to use it, may greatly empower the general public. PPGIS focuses on engaging the public to participate and become involved in a particular subject of interest. It empowers GIS users from all walks of life and enabling them to use the technology purposefully to capture their local knowledge and advance their goals. In the project of public participatory Ontario nuclear waste siting, we focused on developing an Internet based PPGIS prototype to help the public to participate online from inception to the final phase of site decision-making. It shows that in certain siting problems and policy formulation processes, participatory online systems are a useful means of implementing public participation through informing and engaging the public to participate in spatial decision making. Web based PPGIS can involve more participants and higher degree of participation among experts, officials and the pblic than traditional means.

Using spatialized sound cues in an auditorily rich environment

NASA Astrophysics Data System (ADS)

Brock, Derek; Ballas, James A.; Stroup, Janet L.; McClimens, Brian

2004-05-01

Previous Navy research has demonstrated that spatialized sound cues in an otherwise quiet setting are useful for directing attention and improving performance by 16.8% or more in the decision component of a complex dual-task. To examine whether the benefits of this technique are undermined in the presence of additional, unrelated sounds, a background recording of operations in a Navy command center and a voice communications response task [Bolia et al., J. Acoust. Soc. Am. 107, 1065-1066 (2000)] were used to simulate the conditions of an auditorily rich military environment. Without the benefit of spatialized sound cues, performance in the presence of this extraneous auditory information, as measured by decision response times, was an average of 13.6% worse than baseline performance in an earlier study. Performance improved when the cues were present by an average of 18.3%, but this improvement remained below the improvement observed in the baseline study by an average of 11.5%. It is concluded that while the two types of extraneous sound information used in this study degrade performance in the decision task, there is no interaction with the relative performance benefit provided by the use of spatialized auditory cues. [Work supported by ONR.

Multi-Criteria Decision Making for a Spatial Decision Support System on the Analysis of Changing Risk

NASA Astrophysics Data System (ADS)

Olyazadeh, Roya; van Westen, Cees; Bakker, Wim H.; Aye, Zar Chi; Jaboyedoff, Michel; Derron, Marc-Henri

2014-05-01

Natural hazard risk management requires decision making in several stages. Decision making on alternatives for risk reduction planning starts with an intelligence phase for recognition of the decision problems and identifying the objectives. Development of the alternatives and assigning the variable by decision makers to each alternative are employed to the design phase. Final phase evaluates the optimal choice by comparing the alternatives, defining indicators, assigning a weight to each and ranking them. This process is referred to as Multi-Criteria Decision Making analysis (MCDM), Multi-Criteria Evaluation (MCE) or Multi-Criteria Analysis (MCA). In the framework of the ongoing 7th Framework Program "CHANGES" (2011-2014, Grant Agreement No. 263953) of the European Commission, a Spatial Decision Support System is under development, that has the aim to analyse changes in hydro-meteorological risk and provide support to selecting the best risk reduction alternative. This paper describes the module for Multi-Criteria Decision Making analysis (MCDM) that incorporates monetary and non-monetary criteria in the analysis of the optimal alternative. The MCDM module consists of several components. The first step is to define criteria (or Indicators) which are subdivided into disadvantages (criteria that indicate the difficulty for implementing the risk reduction strategy, also referred to as Costs) and advantages (criteria that indicate the favorability, also referred to as benefits). In the next step the stakeholders can use the developed web-based tool for prioritizing criteria and decision matrix. Public participation plays a role in decision making and this is also planned through the use of a mobile web-version where the general local public can indicate their agreement on the proposed alternatives. The application is being tested through a case study related to risk reduction of a mountainous valley in the Alps affected by flooding. Four alternatives are evaluated in this case study namely: construction of defense structures, relocation, implementation of an early warning system and spatial planning regulations. Some of the criteria are determined partly in other modules of the CHANGES SDSS, such as the costs for implementation, the risk reduction in monetary values, and societal risk. Other criteria, which could be environmental, economic, cultural, perception in nature, are defined by different stakeholders such as local authorities, expert organizations, private sector, and local public. In the next step, the stakeholders weight the importance of the criteria by pairwise comparison and visualize the decision matrix, which is a matrix based on criteria versus alternatives values. Finally alternatives are ranked by Analytic Hierarchy Process (AHP) method. We expect that this approach will help the decision makers to ease their works and reduce their costs, because the process is more transparent, more accurate and involves a group decision. In that way there will be more confidence in the overall decision making process. Keywords: MCDM, Analytic Hierarchy Process (AHP), SDSS, Natural Hazard Risk Management

Another look at the question of density and rail transit.

DOT National Transportation Integrated Search

2011-07-01

Long community discussions about rail often include whether a citys spatial distribution of : housing, employment and other trip generators is conducive to supporting rail transit. A citys : decision to construct rail transit is based on an arr...

Designing Dynamic Adaptive Policy Pathways using Many-Objective Robust Decision Making

NASA Astrophysics Data System (ADS)

Kwakkel, Jan; Haasnoot, Marjolijn

2017-04-01

Dealing with climate risks in water management requires confronting a wide variety of deeply uncertain factors, while navigating a many dimensional space of trade-offs amongst objectives. There is an emerging body of literature on supporting this type of decision problem, under the label of decision making under deep uncertainty. Two approaches within this literature are Many-Objective Robust Decision Making, and Dynamic Adaptive Policy Pathways. In recent work, these approaches have been compared. One of the main conclusions of this comparison was that they are highly complementary. Many-Objective Robust Decision Making is a model based decision support approach, while Dynamic Adaptive Policy Pathways is primarily a conceptual framework for the design of flexible strategies that can be adapted over time in response to how the future is actually unfolding. In this research we explore this complementarity in more detail. Specifically, we demonstrate how Many-Objective Robust Decision Making can be used to design adaptation pathways. We demonstrate this combined approach using a water management problem, in the Netherlands. The water level of Lake IJselmeer, the main fresh water resource of the Netherlands, is currently managed through discharge by gravity. Due to climate change, this won't be possible in the future, unless water levels are changed. Changing the water level has undesirable flood risk and spatial planning consequences. The challenge is to find promising adaptation pathways that balance objectives related to fresh water supply, flood risk, and spatial issues, while accounting for uncertain climatic and land use change. We conclude that the combination of Many-Objective Robust Decision Making and Dynamic Adaptive Policy Pathways is particularly suited for dealing with deeply uncertain climate risks.

GIS, modeling, and politics: on the tensions of collaborative decision support.

PubMed

Ramsey, Kevin

2009-05-01

A tension exists at the heart of efforts to support collaboration with GIS. Many scholars and practitioners seek to support two separate objectives: (1) problem solving and (2) the exploration of diverse problem understandings. GIS applications designed for problem solving often pre-define the problem space by structuring the kind of information that can be considered or the way in which the problem is conceptualized. In doing so, they necessarily privilege particular perspectives and understandings of the problem while marginalizing others. As a result, these initiatives undermine their second objective. This is problematic in the context of contentious environmental decisions which have broad-reaching impacts on people with diverse perspectives and interests. In such contexts, I argue that equitable collaboration is impossible without first emphasizing the exploration of diverse problem understandings. I support this argument theoretically by turning to the literatures on collaborative planning and spatial decision support, and empirically in my analysis of a case study of an effort to construct a GIS for supporting collaborative water resource management in rural Idaho. Reflecting upon the case, I provide a set of recommendations to those seeking to better negotiate the tensions of supporting collaboration with GIS in the context of contentious environmental and natural resource decisions.

smokeSALUD: exploring the effect of demographic change on the smoking prevalence at municipality level in Austria.

PubMed

Tomintz, Melanie; Kosar, Bernhard; Clarke, Graham

2016-10-07

Reducing the smoking population is still high on the policy agenda, as smoking leads to many preventable diseases, such as lung cancer, heart disease, diabetes, and more. In Austria, data on smoking prevalence only exists at the federal state level. This provides an interesting overview about the current health situation, but for regional planning authorities these data are often insufficient as they can hide pockets of high and low smoking prevalence in certain municipalities. This paper presents a spatial-temporal change of estimated smokers for municipalities from 2001 and 2011. A synthetic dataset of smokers is built by combining individual large-scale survey data and small area census data using a deterministic spatial microsimulation approach. Statistical analysis, including chi-square test and binary logistic regression, are applied to find the best variables for the simulation model and to validate its results. As no easy-to-use spatial microsimulation software for non-programmers is available yet, a flexible web-based spatial microsimulation application for health decision support (called simSALUD) has been developed and used for these analyses. The results of the simulation show in general a decrease of smoking prevalence within municipalities between 2001 and 2011 and differences within areas are identified. These results are especially valuable to policy decision makers for future planning strategies. This case study shows the application of smokeSALUD to model the spatial-temporal changes in the smoking population in Austria between 2001 and 2011. This is important as no data on smoking exists at this geographical scale (municipality). However, spatial microsimulation models are useful tools to estimate small area health data and to overcome these problems. The simulations and analysis should support health decision makers to identify hot spots of smokers and this should help to show where to spend health resources best in order to reduce health inequalities.

Taking the Next Step: Using Water Quality Data in a Decision Support System for County, State, and Federal Land Managers

NASA Astrophysics Data System (ADS)

Raby, K. S.; Williams, M. W.

2004-12-01

Each passing year amplifies the demands placed on communities across the US in terms of population growth, increased tourism, and stresses resulting from escalated use. The conflicting concerns of recreational users, local citizens, environmentalists, and traditional economic interests cause land managers to contend with controversial decisions regarding development and protection of watersheds. Local history and culture, politics, economic goals, and science are all influential factors in land use decision making. Here we report on a scientific study to determine the sensitivity of alpine areas, and the adaptation of this study into a decision support framework. We use water quality data as an indicator of ecosystem health across a variety of alpine and subalpine landscapes, and input this information into a spatially-based decision support tool that planners can use to make informed land use decisions. We develop this tool in a case study in San Juan County, Colorado, a site chosen because its largest town, Silverton, is a small mountain community experiencing a recent surge in tourism and development, and its fragile high elevation locale makes it more sensitive to environmental changes. Extensive field surveys were conducted in priority drainages throughout the county to map the spatial distribution and aerial extent of landscape types during the summers of 2003 and 2004. Surface water samples were collected and analyzed for inorganic and organic solutes, and water quality values were associated with different land covers to enable sensitivity analysis at the landscape scale. Water quality results for each watershed were entered into a module linked to a geographic information system (GIS), which displays maps of sensitive areas based on criteria selected by the user. The decision support system initially incorporates two major water quality parameters: acid neutralizing capacity (ANC) and nitrate (NO3-) concentration, and several categories of sensitivity were created based on ANC and NO3- levels (e.g., pristine, slightly sensitive, moderately sensitive, highly sensitive, sensitive but unimpacted, disturbance impacted). We based threshold concentrations for these water quality parameters on first principles developed at the Niwot Ridge LTER site. Additional parameters such as specific conductance, base cation concentration, sulfate concentration, and dissolved organic carbon concentration may be added for a particular landscape type. Superimposed on this categorization, federal, state, and county planners are able to make decisions about the degree of potential impairment or enhancement produced by a particular project, or the maximum level of acceptable impairment to a particular area. Because water quality parameters are correlated with landscape types, the model returns a map of the watershed, partitioned by landscape type, presenting the sensitivity level of each area. This format provides land use managers with spatial criteria for project implementation.

The Variable Grid Method, an Approach for the Simultaneous Visualization and Assessment of Spatial Trends and Uncertainty

NASA Astrophysics Data System (ADS)

Rose, K.; Glosser, D.; Bauer, J. R.; Barkhurst, A.

2015-12-01

The products of spatial analyses that leverage the interpolation of sparse, point data to represent continuous phenomena are often presented without clear explanations of the uncertainty associated with the interpolated values. As a result, there is frequently insufficient information provided to effectively support advanced computational analyses and individual research and policy decisions utilizing these results. This highlights the need for a reliable approach capable of quantitatively producing and communicating spatial data analyses and their inherent uncertainties for a broad range of uses. To address this need, we have developed the Variable Grid Method (VGM), and associated Python tool, which is a flexible approach that can be applied to a variety of analyses and use case scenarios where users need a method to effectively study, evaluate, and analyze spatial trends and patterns while communicating the uncertainty in the underlying spatial datasets. The VGM outputs a simultaneous visualization representative of the spatial data analyses and quantification of underlying uncertainties, which can be calculated using data related to sample density, sample variance, interpolation error, uncertainty calculated from multiple simulations, etc. We will present examples of our research utilizing the VGM to quantify key spatial trends and patterns for subsurface data interpolations and their uncertainties and leverage these results to evaluate storage estimates and potential impacts associated with underground injection for CO2 storage and unconventional resource production and development. The insights provided by these examples identify how the VGM can provide critical information about the relationship between uncertainty and spatial data that is necessary to better support their use in advance computation analyses and informing research, management and policy decisions.

Coastal livelihood transitions under globalization with implications for trans-ecosystem interactions.

PubMed

Kramer, Daniel B; Stevens, Kara; Williams, Nicholas E; Sistla, Seeta A; Roddy, Adam B; Urquhart, Gerald R

2017-01-01

Anthropogenic threats to natural systems can be exacerbated due to connectivity between marine, freshwater, and terrestrial ecosystems, complicating the already daunting task of governance across the land-sea interface. Globalization, including new access to markets, can change social-ecological, land-sea linkages via livelihood responses and adaptations by local people. As a first step in understanding these trans-ecosystem effects, we examined exit and entry decisions of artisanal fishers and smallholder farmers on the rapidly globalizing Caribbean coast of Nicaragua. We found that exit and entry decisions demonstrated clear temporal and spatial patterns and that these decisions differed by livelihood. In addition to household characteristics, livelihood exit and entry decisions were strongly affected by new access to regional and global markets. The natural resource implications of these livelihood decisions are potentially profound as they provide novel linkages and spatially-explicit feedbacks between terrestrial and marine ecosystems. Our findings support the need for more scientific inquiry in understanding trans-ecosystem tradeoffs due to linked-livelihood transitions as well as the need for a trans-ecosystem approach to natural resource management and development policy in rapidly changing coastal regions.

DEVELOPMENT OF A DATA EVALUATION/DECISION SUPPORT SYSTEM FOR REMEDIATION OF SUBSURFACE CONTAMINATION

EPA Science Inventory

Subsurface contamination frequently originates from spatially distributed sources of multi-component nonaqueous phase liquids (NAPLs). Such chemicals are typically persistent sources of ground-water contamination that are difficult to characterize. This work addresses the feasi...

Bioenergy Knowledge Discovery Framework Fact Sheet

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

The Bioenergy Knowledge Discovery Framework (KDF) supports the development of a sustainable bioenergy industry by providing access to a variety of data sets, publications, and collaboration and mapping tools that support bioenergy research, analysis, and decision making. In the KDF, users can search for information, contribute data, and use the tools and map interface to synthesize, analyze, and visualize information in a spatially integrated manner.

Data for Renewable Energy Planning, Policy, and Investment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cox, Sarah L

Reliable, robust, and validated data are critical for informed planning, policy development, and investment in the clean energy sector. The Renewable Energy (RE) Explorer was developed to support data-driven renewable energy analysis that can inform key renewable energy decisions globally. This document presents the types of geospatial and other data at the core of renewable energy analysis and decision making. Individual data sets used to inform decisions vary in relation to spatial and temporal resolution, quality, and overall usefulness. From Data to Decisions, a complementary geospatial data and analysis decision guide, provides an in-depth view of these and other considerationsmore » to enable data-driven planning, policymaking, and investment. Data support a wide variety of renewable energy analyses and decisions, including technical and economic potential assessment, renewable energy zone analysis, grid integration, risk and resiliency identification, electrification, and distributed solar photovoltaic potential. This fact sheet provides information on the types of data that are important for renewable energy decision making using the RE Data Explorer or similar types of geospatial analysis tools.« less

RiskChanges Spatial Decision Support system for the analysis of changing multi-hazard risk

NASA Astrophysics Data System (ADS)

van Westen, Cees; Zhang, Kaixi; Bakker, Wim; Andrejchenko, Vera; Berlin, Julian; Olyazadeh, Roya; Cristal, Irina

2015-04-01

Within the framework of the EU FP7 Marie Curie Project CHANGES and the EU FP7 Copernicus project INCREO a spatial decision support system was developed with the aim to analyse the effect of risk reduction planning alternatives on reducing the risk now and in the future, and support decision makers in selecting the best alternatives. Central to the SDSS are the stakeholders. The envisaged users of the system are organizations involved in planning of risk reduction measures, and that have staff capable of visualizing and analyzing spatial data at a municipal scale. The SDSS should be able to function in different countries with different legal frameworks and with organizations with different mandates. These could be subdivided into Civil protection organization with the mandate to design disaster response plans, Expert organizations with the mandate to design structural risk reduction measures (e.g. dams, dikes, check-dams etc), and planning organizations with the mandate to make land development plans. The SDSS can be used in different ways: analyzing the current level of risk, analyzing the best alternatives for risk reduction, the evaluation of the consequences of possible future scenarios to the risk levels, and the evaluation how different risk reduction alternatives will lead to risk reduction under different future scenarios. The SDSS is developed based on open source software and following open standards, for code as well as for data formats and service interfaces. Code development was based upon open source software as well. The architecture of the system is modular. The various parts of the system are loosely coupled, extensible, using standards for interoperability, flexible and web-based. The Spatial Decision Support System is composed of a number of integrated components. The Risk Assessment component allows to carry out spatial risk analysis, with different degrees of complexity, ranging from simple exposure (overlay of hazard and assets maps) to quantitative analysis (using different hazard types, temporal scenarios and vulnerability curves) resulting into risk curves. The platform does not include a component to calculate hazard maps, and existing hazard maps are used as input data for the risk component. The second component of the SDSS is a risk reduction planning component, which forms the core of the platform. This component includes the definition of risk reduction alternatives (related to disaster response planning, risk reduction measures and spatial planning) and links back to the risk assessment module to calculate the new level of risk if the measure is implemented, and a cost-benefit (or cost-effectiveness/ Spatial Multi Criteria Evaluation) component to compare the alternatives and make decision on the optimal one. The third component of the SDSS is a temporal scenario component, which allows to define future scenarios in terms of climate change, land use change and population change, and the time periods for which these scenarios will be made. The component doesn't generate these scenarios but uses input maps for the effect of the scenarios on the hazard and assets maps. The last component is a communication and visualization component, which can compare scenarios and alternatives, not only in the form of maps, but also in other forms (risk curves, tables, graphs)

Evaluation of SOVAT: an OLAP-GIS decision support system for community health assessment data analysis.

PubMed

Scotch, Matthew; Parmanto, Bambang; Monaco, Valerie

2008-06-09

Data analysis in community health assessment (CHA) involves the collection, integration, and analysis of large numerical and spatial data sets in order to identify health priorities. Geographic Information Systems (GIS) enable for management and analysis using spatial data, but have limitations in performing analysis of numerical data because of its traditional database architecture.On-Line Analytical Processing (OLAP) is a multidimensional datawarehouse designed to facilitate querying of large numerical data. Coupling the spatial capabilities of GIS with the numerical analysis of OLAP, might enhance CHA data analysis. OLAP-GIS systems have been developed by university researchers and corporations, yet their potential for CHA data analysis is not well understood. To evaluate the potential of an OLAP-GIS decision support system for CHA problem solving, we compared OLAP-GIS to the standard information technology (IT) currently used by many public health professionals. SOVAT, an OLAP-GIS decision support system developed at the University of Pittsburgh, was compared against current IT for data analysis for CHA. For this study, current IT was considered the combined use of SPSS and GIS ("SPSS-GIS"). Graduate students, researchers, and faculty in the health sciences at the University of Pittsburgh were recruited. Each round consisted of: an instructional video of the system being evaluated, two practice tasks, five assessment tasks, and one post-study questionnaire. Objective and subjective measurement included: task completion time, success in answering the tasks, and system satisfaction. Thirteen individuals participated. Inferential statistics were analyzed using linear mixed model analysis. SOVAT was statistically significant (alpha = .01) from SPSS-GIS for satisfaction and time (p < .002). Descriptive results indicated that participants had greater success in answering the tasks when using SOVAT as compared to SPSS-GIS. Using SOVAT, tasks were completed more efficiently, with a higher rate of success, and with greater satisfaction, than the combined use of SPSS and GIS. The results from this study indicate a potential for OLAP-GIS decision support systems as a valuable tool for CHA data analysis.

Evaluation of SOVAT: An OLAP-GIS decision support system for community health assessment data analysis

PubMed Central

Scotch, Matthew; Parmanto, Bambang; Monaco, Valerie

2008-01-01

Background Data analysis in community health assessment (CHA) involves the collection, integration, and analysis of large numerical and spatial data sets in order to identify health priorities. Geographic Information Systems (GIS) enable for management and analysis using spatial data, but have limitations in performing analysis of numerical data because of its traditional database architecture. On-Line Analytical Processing (OLAP) is a multidimensional datawarehouse designed to facilitate querying of large numerical data. Coupling the spatial capabilities of GIS with the numerical analysis of OLAP, might enhance CHA data analysis. OLAP-GIS systems have been developed by university researchers and corporations, yet their potential for CHA data analysis is not well understood. To evaluate the potential of an OLAP-GIS decision support system for CHA problem solving, we compared OLAP-GIS to the standard information technology (IT) currently used by many public health professionals. Methods SOVAT, an OLAP-GIS decision support system developed at the University of Pittsburgh, was compared against current IT for data analysis for CHA. For this study, current IT was considered the combined use of SPSS and GIS ("SPSS-GIS"). Graduate students, researchers, and faculty in the health sciences at the University of Pittsburgh were recruited. Each round consisted of: an instructional video of the system being evaluated, two practice tasks, five assessment tasks, and one post-study questionnaire. Objective and subjective measurement included: task completion time, success in answering the tasks, and system satisfaction. Results Thirteen individuals participated. Inferential statistics were analyzed using linear mixed model analysis. SOVAT was statistically significant (α = .01) from SPSS-GIS for satisfaction and time (p < .002). Descriptive results indicated that participants had greater success in answering the tasks when using SOVAT as compared to SPSS-GIS. Conclusion Using SOVAT, tasks were completed more efficiently, with a higher rate of success, and with greater satisfaction, than the combined use of SPSS and GIS. The results from this study indicate a potential for OLAP-GIS decision support systems as a valuable tool for CHA data analysis. PMID:18541037

Seventh symposium on systems analysis in forest resources; 1997 May 28-31; Traverse City, MI.

Treesearch

J. Michael Vasievich; Jeremy S. Fried; Larry A. Leefers

2000-01-01

This international symposium included presentations by representatives from government, academic, and private institutions. Topics covered management objectives; information systems: modeling, optimization, simulation and decision support techniques; spatial methods; timber supply; and economic and operational analyses.

NASA Remote Sensing Observations for Water Resource and Infrastructure Management

NASA Astrophysics Data System (ADS)

Granger, S. L.; Armstrong, L.; Farr, T.; Geller, G.; Heath, E.; Hyon, J.; Lavoie, S.; McDonald, K.; Realmuto, V.; Stough, T.; Szana, K.

2008-12-01

Decision support tools employed by water resource and infrastructure managers often utilize data products obtained from local sources or national/regional databases of historic surveys and observations. Incorporation of data from these sources can be laborious and time consuming as new products must be identified, cleaned and archived for each new study site. Adding remote sensing observations to the list of sources holds promise for a timely, consistent, global product to aid decision support at regional and global scales by providing global observations of geophysical parameters including soil moisture, precipitation, atmospheric temperature, derived evapotranspiration, and snow extent needed for hydrologic models and decision support tools. However, issues such as spatial and temporal resolution arise when attempting to integrate remote sensing observations into existing decision support tools. We are working to overcome these and other challenges through partnerships with water resource managers, tool developers and other stakeholders. We are developing a new data processing framework, enabled by a core GIS server, to seamlessly pull together observations from disparate sources for synthesis into information products and visualizations useful to the water resources community. A case study approach is being taken to develop the system by working closely with water infrastructure and resource managers to integrate remote observations into infrastructure, hydrologic and water resource decision tools. We present the results of a case study utilizing observations from the PALS aircraft instrument as a proxy for NASA's upcoming Soil Moisture Active Passive (SMAP) mission and an existing commercial decision support tool.

Leveraging Trillions of Pixels for Flood Mitigation Decisions Support in the Rio Salado Basin, Argentina

NASA Astrophysics Data System (ADS)

Sullivan, J.; Routh, D.; Tellman, B.; Doyle, C.; Tomlin, J. N.

2017-12-01

The Rio Salado River Basin in Argentina is an economically important region that generates 25-30 percent of Argentina's grain and meat production. Between 2000-2011, floods in the basin caused nearly US$4.5 billion in losses and affected 5.5 million people. With the goal of developing cost-efficient flood monitoring and prediction capabilities in the Rio Salado Basin to support decision making, Cloud to Street is developing satellite based analytics to cover information gaps and improve monitoring capacity. This talk will showcase the Flood Risk Dashboard developed by Cloud to Street to support monitoring and decision-making at the level of provincial and national water management agencies in the Rio Salado Watershed. The Dashboard is based on analyzing thousands of MODIS, Landsat, and Sentinel scenes in Google Earth Engine to reconstruct the spatial history of flooding in the basin. The tool, iteratively designed with the end-user, shows a history of floodable areas with specific return times, exposed land uses and population, precipitation hyetographs, and spatial and temporal flood trends in the basin. These trends are used to understand both the impact of past flood mitigation investments (i.e. wetland reconstruction) and identify shifting flood risks. Based on this experience, we will also describe best practices on making remote sensing "flood dashboards" for water agencies.

Geospatial Data Fusion and Multigroup Decision Support for Surface Water Quality Management

NASA Astrophysics Data System (ADS)

Sun, A. Y.; Osidele, O.; Green, R. T.; Xie, H.

2010-12-01

Social networking and social media have gained significant popularity and brought fundamental changes to many facets of our everyday life. With the ever-increasing adoption of GPS-enabled gadgets and technology, location-based content is likely to play a central role in social networking sites. While location-based content is not new to the geoscience community, where geographic information systems (GIS) are extensively used, the delivery of useful geospatial data to targeted user groups for decision support is new. Decision makers and modelers ought to make more effective use of the new web-based tools to expand the scope of environmental awareness education, public outreach, and stakeholder interaction. Environmental decision processes are often rife with uncertainty and controversy, requiring integration of multiple sources of information and compromises between diverse interests. Fusing of multisource, multiscale environmental data for multigroup decision support is a challenging task. Toward this goal, a multigroup decision support platform should strive to achieve transparency, impartiality, and timely synthesis of information. The latter criterion often constitutes a major technical bottleneck to traditional GIS-based media, featuring large file or image sizes and requiring special processing before web deployment. Many tools and design patterns have appeared in recent years to ease the situation somewhat. In this project, we explore the use of Web 2.0 technologies for “pushing” location-based content to multigroups involved in surface water quality management and decision making. In particular, our granular bottom-up approach facilitates effective delivery of information to most relevant user groups. Our location-based content includes in-situ and remotely sensed data disseminated by NASA and other national and local agencies. Our project is demonstrated for managing the total maximum daily load (TMDL) program in the Arroyo Colorado coastal river basin in Texas. The overall design focuses on assigning spatial information to decision support elements and on efficiently using Web 2.0 technologies to relay scientific information to the nonscientific community. We conclude that (i) social networking, if appropriately used, has great potential for mitigating difficulty associated with multigroup decision making; (ii) all potential stakeholder groups should be involved in creating a useful decision support system; and (iii) environmental decision support systems should be considered a must-have, instead of an optional component of TMDL decision support projects. Acknowledgment: This project was supported by NASA grant NNX09AR63G.

`spup' - An R Package for Analysis of Spatial Uncertainty Propagation and Application to Trace Gas Emission Simulations

NASA Astrophysics Data System (ADS)

Sawicka, K.; Breuer, L.; Houska, T.; Santabarbara Ruiz, I.; Heuvelink, G. B. M.

2016-12-01

Computer models have become a crucial tool in engineering and environmental sciences for simulating the behaviour of complex static and dynamic systems. However, while many models are deterministic, the uncertainty in their predictions needs to be estimated before they are used for decision support. Advances in uncertainty propagation analysis and assessment have been paralleled by a growing number of software tools for uncertainty analysis, but none has gained recognition for a universal applicability, including case studies with spatial models and spatial model inputs. Due to the growing popularity and applicability of the open source R programming language we undertook a project to develop an R package that facilitates uncertainty propagation analysis in spatial environmental modelling. In particular, the `spup' package provides functions for examining the uncertainty propagation starting from input data and model parameters, via the environmental model onto model predictions. The functions include uncertainty model specification, stochastic simulation and propagation of uncertainty using Monte Carlo techniques, as well as several uncertainty visualization functions. Here we will demonstrate that the 'spup' package is an effective and easy-to-use tool to be applied even in a very complex study case, and that it can be used in multi-disciplinary research and model-based decision support. As an example, we use the ecological LandscapeDNDC model to analyse propagation of uncertainties associated with spatial variability of the model driving forces such as rainfall, nitrogen deposition and fertilizer inputs. The uncertainty propagation is analysed for the prediction of emissions of N2O and CO2 for a German low mountainous, agriculturally developed catchment. The study tests the effect of spatial correlations on spatially aggregated model outputs, and could serve as an advice for developing best management practices and model improvement strategies.

An integrated crop model and GIS decision support system for assisting agronomic decision making under climate change.

PubMed

Kadiyala, M D M; Nedumaran, S; Singh, Piara; S, Chukka; Irshad, Mohammad A; Bantilan, M C S

2015-07-15

The semi-arid tropical (SAT) regions of India are suffering from low productivity which may be further aggravated by anticipated climate change. The present study analyzes the spatial variability of climate change impacts on groundnut yields in the Anantapur district of India and examines the relative contribution of adaptation strategies. For this purpose, a web based decision support tool that integrates crop simulation model and Geographical Information System (GIS) was developed to assist agronomic decision making and this tool can be scalable to any location and crop. The climate change projections of five global climate models (GCMs) relative to the 1980-2010 baseline for Anantapur district indicates an increase in rainfall activity to the tune of 10.6 to 25% during Mid-century period (2040-69) with RCP 8.5. The GCMs also predict warming exceeding 1.4 to 2.4°C by 2069 in the study region. The spatial crop responses to the projected climate indicate a decrease in groundnut yields with four GCMs (MPI-ESM-MR, MIROC5, CCSM4 and HadGEM2-ES) and a contrasting 6.3% increase with the GCM, GFDL-ESM2M. The simulation studies using CROPGRO-Peanut model reveals that groundnut yields can be increased on average by 1.0%, 5.0%, 14.4%, and 20.2%, by adopting adaptation options of heat tolerance, drought tolerant cultivars, supplemental irrigation and a combination of drought tolerance cultivar and supplemental irrigation respectively. The spatial patterns of relative benefits of adaptation options were geographically different and the greatest benefits can be achieved by adopting new cultivars having drought tolerance and with the application of one supplemental irrigation at 60days after sowing. Copyright © 2015 Elsevier B.V. All rights reserved.

An Intelligent Polar Cyberinfrastrucuture to Support Spatiotemporal Decision Making

NASA Astrophysics Data System (ADS)

Song, M.; Li, W.; Zhou, X.

2014-12-01

In the era of big data, polar sciences have already faced an urgent demand of utilizing intelligent approaches to support precise and effective spatiotemporal decision-making. Service-oriented cyberinfrastructure has advantages of seamlessly integrating distributed computing resources, and aggregating a variety of geospatial data derived from Earth observation network. This paper focuses on building a smart service-oriented cyberinfrastructure to support intelligent question answering related to polar datasets. The innovation of this polar cyberinfrastructure includes: (1) a problem-solving environment that parses geospatial question in natural language, builds geoprocessing rules, composites atomic processing services and executes the entire workflow; (2) a self-adaptive spatiotemporal filter that is capable of refining query constraints through semantic analysis; (3) a dynamic visualization strategy to support results animation and statistics in multiple spatial reference systems; and (4) a user-friendly online portal to support collaborative decision-making. By means of this polar cyberinfrastructure, we intend to facilitate integration of distributed and heterogeneous Arctic datasets and comprehensive analysis of multiple environmental elements (e.g. snow, ice, permafrost) to provide a better understanding of the environmental variation in circumpolar regions.

Assessment of a Bayesian Belief Network-GIS framework as a practical tool to support marine planning.

PubMed

Stelzenmüller, V; Lee, J; Garnacho, E; Rogers, S I

2010-10-01

For the UK continental shelf we developed a Bayesian Belief Network-GIS framework to visualise relationships between cumulative human pressures, sensitive marine landscapes and landscape vulnerability, to assess the consequences of potential marine planning objectives, and to map uncertainty-related changes in management measures. Results revealed that the spatial assessment of footprints and intensities of human activities had more influence on landscape vulnerabilities than the type of landscape sensitivity measure used. We addressed questions regarding consequences of potential planning targets, and necessary management measures with spatially-explicit assessment of their consequences. We conclude that the BN-GIS framework is a practical tool allowing for the visualisation of relationships, the spatial assessment of uncertainty related to spatial management scenarios, the engagement of different stakeholder views, and enables a quick update of new spatial data and relationships. Ultimately, such BN-GIS based tools can support the decision-making process used in adaptive marine management. Copyright © 2010 Elsevier Ltd. All rights reserved.

GeoProMT: A Collaborative Platform Supporting Natural Hazards Project Management From Assessment to Resilience

NASA Astrophysics Data System (ADS)

Renschler, C.; Sheridan, M. F.; Patra, A. K.

2008-05-01

The impact and consequences of extreme geophysical events (hurricanes, floods, wildfires, volcanic flows, mudflows, etc.) on properties and processes should be continuously assessed by a well-coordinated interdisciplinary research and outreach approach addressing risk assessment and resilience. Communication between various involved disciplines and stakeholders is the key to a successful implementation of an integrated risk management plan. These issues become apparent at the level of decision support tools for extreme events/disaster management in natural and managed environments. The Geospatial Project Management Tool (GeoProMT) is a collaborative platform for research and training to document and communicate the fundamental steps in transforming information for extreme events at various scales for analysis and management. GeoProMT is an internet-based interface for the management of shared geo-spatial and multi-temporal information such as measurements, remotely sensed images, and other GIS data. This tool enhances collaborative research activities and the ability to assimilate data from diverse sources by integrating information management. This facilitates a better understanding of natural processes and enhances the integrated assessment of resilience against both the slow and fast onset of hazard risks. Fundamental to understanding and communicating complex natural processes are: (a) representation of spatiotemporal variability, extremes, and uncertainty of environmental properties and processes in the digital domain, (b) transformation of their spatiotemporal representation across scales (e.g. interpolation, aggregation, disaggregation.) during data processing and modeling in the digital domain, and designing and developing tools for (c) geo-spatial data management, and (d) geo-spatial process modeling and effective implementation, and (e) supporting decision- and policy-making in natural resources and hazard management at various spatial and temporal scales of interest. GeoProMT is useful for researchers, practitioners, and decision-makers, because it provides an integrated environmental system assessment and data management approach that considers the spatial and temporal scales and variability in natural processes. Particularly in the occurrence or onset of extreme events it can utilize the latest data sources that are available at variable scales, combine them with existing information, and update assessment products such as risk and vulnerability assessment maps. Because integrated geo-spatial assessment requires careful consideration of all the steps in utilizing data, modeling and decision-making formats, each step in the sequence must be assessed in terms of how information is being scaled. At the process scale various geophysical models (e.g. TITAN, LAHARZ, or many other examples) are appropriate for incorporation in the tool. Some examples that illustrate our approach include: 1) coastal parishes impacted by Hurricane Rita (Southwestern Louisiana), 2) a watershed affected by extreme rainfall induced debris-flows (Madison County, Virginia; Panabaj, Guatemala; Casita, Nicaragua), and 3) the potential for pyroclastic flows to threaten a city (Tungurahua, Ecuador). This research was supported by the National Science Foundation.

Generalized Cartographic and Simultaneous Representation of Utility Networks for Decision-Support Systems and Crisis Management in Urban Environments

NASA Astrophysics Data System (ADS)

Becker, T.; König, G.

2015-10-01

Cartographic visualizations of crises are used to create a Common Operational Picture (COP) and enforce Situational Awareness by presenting relevant information to the involved actors. As nearly all crises affect geospatial entities, geo-data representations have to support location-specific analysis throughout the decision-making process. Meaningful cartographic presentation is needed for coordinating the activities of crisis manager in a highly dynamic situation, since operators' attention span and their spatial memories are limiting factors during the perception and interpretation process. Situational Awareness of operators in conjunction with a COP are key aspects in decision-making process and essential for making well thought-out and appropriate decisions. Considering utility networks as one of the most complex and particularly frequent required systems in urban environment, meaningful cartographic presentation of multiple utility networks with respect to disaster management do not exist. Therefore, an optimized visualization of utility infrastructure for emergency response procedures is proposed. The article will describe a conceptual approach on how to simplify, aggregate, and visualize multiple utility networks and their components to meet the requirements of the decision-making process and to support Situational Awareness.

Enriching Spatial Data Infrastructure (sdi) by User Generated Contents for Transportation

NASA Astrophysics Data System (ADS)

Shakeri, M.; Alimohammadi, A.; Sadeghi-Niaraki, A.; Alesheikh, A. A.

2013-09-01

Spatial data is one of the most critical elements underpinning decision making for many disciplines. Accessing and sharing spatial data have always been a great struggle for researchers. Spatial data infrastructure (SDI) plays a key role in spatial data sharing by building a suitable platform for collaboration and cooperation among the different data producer organizations. In recent years, SDI vision has been moved toward a user-centric platform which has led to development of a new and enriched generation of SDI (third generation). This vision is to provide an environment where users can cooperate to handle spatial data in an effective and satisfactory way. User-centric SDI concentrates on users, their requirements and preferences while in the past, SDI initiatives were mainly concentrated on technological issues such as the data harmonization, standardized metadata models, standardized web services for data discovery, visualization and download. On the other hand, new technologies such as the GPS-equipped smart phones, navigation devices and Web 2.0 technologies have enabled citizens to actively participate in production and sharing of the spatial information. This has led to emergence of the new phenomenon called the Volunteered Geographic Information (VGI). VGI describes any type of content that has a geographic element which has been voluntarily collected. However, its distinctive element is the geographic information that can be collected and produced by citizens with different formal expertise and knowledge of the spatial or geographical concepts. Therefore, ordinary citizens can cooperate in providing massive sources of information that cannot be ignored. These can be considered as the valuable spatial information sources in SDI. These sources can be used for completing, improving and updating of the existing databases. Spatial information and technologies are an important part of the transportation systems. Planning, design and operation of the transportation systems requires the exchange of large volumes of spatial data and often close cooperation among the various organizations. However, there is no technical and organizational process to get a suitable data infrastructure to address diverse needs of the transportation. Hence, development of a common standards and a simple data exchange mechanism is strongly needed in the field of transportation for decision support. Since one of the main purposes of transportation projects is to improve the quality of services provided to users, it is necessary to involve the users themselves in the decision making processes. This should be done through a public participation and involvement in all stages of the transportation projects. In other words, using public knowledge and information as another source of information is very important to make better and more efficient decisions. Public participation in transportation projects can also help organizations to enhance their public supports; because the lack of public support can lead to failure of technically valid projects. However, due to complexity of the transportation tasks, lack of appropriate environment and methods for facilitation of the public participation, collection and analysis of the public information and opinions, public participation in this field has not been well considered so far. This paper reviews the previous researches based on the enriched SDI development and its movement toward the VGI by focusing on the public participation in transportation projects. To this end, methods and models that have been used in previous researches are studied and classified initially. Then, methods of the previous researchers on VGI and transportation are conceptualized in SDI. Finally, the suggested method for transportation projects is presented. Results indicate success of the new generation of SDI in integration with public participation for transportation projects.

All Source Solution Decision Support Products Created for Stennis Space Center in Response to Hurricane Katrina

NASA Technical Reports Server (NTRS)

Ross, Kenton W.; Graham, William D.

2007-01-01

In the aftermath of Hurricane Katrina and in response to the needs of SSC (Stennis Space Center), NASA required the generation of decision support products with a broad range of geospatial inputs. Applying a systems engineering approach, the NASA ARTPO (Applied Research and Technology Project Office) at SSC evaluated the Center's requirements and source data quality. ARTPO identified data and information products that had the potential to meet decision-making requirements; included were remotely sensed data ranging from high-spatial-resolution aerial images through high-temporal-resolution MODIS (Moderate Resolution Imaging Spectroradiometer) products. Geospatial products, such as FEMA's (Federal Emergency Management Agency's) Advisory Base Flood Elevations, were also relevant. Where possible, ARTPO applied SSC calibration/validation expertise to both clarify the quality of various data source options and to validate that the inputs that were finally chosen met SSC requirements. ARTPO integrated various information sources into multiple decision support products, including two maps: Hurricane Katrina Inundation Effects at Stennis Space Center (highlighting surge risk posture) and Vegetation Change In and Around Stennis Space Center: Katrina and Beyond (highlighting fire risk posture).

Design and implementation of visualization methods for the CHANGES Spatial Decision Support System

NASA Astrophysics Data System (ADS)

Cristal, Irina; van Westen, Cees; Bakker, Wim; Greiving, Stefan

2014-05-01

The CHANGES Spatial Decision Support System (SDSS) is a web-based system aimed for risk assessment and the evaluation of optimal risk reduction alternatives at local level as a decision support tool in long-term natural risk management. The SDSS use multidimensional information, integrating thematic, spatial, temporal and documentary data. The role of visualization in this context becomes of vital importance for efficiently representing each dimension. This multidimensional aspect of the required for the system risk information, combined with the diversity of the end-users imposes the use of sophisticated visualization methods and tools. The key goal of the present work is to exploit efficiently the large amount of data in relation to the needs of the end-user, utilizing proper visualization techniques. Three main tasks have been accomplished for this purpose: categorization of the end-users, the definition of system's modules and the data definition. The graphical representation of the data and the visualization tools were designed to be relevant to the data type and the purpose of the analysis. Depending on the end-users category, each user should have access to different modules of the system and thus, to the proper visualization environment. The technologies used for the development of the visualization component combine the latest and most innovative open source JavaScript frameworks, such as OpenLayers 2.13.1, ExtJS 4 and GeoExt 2. Moreover, the model-view-controller (MVC) pattern is used in order to ensure flexibility of the system at the implementation level. Using the above technologies, the visualization techniques implemented so far offer interactive map navigation, querying and comparison tools. The map comparison tools are of great importance within the SDSS and include the following: swiping tool for comparison of different data of the same location; raster subtraction for comparison of the same phenomena varying in time; linked views for comparison of data from different locations and a time slider tool for monitoring changes in spatio-temporal data. All these techniques are part of the interactive interface of the system and make use of spatial and spatio-temporal data. Further significant aspects of the visualization component include conventional cartographic techniques and visualization of non-spatial data. The main expectation from the present work is to offer efficient visualization of risk-related data in order to facilitate the decision making process, which is the final purpose of the CHANGES SDSS. This work is part of the "CHANGES" project, funded by the European Community's 7th Framework Programme.

GEOGRAPHICAL INFORMATION SYSTEM, DECISION SUPPORT SYSTEMS, AND URBAN STORMWATER MANAGEMENT

EPA Science Inventory

The full report reviews the application of Geographic Inforamtion System (GIS) technology to the field of urban stormwater modeling. The GIS literature is reviewed in the context of its use as a spatial database for urban stormwater modeling, integration of GIS and hydroloic time...

Ecosystem informaties for natural history data - Developing an integrated framework for biological and geographic data

EPA Science Inventory

Threats to the ecological integrity of marine and estuarine systems operate over many spatial scales, from nutrient enrichment at watershed/estuarine linkages to invasive species and climate change at regional/global scales. Decision support tools and information systems needed t...

EnviroAtlas: Two Use Cases in the EnviroAtlas

EPA Science Inventory

EnviroAtlas is an online spatial decision support tool for viewing and analyzing the supply, demand, and drivers of change related to natural and built infrastructure at multiple scales for the nation. To maximize usefulness to a broad range of users, EnviroAtlas contains trainin...

EnviroAtlas: Incorporation of Community-Scale Data for Additional Communities

EPA Science Inventory

EnviroAtlas is ORD’s online spatial decision support tool for viewing and analyzing the supply, demand, and drivers of change related to natural and built infrastructure at multiple scales for the nation. Maps and text identify known relationships between the goods and services ...

Acquisition and management of continuous data streams for crop water management

USDA-ARS?s Scientific Manuscript database

Wireless sensor network systems for decision support in crop water management offer many advantages including larger spatial coverage and multiple types of data input. However, collection and management of multiple and continuous data streams for near real-time post analysis can be problematic. Thi...

Data Model for Multi Hazard Risk Assessment Spatial Support Decision System

NASA Astrophysics Data System (ADS)

Andrejchenko, Vera; Bakker, Wim; van Westen, Cees

2014-05-01

The goal of the CHANGES Spatial Decision Support System is to support end-users in making decisions related to risk reduction measures for areas at risk from multiple hydro-meteorological hazards. The crucial parts in the design of the system are the user requirements, the data model, the data storage and management, and the relationships between the objects in the system. The implementation of the data model is carried out entirely with an open source database management system with a spatial extension. The web application is implemented using open source geospatial technologies with PostGIS as the database, Python for scripting, and Geoserver and javascript libraries for visualization and the client-side user-interface. The model can handle information from different study areas (currently, study areas from France, Romania, Italia and Poland are considered). Furthermore, the data model handles information about administrative units, projects accessible by different types of users, user-defined hazard types (floods, snow avalanches, debris flows, etc.), hazard intensity maps of different return periods, spatial probability maps, elements at risk maps (buildings, land parcels, linear features etc.), economic and population vulnerability information dependent on the hazard type and the type of the element at risk, in the form of vulnerability curves. The system has an inbuilt database of vulnerability curves, but users can also add their own ones. Included in the model is the management of a combination of different scenarios (e.g. related to climate change, land use change or population change) and alternatives (possible risk-reduction measures), as well as data-structures for saving the calculated economic or population loss or exposure per element at risk, aggregation of the loss and exposure using the administrative unit maps, and finally, producing the risk maps. The risk data can be used for cost-benefit analysis (CBA) and multi-criteria evaluation (SMCE). The data model includes data-structures for CBA and SMCE. The model is at the stage where risk and cost-benefit calculations can be stored but the remaining part is currently under development. Multi-criteria information, user management and the relation of these with the rest of the model is our next step. Having a carefully designed data model plays a crucial role in the development of the whole system for rapid development, keeping the data consistent, and in the end, support the end-user in making good decisions in risk-reduction measures related to multiple natural hazards. This work is part of the EU FP7 Marie Curie ITN "CHANGES"project (www.changes-itn.edu)

Coastal livelihood transitions under globalization with implications for trans-ecosystem interactions

PubMed Central

Stevens, Kara; Williams, Nicholas E.; Sistla, Seeta A.; Roddy, Adam B.; Urquhart, Gerald R.

2017-01-01

Anthropogenic threats to natural systems can be exacerbated due to connectivity between marine, freshwater, and terrestrial ecosystems, complicating the already daunting task of governance across the land-sea interface. Globalization, including new access to markets, can change social-ecological, land-sea linkages via livelihood responses and adaptations by local people. As a first step in understanding these trans-ecosystem effects, we examined exit and entry decisions of artisanal fishers and smallholder farmers on the rapidly globalizing Caribbean coast of Nicaragua. We found that exit and entry decisions demonstrated clear temporal and spatial patterns and that these decisions differed by livelihood. In addition to household characteristics, livelihood exit and entry decisions were strongly affected by new access to regional and global markets. The natural resource implications of these livelihood decisions are potentially profound as they provide novel linkages and spatially-explicit feedbacks between terrestrial and marine ecosystems. Our findings support the need for more scientific inquiry in understanding trans-ecosystem tradeoffs due to linked-livelihood transitions as well as the need for a trans-ecosystem approach to natural resource management and development policy in rapidly changing coastal regions. PMID:29077748

Evaluating PRISM precipitation grid data as possible surrogates for station data at four sites in Oklahoma

USDA-ARS?s Scientific Manuscript database

The development of climate-sensitive decision support for agriculture or water resource management requires long time series of monthly precipitation for specific locations. Archived station data for many locations is available, but time continuity, quality, and spatial coverage of station data rem...

Multi-profile analysis of soil moisture within the U.S. Climate Reference Network

USDA-ARS?s Scientific Manuscript database

Soil moisture estimates are crucial for hydrologic modeling and agricultural decision-support efforts. These measurements are also pivotal for long-term inquiries regarding the impacts of climate change and the resulting droughts over large spatial and temporal scales. However, it has only been t...

A Random Forest Approach to Predict the Spatial Distribution of Sediment Pollution in an Estuarine System

EPA Science Inventory

Modeling the magnitude and distribution of sediment-bound pollutants in estuaries is often limited by incomplete knowledge of the site and inadequate sample density. To address these modeling limitations, a decision-support tool framework was conceived that predicts sediment cont...

Stable isotopes to trace food web stressors: Is space the final frontier?

EPA Science Inventory

To support community decision-making, we need to evaluate sources of stress and impact at a variety of spatial scales, whether local or watershed-based. Increasingly, we are using stable isotope-based approaches to determine those scales of impact, and using these approaches in v...

Spatially targeted social interventions to improve BMP adoption in Maryland watersheds

USDA-ARS?s Scientific Manuscript database

The results of surveys of stakeholders knowledge and attitudes related to water resources, pollution and Best Management Practices (BMPs) are analyzed and used to develop a model of BMP adoption likelihood based on socio-economic factors. The model is integrated into a Diagnostic Decision Support Sy...

Comparison of risk-based decision-support systems for brownfield site rehabilitation: DESYRE and SADA applied to a Romanian case study.

PubMed

Stezar, I C; Pizzol, L; Critto, A; Ozunu, A; Marcomini, A

2013-12-15

Brownfield rehabilitation is an essential step for sustainable land-use planning and management in the European Union. In brownfield regeneration processes, the legacy contamination plays a significant role, firstly because of the persistent contaminants in soil or groundwater which extends the existing hazards and risks well into the future; and secondly, problems from historical contamination are often more difficult to manage than contamination caused by new activities. Due to the complexity associated with the management of brownfield site rehabilitation, Decision Support Systems (DSSs) have been developed to support problem holders and stakeholders in the decision-making process encompassing all phases of the rehabilitation. This paper presents a comparative study between two DSSs, namely SADA (Spatial Analysis and Decision Assistance) and DESYRE (Decision Support System for the Requalification of Contaminated Sites), with the main objective of showing the benefits of using DSSs to introduce and process data and then to disseminate results to different stakeholders involved in the decision-making process. For this purpose, a former car manufacturing plant located in the Brasov area, Central Romania, contaminated chiefly by heavy metals and total petroleum hydrocarbons, has been selected as a case study to apply the two examined DSSs. Major results presented here concern the analysis of the functionalities of the two DSSs in order to identify similarities, differences and complementarities and, thus, to provide an indication of the most suitable integration options. Copyright © 2013 Elsevier Ltd. All rights reserved.

The conceptual foundation of environmental decision support.

PubMed

Reichert, Peter; Langhans, Simone D; Lienert, Judit; Schuwirth, Nele

2015-05-01

Environmental decision support intends to use the best available scientific knowledge to help decision makers find and evaluate management alternatives. The goal of this process is to achieve the best fulfillment of societal objectives. This requires a careful analysis of (i) how scientific knowledge can be represented and quantified, (ii) how societal preferences can be described and elicited, and (iii) how these concepts can best be used to support communication with authorities, politicians, and the public in environmental management. The goal of this paper is to discuss key requirements for a conceptual framework to address these issues and to suggest how these can best be met. We argue that a combination of probability theory and scenario planning with multi-attribute utility theory fulfills these requirements, and discuss adaptations and extensions of these theories to improve their application for supporting environmental decision making. With respect to (i) we suggest the use of intersubjective probabilities, if required extended to imprecise probabilities, to describe the current state of scientific knowledge. To address (ii), we emphasize the importance of value functions, in addition to utilities, to support decisions under risk. We discuss the need for testing "non-standard" value aggregation techniques, the usefulness of flexibility of value functions regarding attribute data availability, the elicitation of value functions for sub-objectives from experts, and the consideration of uncertainty in value and utility elicitation. With respect to (iii), we outline a well-structured procedure for transparent environmental decision support that is based on a clear separation of scientific prediction and societal valuation. We illustrate aspects of the suggested methodology by its application to river management in general and with a small, didactical case study on spatial river rehabilitation prioritization. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Decision support system development at the Upper Midwest Environmental Sciences Center

USGS Publications Warehouse

Fox, Timothy J.; Nelson, J. C.; Rohweder, Jason J.

2014-01-01

A Decision Support System (DSS) can be defined in many ways. The working definition used by the U.S. Geological Survey Upper Midwest Environmental Sciences Center (UMESC) is, “A spatially based computer application or data that assists a researcher or manager in making decisions.” This is quite a broad definition—and it needs to be, because the possibilities for types of DSSs are limited only by the user group and the developer’s imagination. There is no one DSS; the types of DSSs are as diverse as the problems they help solve. This diversity requires that DSSs be built in a variety of ways, using the most appropriate methods and tools for the individual application. The skills of potential DSS users vary widely as well, further necessitating multiple approaches to DSS development. Some small, highly trained user groups may want a powerful modeling tool with extensive functionality at the expense of ease of use. Other user groups less familiar with geographic information system (GIS) and spatial data may want an easy-to-use application for a nontechnical audience. UMESC has been developing DSSs for almost 20 years. Our DSS developers offer our partners a wide variety of technical skills and development options, ranging from the most simple Web page or small application to complex modeling application development.

GIS, remote sensing and spatial modeling for conservation of stone forest landscape in Lunan, China

NASA Astrophysics Data System (ADS)

Zhang, Chuanrong

The Lunan Stone Forest is the World's premier pinnacle karst landscape, with considerable scientific and cultural importance. Because of its inherent ecological fragility and ongoing human disruption, especially recently burgeoning tourism development, the landscape is stressed and is in danger of being destroyed. Conservation policies have been implemented by the local and national governments, but many problems remain in the national park. For example, there is no accurate detailed map and no computer system to help authorities manage the natural resources. By integrating GIS, remote sensing and spatial modeling this dissertation investigates the issue of landscape conservation and develops some methodologies to assist in management of the natural resources in the national park. Four elements are involved: (1) To help decision-makers and residents understand the scope of resource exploitation and develop appropriate protective strategies, the dissertation documents how the landscape has been changed by human activities over the past 3 decades; (2) To help authorities scientifically designate different levels of protection in the park and to let the public actively participate in conservation decision making, a web-based Spatial Decision Support System for the conservation of the landscape was developed; (3) To make data sharing and integration easy in the future, a GML-based interoperable database for the park was implemented; and (4) To acquire more information and provide the uncertainty information to landscape conservation decision-makers, spatial land use patterns were modeled and the distributional uncertainty of land cover categories was assessed using a triplex Markov chain (TMC) model approach.

Utility assessment of a map-based online geo-collaboration tool.

PubMed

Sidlar, Christopher L; Rinner, Claus

2009-05-01

Spatial group decision-making processes often include both informal and analytical components. Discussions among stakeholders or planning experts are an example of an informal component. When participants discuss spatial planning projects they typically express concerns and comments by pointing to places on a map. The Argumentation Map model provides a conceptual basis for collaborative tools that enable explicit linkages of arguments to the places to which they refer. These tools allow for the input of explicitly geo-referenced arguments as well as the visual access to arguments through a map interface. In this paper, we will review previous utility studies in geo-collaboration and evaluate a case study of a Web-based Argumentation Map application. The case study was conducted in the summer of 2005 when student participants discussed planning issues on the University of Toronto St. George campus. During a one-week unmoderated discussion phase, 11 participants wrote 60 comments on issues such as safety, facilities, parking, and building aesthetics. By measuring the participants' use of geographic references, we draw conclusions on how well the software tool supported the potential of the underlying concept. This research aims to contribute to a scientific approach to geo-collaboration in which the engineering of novel spatial decision support methods is complemented by a critical assessment of their utility in controlled, realistic experiments.

The Huaihe Basin Water Resource and Water Quality Management Platform Implemented with a Spatio-Temporal Data Model

NASA Astrophysics Data System (ADS)

Liu, Y.; Zhang, W.; Yan, C.

2012-07-01

Presently, planning and assessment in maintenance, renewal and decision-making for watershed hydrology, water resource management and water quality assessment are evolving toward complex, spatially explicit regional environmental assessments. These problems have to be addressed with object-oriented spatio-temporal data models that can restore, manage, query and visualize various historic and updated basic information concerning with watershed hydrology, water resource management and water quality as well as compute and evaluate the watershed environmental conditions so as to provide online forecasting to police-makers and relevant authorities for supporting decision-making. The extensive data requirements and the difficult task of building input parameter files, however, has long been an obstacle to use of such complex models timely and effectively by resource managers. Success depends on an integrated approach that brings together scientific, education and training advances made across many individual disciplines and modified to fit the needs of the individuals and groups who must write, implement, evaluate, and adjust their watershed management plans. The centre for Hydro-science Research, Nanjing University, in cooperation with the relevant watershed management authorities, has developed a WebGIS management platform to facilitate this complex process. Improve the management of watersheds over the Huaihe basin through the development, promotion and use of a web-based, user-friendly, geospatial watershed management data and decision support system (WMDDSS) involved many difficulties for the development of this complicated System. In terms of the spatial and temporal characteristics of historic and currently available information on meteorological, hydrological, geographical, environmental and other relevant disciplines, we designed an object-oriented spatiotemporal data model that combines spatial, attribute and temporal information to implement the management system. Using this system, we can update, query and analyze environmental information as well as manage historical data, and a visualization tool was provided to help the user interpret results so as to provide scientific support for decision-making. The utility of the system has been demonstrated its values by being used in watershed management and environmental assessments.

From Resource-Adaptive Navigation Assistance to Augmented Cognition

NASA Astrophysics Data System (ADS)

Zimmer, Hubert D.; Münzer, Stefan; Baus, Jörg

In an assistance scenario, a computer provides purposive information supporting a human user in an everyday situation. Wayfinding with navigation assistance is a prototypical assistance scenario. The present chapter analyzes the interplay of the resources of the assistance system and the resources of the user. The navigation assistance system provides geographic knowledge, positioning information, route planning, spatial overview information, and route commands at decision points. The user's resources encompass spatial knowledge, spatial abilities and visuo-spatial working memory, orientation strategies, and cultural habit. Flexible adaptations of the assistance system to available resources of the user are described, taking different wayfinding goals, situational constraints, and individual differences into account. Throughout the chapter, the idea is pursued that the available resources of the user should be kept active.

Decision support models for economically efficient integrated forest management

Treesearch

Hans R. Zuuring; Judy M. Troutwine; Greg J. Jones; Janet Sullivan

2005-01-01

Forest managers are challenged to fulfill conflicting social, biological, and commodity production objectives. To wisely use available, scarce resources for management activities, it is not enough to consider short term costs and effects of management (fuel reduction, planting, or other forest treatments). Long term tactical, spatial and temporal planning is needed to...

Issues of Spatial and Temporal Scale in Modeling the Effects of Field Operatiions on Soil Properties

USDA-ARS?s Scientific Manuscript database

Tillage is an important procedure for modifying the soil environment in order to enhance crop growth and conserve soil and water resources. Process-based models of crop production are widely used in decision support, but few explicitly simulate tillage. The Cropping Systems Model (CSM) was modified ...

A framework for simulating map error in ecosystem models

Treesearch

Sean P. Healey; Shawn P. Urbanski; Paul L. Patterson; Chris Garrard

2014-01-01

The temporal depth and spatial breadth of observations from platforms such as Landsat provide unique perspective on ecosystem dynamics, but the integration of these observations into formal decision support will rely upon improved uncertainty accounting. Monte Carlo (MC) simulations offer a practical, empirical method of accounting for potential map errors in broader...

Challenges to Applying a Metamodel for Groundwater Flow Beyond Underlying Numerical Model Boundaries

NASA Astrophysics Data System (ADS)

Reeves, H. W.; Fienen, M. N.; Feinstein, D.

2015-12-01

Metamodels of environmental behavior offer opportunities for decision support, adaptive management, and increased stakeholder engagement through participatory modeling and model exploration. Metamodels are derived from calibrated, computationally demanding, numerical models. They may potentially be applied to non-modeled areas to provide screening or preliminary analysis tools for areas that do not yet have the benefit of more comprehensive study. In this decision-support mode, they may be fulfilling a role often accomplished by application of analytical solutions. The major challenge to transferring a metamodel to a non-modeled area is how to quantify the spatial data in the new area of interest in such a way that it is consistent with the data used to derive the metamodel. Tests based on transferring a metamodel derived from a numerical groundwater-flow model of the Lake Michigan Basin to other glacial settings across the northern U.S. show that the spatial scale of the numerical model must be appropriately scaled to adequately represent different settings. Careful GIS analysis of the numerical model, metamodel, and new area of interest is required for successful transfer of results.

Developing AN Emergency Response Model for Offshore Oil Spill Disaster Management Using Spatial Decision Support System (sdss)

NASA Astrophysics Data System (ADS)

Balogun, Abdul-Lateef; Matori, Abdul-Nasir; Wong Toh Kiak, Kelvin

2018-04-01

Environmental resources face severe risks during offshore oil spill disasters and Geographic Information System (GIS) Environmental Sensitivity Index (ESI) maps are increasingly being used as response tools to minimize the huge impacts of these spills. However, ESI maps are generally unable to independently harmonize the diverse preferences of the multiple stakeholders' involved in the response process, causing rancour and delay in response time. This paper's Spatial Decision Support System (SDSS) utilizes the Analytic Hierarchy Process (AHP) model to perform tradeoffs in determining the most significant resources to be secured considering the limited resources and time available to perform the response operation. The AHP approach is used to aggregate the diverse preferences of the stakeholders and reach a consensus. These preferences, represented as priority weights, are incorporated in a GIS platform to generate Environmental sensitivity risk (ESR) maps. The ESR maps provide a common operational platform and consistent situational awareness for the multiple parties involved in the emergency response operation thereby minimizing discord among the response teams and saving the most valuable resources.

[A spatially explicit analysis of traffic accidents involving pedestrians and cyclists in Berlin].

PubMed

Lakes, Tobia

2017-12-01

In many German cities and counties, sustainable mobility concepts that strengthen pedestrian and cyclist traffic are promoted. From the perspectives of urban development, traffic planning and public healthcare, a spatially differentiated analysis of traffic accident data is decisive. 1) The identification of spatial and temporal patterns of the distribution of accidents involving cyclists and pedestrians, 2) the identification of hotspots and exploration of possible underlying causes and 3) the critical discussion of benefits and challenges of the results and the derivation of conclusions. Spatio-temporal distributions of data from accident statistics in Berlin involving pedestrians and cyclists from 2011 to 2015 were analysed with geographic information systems (GIS). While the total number of accidents remains relatively stable for pedestrian and cyclist accidents, the spatial distribution analysis shows, however, that there are significant spatial clusters (hotspots) of traffic accidents with a strong concentration in the inner city area. In a critical discussion, the benefits of geographic concepts are identified, such as spatially explicit health data (in this case traffic accident data), the importance of the integration of other data sources for the evaluation of the health impact of areas (traffic accident statistics of the police), and the possibilities and limitations of spatial-temporal data analysis (spatial point-density analyses) for the derivation of decision-supported recommendations and for the evaluation of policy measures of health prevention and of health-relevant urban development.

A functional difference in information processing between orbitofrontal cortex and ventral striatum during decision-making behaviour.

PubMed

Stott, Jeffrey J; Redish, A David

2014-11-05

Both orbitofrontal cortex (OFC) and ventral striatum (vStr) have been identified as key structures that represent information about value in decision-making tasks. However, the dynamics of how this information is processed are not yet understood. We recorded ensembles of cells from OFC and vStr in rats engaged in the spatial adjusting delay-discounting task, a decision-making task that involves a trade-off between delay to and magnitude of reward. Ventral striatal neural activity signalled information about reward before the rat's decision, whereas such reward-related signals were absent in OFC until after the animal had committed to its decision. These data support models in which vStr is directly involved in action selection, but OFC processes decision-related information afterwards that can be used to compare the predicted and actual consequences of behaviour. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Cost analysis of the development and implementation of a spatial decision support system for malaria elimination in Solomon Islands.

PubMed

Marston, Luke; Kelly, Gerard C; Hale, Erick; Clements, Archie C A; Hodge, Andrew; Jimenez-Soto, Eliana

2014-08-18

The goal of malaria elimination faces numerous challenges. New tools are required to support the scale up of interventions and improve national malaria programme capacity to conduct detailed surveillance. This study investigates the cost factors influencing the development and implementation of a spatial decision support system (SDSS) for malaria elimination in the two elimination provinces of Isabel and Temotu, Solomon Islands. Financial and economic costs to develop and implement a SDSS were estimated using the Solomon Islands programme's financial records. Using an ingredients approach, verified by stakeholders and operational reports, total costs for each province were quantified. A budget impact sensitivity analysis was conducted to investigate the influence of variations in standard budgetary components on the costs and to identify potential cost savings. A total investment of US$ 96,046 (2012 constant dollars) was required to develop and implement the SDSS in two provinces (Temotu Province US$ 49,806 and Isabel Province US$ 46,240). The single largest expense category was for computerized equipment totalling approximately US$ 30,085. Geographical reconnaissance was the most expensive phase of development and implementation, accounting for approximately 62% of total costs. Sensitivity analysis identified different cost factors between the provinces. Reduced equipment costs would deliver a budget saving of approximately 10% in Isabel Province. Combined travel costs represented the greatest influence on the total budget in the more remote Temotu Province. This study provides the first cost analysis of an operational surveillance tool used specifically for malaria elimination in the South-West Pacific. It is demonstrated that the costs of such a decision support system are driven by specialized equipment and travel expenses. Such factors should be closely scrutinized in future programme budgets to ensure maximum efficiencies are gained and available resources are allocated effectively.

A Regional Monitoring and Visualization System for Decision Support and Disaster Management Applications for the Mesoamerican Biological Corridor and Beyond

NASA Technical Reports Server (NTRS)

Irwin, Daniel

2002-01-01

The Mesoamerican Biological Corridor (MBC)-a network of managed and protected areas extending from Mexico to Columbia-is a crucial initiative for the Mesoamerican region, with a central development concept of integrating conservation and sustainable use of biodiversity within the framework of sustainable economic development. The MBC is of particular importance to the Central American Commission for Environment and Development (CCAD), which is comprised of the environmental ministers from the seven Central American countries. Responsible for determining priority areas for action in the corridor, CCAD decision makers require current and accurate information, and access to the dynamic knowledge of the changes in the MBC such as deforestation hotspots, fires, and the effects of natural disasters. Currently this information is not integrated and in disparate locations throughout the region and the world. Leveraging NASA technology, satellite data, and capability, we propose to team with the World Bank and the CCAD to develop a regional monitoring and visualization system-with central nodes at the NASA/Marshall Space Flight Center and at CCAD headquarters. This system will assimilate NASA spatial datasets (e.g. MODIS, Landsat, etc.), spatial data from other sources (commercial and public-domain), and ancillary data developed in each of the seven Central American countries (soils, transportation networks, biodiversity indicator maps, etc.). The system will function as a "virtual dashboard" for monitoring the MBC and provide the critical decision support tools for CCAD decision makers. The CCAD central node will also serve as a high-tech showcase for the corridor among the international community, other decision-makers, the media, and students.

E-DECIDER Decision Support Gateway For Earthquake Disaster Response

NASA Astrophysics Data System (ADS)

Glasscoe, M. T.; Stough, T. M.; Parker, J. W.; Burl, M. C.; Donnellan, A.; Blom, R. G.; Pierce, M. E.; Wang, J.; Ma, Y.; Rundle, J. B.; Yoder, M. R.

2013-12-01

Earthquake Data Enhanced Cyber-Infrastructure for Disaster Evaluation and Response (E-DECIDER) is a NASA-funded project developing capabilities for decision-making utilizing remote sensing data and modeling software in order to provide decision support for earthquake disaster management and response. E-DECIDER incorporates earthquake forecasting methodology and geophysical modeling tools developed through NASA's QuakeSim project in order to produce standards-compliant map data products to aid in decision-making following an earthquake. Remote sensing and geodetic data, in conjunction with modeling and forecasting tools, help provide both long-term planning information for disaster management decision makers as well as short-term information following earthquake events (i.e. identifying areas where the greatest deformation and damage has occurred and emergency services may need to be focused). E-DECIDER utilizes a service-based GIS model for its cyber-infrastructure in order to produce standards-compliant products for different user types with multiple service protocols (such as KML, WMS, WFS, and WCS). The goal is to make complex GIS processing and domain-specific analysis tools more accessible to general users through software services as well as provide system sustainability through infrastructure services. The system comprises several components, which include: a GeoServer for thematic mapping and data distribution, a geospatial database for storage and spatial analysis, web service APIs, including simple-to-use REST APIs for complex GIS functionalities, and geoprocessing tools including python scripts to produce standards-compliant data products. These are then served to the E-DECIDER decision support gateway (http://e-decider.org), the E-DECIDER mobile interface, and to the Department of Homeland Security decision support middleware UICDS (Unified Incident Command and Decision Support). The E-DECIDER decision support gateway features a web interface that delivers map data products including deformation modeling results (slope change and strain magnitude) and aftershock forecasts, with remote sensing change detection results under development. These products are event triggered (from the USGS earthquake feed) and will be posted to event feeds on the E-DECIDER webpage and accessible via the mobile interface and UICDS. E-DECIDER also features a KML service that provides infrastructure information from the FEMA HAZUS database through UICDS and the mobile interface. The back-end GIS service architecture and front-end gateway components form a decision support system that is designed for ease-of-use and extensibility for end-users.

Artificial intelligence based decision support for trumpeter swan management

USGS Publications Warehouse

Sojda, Richard S.

2002-01-01

The number of trumpeter swans (Cygnus buccinator) breeding in the Tri-State area where Montana, Idaho, and Wyoming come together has declined to just a few hundred pairs. However, these birds are part of the Rocky Mountain Population which additionally has over 3,500 birds breeding in Alberta, British Columbia, Northwest Territories, and Yukon Territory. To a large degree, these birds seem to have abandoned traditional migratory pathways in the flyway. Waterfowl managers have been interested in decision support tools that would help them explore simulated management scenarios in their quest towards reaching population recovery and the reestablishment of traditional migratory pathways. I have developed a decision support system to assist biologists with such management, especially related to wetland ecology. Decision support systems use a combination of models, analytical techniques, and information retrieval to help develop and evaluate appropriate alternatives. Swan management is a domain that is ecologically complex, and this complexity is compounded by spatial and temporal issues. As such, swan management is an inherently distributed problem. Therefore, the ecological context for modeling swan movements in response to management actions was built as a multiagent system of interacting intelligent agents that implements a queuing model representing swan migration. These agents accessed ecological knowledge about swans, their habitats, and flyway management principles from three independent expert systems. The agents were autonomous, had some sensory capability, and could respond to changing conditions. A key problem when developing ecological decision support systems is empirically determining that the recommendations provided are valid. Because Rocky Mountain trumpeter swans have been surveyed for a long period of time, I was able to compare simulated distributions provided by the system with actual field observations across 20 areas for the period 1988-2000. Applying the Matched Pairs Multivariate Permutation Test as a statistical tool was a new approach for comparing flyway distributions of waterfowl over time that seemed to work well. Based on this approach, the empirical evidence that I gathered led me to conclude that the base queuing model does accurately simulate swan distributions in the flyway. The system was insensitive to almost all model parameters tested. That remains perplexing, but might result from the base queuing model, itself, being particularly effective at representing the actual ecological diversity in the world of Rocky Mountain trumpeter swans, both spatial and temporally.

Facing uncertainty in ecosystem services-based resource management.

PubMed

Grêt-Regamey, Adrienne; Brunner, Sibyl H; Altwegg, Jürg; Bebi, Peter

2013-09-01

The concept of ecosystem services is increasingly used as a support for natural resource management decisions. While the science for assessing ecosystem services is improving, appropriate methods to address uncertainties in a quantitative manner are missing. Ignoring parameter uncertainties, modeling uncertainties and uncertainties related to human-environment interactions can modify decisions and lead to overlooking important management possibilities. In this contribution, we present a new approach for mapping the uncertainties in the assessment of multiple ecosystem services. The spatially explicit risk approach links Bayesian networks to a Geographic Information System for forecasting the value of a bundle of ecosystem services and quantifies the uncertainties related to the outcomes in a spatially explicit manner. We demonstrate that mapping uncertainties in ecosystem services assessments provides key information for decision-makers seeking critical areas in the delivery of ecosystem services in a case study in the Swiss Alps. The results suggest that not only the total value of the bundle of ecosystem services is highly dependent on uncertainties, but the spatial pattern of the ecosystem services values changes substantially when considering uncertainties. This is particularly important for the long-term management of mountain forest ecosystems, which have long rotation stands and are highly sensitive to pressing climate and socio-economic changes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Urban Rain Gauge Siting Selection Based on Gis-Multicriteria Analysis

NASA Astrophysics Data System (ADS)

Fu, Yanli; Jing, Changfeng; Du, Mingyi

2016-06-01

With the increasingly rapid growth of urbanization and climate change, urban rainfall monitoring as well as urban waterlogging has widely been paid attention. In the light of conventional siting selection methods do not take into consideration of geographic surroundings and spatial-temporal scale for the urban rain gauge site selection, this paper primarily aims at finding the appropriate siting selection rules and methods for rain gauge in urban area. Additionally, for optimization gauge location, a spatial decision support system (DSS) aided by geographical information system (GIS) has been developed. In terms of a series of criteria, the rain gauge optimal site-search problem can be addressed by a multicriteria decision analysis (MCDA). A series of spatial analytical techniques are required for MCDA to identify the prospective sites. With the platform of GIS, using spatial kernel density analysis can reflect the population density; GIS buffer analysis is used to optimize the location with the rain gauge signal transmission character. Experiment results show that the rules and the proposed method are proper for the rain gauge site selection in urban areas, which is significant for the siting selection of urban hydrological facilities and infrastructure, such as water gauge.

Marine spatial planning in practice

NASA Astrophysics Data System (ADS)

Collie, Jeremy S.; (Vic) Adamowicz, W. L.; Beck, Michael W.; Craig, Bethany; Essington, Timothy E.; Fluharty, David; Rice, Jake; Sanchirico, James N.

2013-01-01

Multiple competing uses of continental-shelf environments have led to a proliferation of marine spatial planning initiatives, together with expert guidance on marine spatial planning. This study provides an empirical review of marine spatial plans, their attributes, and the extent to which the expert guidance is actually being followed. We performed a structured review of 16 existing marine spatial plans and created an idealized marine spatial plan from the steps included in recent expert papers. A cluster analysis of the yes/no answers to 28 questions was used to ordinate the 16 marine spatial plans and to compare them with the idealized plan. All the plans that have been implemented have a high-level government mandate and the authority to implement spatial planning vested in existing institutions. Almost all the plans used data with clear criteria for data inclusion. Stakeholders were included in almost all the plans; they did not participate in all stages of the planning process but their roles were generally clearly defined. Decision-support tools were applied inconsistently across plans and were seldom used dynamically over time. Most spatial planning processes did not select specific outcomes, such as preferred use scenarios. Success is defined inconsistently across plans; in half the cases there are no metrics of success with reference benchmarks. Although monitoring is included in the majority of plans, only in some cases do monitoring results feed back into management decisions. The process of marine spatial planning had advanced in that some of the more recent plans were developed more quickly and contain more desirable attributes than earlier plans. Even so, existing marine spatial plans are heterogeneous—there are essential ingredients, but no single recipe for success.

Saccadic eye movements as an index of perceptual decision-making.

PubMed

McSorley, Eugene; McCloy, Rachel

2009-10-01

One of the most common decisions we make is the one about where to move our eyes next. Here we examine the impact that processing the evidence supporting competing options has on saccade programming. Participants were asked to saccade to one of two possible visual targets indicated by a cloud of moving dots. We varied the evidence which supported saccade target choice by manipulating the proportion of dots moving towards one target or the other. The task was found to become easier as the evidence supporting target choice increased. This was reflected in an increase in percent correct and a decrease in saccade latency. The trajectory and landing position of saccades were found to deviate away from the non-selected target reflecting the choice of the target and the inhibition of the non-target. The extent of the deviation was found to increase with amount of sensory evidence supporting target choice. This shows that decision-making processes involved in saccade target choice have an impact on the spatial control of a saccade. This would seem to extend the notion of the processes involved in the control of saccade metrics beyond a competition between visual stimuli to one also reflecting a competition between options.

A spatially explicit decision support model for restoration of forest bird habitat

USGS Publications Warehouse

Twedt, D.J.; Uihlein, W.B.; Elliott, A.B.

2006-01-01

The historical area of bottomland hardwood forest in the Mississippi Alluvial Valley has been reduced by >75%. Agricultural production was the primary motivator for deforestation; hence, clearing deliberately targeted higher and drier sites. Remaining forests are highly fragmented and hydrologically altered, with larger forest fragments subject to greater inundation, which has negatively affected many forest bird populations. We developed a spatially explicit decision support model, based on a Partners in Flight plan for forest bird conservation, that prioritizes forest restoration to reduce forest fragmentation and increase the area of forest core (interior forest >1 km from 'hostile' edge). Our primary objective was to increase the number of forest patches that harbor >2000 ha of forest core, but we also sought to increase the number and area of forest cores >5000 ha. Concurrently, we targeted restoration within local (320 km2) landscapes to achieve >60% forest cover. Finally, we emphasized restoration of higher-elevation bottomland hardwood forests in areas where restoration would not increase forest fragmentation. Reforestation of 10% of restorable land in the Mississippi Alluvial Valley (approximately 880,000 ha) targeted at priorities established by this decision support model resulted in approximately 824,000 ha of new forest core. This is more than 32 times the amount of core forest added through reforestation of randomly located fields (approximately 25,000 ha). The total area of forest core (1.6 million ha) that resulted from targeted restoration exceeded habitat objectives identified in the Partners in Flight Bird Conservation Plan and approached the area of forest core present in the 1950s.

Spatial decision supporting for winter wheat irrigation and fertilizer optimizing in North China Plain

NASA Astrophysics Data System (ADS)

Yang, Xiaodong; Yang, Hao; Dong, Yansheng; Yu, Haiyang

2014-11-01

Production management of winter wheat is more complicated than other crops since its growth period is covered all four seasons and growth environment is very complex with frozen injury, drought, insect or disease injury and others. In traditional irrigation and fertilizer management, agricultural technicians or farmers mainly make decision based on phenology, planting experience to carry out artificial fertilizer and irrigation management. For example, wheat needs more nitrogen fertilizer in jointing and booting stage by experience, then when the wheat grow to the two growth periods, the farmer will fertilize to the wheat whether it needs or not. We developed a spatial decision support system for optimizing irrigation and fertilizer measures based on WebGIS, which monitoring winter wheat growth and soil moisture content by combining a crop model, remote sensing data and wireless sensors data, then reasoning professional management schedule from expert knowledge warehouse. This system is developed by ArcIMS, IDL in server-side and JQuery, Google Maps API, ASP.NET in client-side. All computing tasks are run on server-side, such as computing 11 normal vegetable indexes (NDVI/ NDWI/ NDWI2/ NRI/ NSI/ WI/ G_SWIR/ G_SWIR2/ SPSI/ TVDI/ VSWI) and custom VI of remote sensing image by IDL; while real-time building map configuration file and generating thematic map by ArcIMS.

Site selection for drinking-water pumping boreholes using a fuzzy spatial decision support system in the Korinthia prefecture, SE Greece

NASA Astrophysics Data System (ADS)

Antonakos, Andreas K.; Voudouris, Konstantinos S.; Lambrakis, Nikolaos I.

2014-12-01

The implementation of a geographic information system (GIS)/fuzzy spatial decision support system in the selection of sites for drinking-water pumping boreholes is described. Groundwater is the main source of domestic supply and irrigation in Korinthia prefecture, south-eastern Greece. Water demand has increased considerably over the last 30 years and is mainly met by groundwater abstracted via numerous wells and boreholes. The definition of the most "suitable" site for the drilling of new boreholes is a major issue in this area. A method of allocating suitable locations has been developed based on multicriteria analysis and fuzzy logic. Twelve parameters were finally involved in the model, prearranged into three categories: borehole yield, groundwater quality, and economic and technical constraints. GIS was used to create a classification map of the research area, based on the suitability of each point for the placement of new borehole fields. The coastal part of the study area is completely unsuitable, whereas high values of suitability are recorded in the south-western part. The study demonstrated that the method of multicriteria analysis in combination with fuzzy logic is a useful tool for selecting the best sites for new borehole drilling on a regional scale. The results could be used by local authorities and decision-makers for integrated groundwater resources management.

Decision support for integrated landscape evaluation and restoration planning.

Treesearch

Keith M. Reynolds; Paul F. Hessburg

2005-01-01

The historical patterns of Inland Northwest United States forests have been dramatically altered by a little more than two centuries of human settlement and land use. Spatial patterns of forest structural conditions, tree species composition, snags and down wood, and temporal variation in these patterns, have been altered to such an extent that the natural ebb and flow...

Computer-based tools for decision support in agroforestry: Current state and future needs

Treesearch

E.A. Ellis; G. Bentrup; Michelle M. Schoeneberger

2004-01-01

Successful design of agroforestry practices hinges on the ability to pull together very diverse and sometimes large sets of information (i.e., biophysical, economic and social factors), and then implementing the synthesis of this information across several spatial scales from site to landscape. Agroforestry, by its very nature, creates complex systems with impacts...

Modeling fire and other disturbance processes using LANDIS

Treesearch

Stephen R. Shifley; Jian Yang; Hong He

2009-01-01

LANDIS is a landscape decision support tool that models spatial relationships to help managers and planners examine the large-scale, long-term, cumulative effects of succession, harvesting, wildfire, prescribed fire, insects, and disease. It can operate on forest landscapes from a few thousand to a few million acres in extent. Fire modeling capabilities in LANDIS are...

Composition, biomass and structure of mangroves within the Zambezi River Delta

Treesearch

Carl C. Trettin; Christina E. Stringer; Stan Zarnoch

2015-01-01

We used a stratified random sampling design to inventory the mangrove vegetation within the Zambezi River Delta, Mozambique, to provide a basis for estimating biomass pools. We used canopy height, derived from remote sensing data, to stratify the inventory area, and then applied a spatial decision support system to objectively allocate sample plots among five...

Decision support for evaluating landscape departure and prioritizing forest management activities in a changing environment

Treesearch

S. Gärtner; K.M. Reynolds; P.F. Hessburg; S.S. Hummel; M. Twery

2008-01-01

We evaluated changes (hereafter, departures) in spatial patterns of various patch types of forested landscapes in two subwatersheds ("east" and "west") in eastern Washington, USA, from the patterns of two sets of reference conditions; one representing the broad variability of pre-management era (~1900) conditions, and another representing the broad...

The STRATEGY project: decision tools to aid sustainable restoration and long-term management of contaminated agricultural ecosystems.

PubMed

Howard, B J; Beresford, N A; Nisbet, A; Cox, G; Oughton, D H; Hunt, J; Alvarez, B; Andersson, K G; Liland, A; Voigt, G

2005-01-01

The STRATEGY project (Sustainable Restoration and Long-Term Management of Contaminated Rural, Urban and Industrial Ecosystems) aimed to provide a holistic decision framework for the selection of optimal restoration strategies for the long-term sustainable management of contaminated areas in Western Europe. A critical evaluation was carried out of countermeasures and waste disposal options, from which compendia of state-of-the-art restoration methods were compiled. A decision support system capable of optimising spatially varying restoration strategies, that considered the level of averted dose, costs (including those of waste disposal) and environmental side effects was developed. Appropriate methods of estimating indirect costs associated with side effects and of communicating with stakeholders were identified. The importance of stakeholder consultation at a local level and of ensuring that any response is site and scenario specific were emphasised. A value matrix approach was suggested as a method of addressing social and ethical issues within the decision-making process, and was designed to be compatible with both the countermeasure compendia and the decision support system. The applicability and usefulness of STRATEGY outputs for food production systems in the medium to long term is assessed.

Fuzzification of continuous-value spatial evidence for mineral prospectivity mapping

NASA Astrophysics Data System (ADS)

Yousefi, Mahyar; Carranza, Emmanuel John M.

2015-01-01

Complexities of geological processes portrayed as certain feature in a map (e.g., faults) are natural sources of uncertainties in decision-making for exploration of mineral deposits. Besides natural sources of uncertainties, knowledge-driven (e.g., fuzzy logic) mineral prospectivity mapping (MPM) is also plagued and incurs further uncertainty in subjective judgment of analyst when there is no reliable proven value of evidential scores corresponding to relative importance of geological features that can directly be measured. In this regard, analysts apply expert opinion to assess relative importance of spatial evidences as meaningful decision support. This paper aims for fuzzification of continuous spatial data used as proxy evidence to facilitate and to support fuzzy MPM to generate exploration target areas for further examination of undiscovered deposits. In addition, this paper proposes to adapt the concept of expected value to further improve fuzzy logic MPM because the analysis of uncertain variables can be presented in terms of their expected value. The proposed modified expected value approach to MPM is not only a multi-criteria approach but it also treats uncertainty of geological processes a depicted by maps or spatial data in term of biased weighting more realistically in comparison with classified evidential maps because fuzzy membership scores are defined continuously whereby, for example, there is no need to categorize distances from evidential features to proximity classes using arbitrary intervals. The proposed continuous weighting approach and then integrating the weighted evidence layers by using modified expected value function, described in this paper can be used efficiently in either greenfields or brownfields.

Implementation of AN Agricultural Environmental Information System (aeis) for the Sanjiang Plain, Ne-China

NASA Astrophysics Data System (ADS)

Zhao, Q.; Brocks, S.; Lenz-Wiedemann, V.; Miao, Y.; Jiang, R.; Chen, X.; Zhang, F.; Bareth, G.

2012-07-01

The Sino-German Project between the China Agricultural University and the University of Cologne, Germany, focuses on regional agro-ecosystem modelling. One major focus of the cooperation activity is the establishment of joint rice field experiment research in Jiansanjiang, located in the Sanjiang Plain (Heilongjiang Province, north-eastern part of China), to investigate the different agricultural practices and their impact on yield and environment. An additional task is to set-up an Agricultural Environmental Information System (AEIS) for the Sanjiang Plain (SJP), which covers more than 100 000 km2. Research groups from Geography (e.g. GIS & Remote Sensing) and Plant Nutrition (e.g. Precision Agriculture) are involved in the project. The major aim of the AEIS for the SJP is to provide information about (i) agriculture in the region, (ii) the impact of agricultural practices on the environment, and (iii) simulation scenarios for sustainable strategies. Consequently, the AEIS for the SJP provides information for decision support and therefore could be regarded as a Spatial Decision Support System (SDSS), too. The investigation of agricultural and environmental issues has a spatial context, which requires the management, handling, and analysis of spatial data. The use of GIS enables the capture, storage, analysis and presentation of spatial data. Therefore, GIS is the major tool for the set-up of the AEIS for the SJP. This contribution presents the results of linking agricultural statistics with GIS to provide information about agriculture in the SJP and discusses the benefits of this method as well as the integration of methods to produce new data.

The Role of Low-Spatial Frequencies in Lexical Decision and Masked Priming

ERIC Educational Resources Information Center

Boden, C.; Giaschi, D.

2009-01-01

Spatial frequency filtering was used to test the hypotheses that low-spatial frequency information in printed text can: (1) lead to a rapid lexical decision or (2) facilitate word recognition. Adult proficient readers made lexical decisions in unprimed and masked repetition priming experiments with unfiltered, low-pass, high-pass and notch…

Toward a multi-objective decision support framework to support regulations of unconventional oil and gas development

NASA Astrophysics Data System (ADS)

Alongi, M.; Howard, C.; Kasprzyk, J. R.; Ryan, J. N.

2015-12-01

Unconventional oil and gas development (UOGD) using hydraulic fracturing and horizontal drilling has recently fostered an unprecedented acceleration in energy development. Regulations seek to protect environmental quality of areas surrounding UOGD, while maintaining economic benefits. One such regulation is a setback distance, which dictates the minimum proximity between an oil and gas well and an object such as a residential or commercial building, property line, or water source. In general, most setback regulations have been strongly politically motivated without a clear scientific basis for understanding the relationship between the setback distance and various performance outcomes. This presentation discusses a new decision support framework for setback regulations, as part of a large NSF-funded sustainability research network (SRN) on UOGD. The goal of the decision support framework is to integrate a wide array of scientific information from the SRN into a coherent framework that can help inform policy regarding UOGD. The decision support framework employs multiobjective evolutionary algorithm (MOEA) optimization coupled with simulation models of air quality and other performance-based outcomes on UOGD. The result of the MOEA optimization runs are quantitative tradeoff curves among different objectives. For example, one such curve could demonstrate air pollution concentrations versus estimates of energy development profits, for different levels of setback distance. Our results will also inform policy-relevant discussions surrounding UOGD such as comparing single- and multi-well pads, as well as regulations on the density of well development over a spatial area.

Geospatial decision support systems for societal decision making

USGS Publications Warehouse

Bernknopf, R.L.

2005-01-01

While science provides reliable information to describe and understand the earth and its natural processes, it can contribute more. There are many important societal issues in which scientific information can play a critical role. Science can add greatly to policy and management decisions to minimize loss of life and property from natural and man-made disasters, to manage water, biological, energy, and mineral resources, and in general, to enhance and protect our quality of life. However, the link between science and decision-making is often complicated and imperfect. Technical language and methods surround scientific research and the dissemination of its results. Scientific investigations often are conducted under different conditions, with different spatial boundaries, and in different timeframes than those needed to support specific policy and societal decisions. Uncertainty is not uniformly reported in scientific investigations. If society does not know that data exist, what the data mean, where to use the data, or how to include uncertainty when a decision has to be made, then science gets left out -or misused- in a decision making process. This paper is about using Geospatial Decision Support Systems (GDSS) for quantitative policy analysis. Integrated natural -social science methods and tools in a Geographic Information System that respond to decision-making needs can be used to close the gap between science and society. The GDSS has been developed so that nonscientists can pose "what if" scenarios to evaluate hypothetical outcomes of policy and management choices. In this approach decision makers can evaluate the financial and geographic distribution of potential policy options and their societal implications. Actions, based on scientific information, can be taken to mitigate hazards, protect our air and water quality, preserve the planet's biodiversity, promote balanced land use planning, and judiciously exploit natural resources. Applications using the GDSS have demonstrated the benefits of utilizing science for policy decisions. Investment in science reduces decision-making uncertainty and reducing that uncertainty has economic value.

An optimized solution of multi-criteria evaluation analysis of landslide susceptibility using fuzzy sets and Kalman filter

NASA Astrophysics Data System (ADS)

Gorsevski, Pece V.; Jankowski, Piotr

2010-08-01

The Kalman recursive algorithm has been very widely used for integrating navigation sensor data to achieve optimal system performances. This paper explores the use of the Kalman filter to extend the aggregation of spatial multi-criteria evaluation (MCE) and to find optimal solutions with respect to a decision strategy space where a possible decision rule falls. The approach was tested in a case study in the Clearwater National Forest in central Idaho, using existing landslide datasets from roaded and roadless areas and terrain attributes. In this approach, fuzzy membership functions were used to standardize terrain attributes and develop criteria, while the aggregation of the criteria was achieved by the use of a Kalman filter. The approach presented here offers advantages over the classical MCE theory because the final solution includes both the aggregated solution and the areas of uncertainty expressed in terms of standard deviation. A comparison of this methodology with similar approaches suggested that this approach is promising for predicting landslide susceptibility and further application as a spatial decision support system.

Integrating Water Quality and River Rehabilitation Management - A Decision-Analytical Perspective

NASA Astrophysics Data System (ADS)

Reichert, P.; Langhans, S.; Lienert, J.; Schuwirth, N.

2009-04-01

Integrative river management involves difficult decisions about alternative measures to improve their ecological state. For this reason, it seems useful to apply knowledge from the decision sciences to support river management. We discuss how decision-analytical elements can be employed for designing an integrated river management procedure. An important aspect of this procedure is to clearly separate scientific predictions of the consequences of alternatives from objectives to be achieved by river management. The key elements of the suggested procedure are (i) the quantitative elicitation of the objectives from different stakeholder groups, (ii) the compilation of the current scientific knowledge about the consequences of the effects resulting from suggested measures in the form of a probabilistic mathematical model, and (iii) the use of these predictions and valuations to prioritize alternatives, to uncover conflicting objectives, to support the design of better alternatives, and to improve the transparency of communication about the chosen management strategy. The development of this procedure led to insights regarding necessary steps to be taken for rational decision-making in river management, to guidelines about the use of decision-analytical techniques for performing these steps, but also to new insights about the application of decision-analytical techniques in general. In particular, the consideration of the spatial distribution of the effects of measures and the potential added value of connected rehabilitated river reaches leads to favoring measures that have a positive effect beyond a single river reach. As these effects only propagate within the river network, this results in a river basin oriented management concept as a consequence of a rational decision support procedure, rather than as an a priori management paradigm. There are also limitations to the support that can be expected from the decision-analytical perspective. It will not provide the societal values that are driving prioritization in river management, it will only support their elicitation and rational use. This is particularly important for the assessment of micro-pollutants because of severe limitations in scientific knowledge of their effects on river ecosystems. This makes the influence of pollution by micro-pollutants on prioritization of measures strongly dependent on the weight of the precautionary principle relative to other societal objectives of river management.

Engineering-Geological Data Model - The First Step to Build National Polish Standard for Multilevel Information Management

NASA Astrophysics Data System (ADS)

Ryżyński, Grzegorz; Nałęcz, Tomasz

2016-10-01

The efficient geological data management in Poland is necessary to support multilevel decision processes for government and local authorities in case of spatial planning, mineral resources and groundwater supply and the rational use of subsurface. Vast amount of geological information gathered in the digital archives and databases of Polish Geological Survey (PGS) is a basic resource for multi-scale national subsurface management. Data integration is the key factor to allow development of GIS and web tools for decision makers, however the main barrier for efficient geological information management is the heterogeneity of data in the resources of the Polish Geological Survey. Engineering-geological database is the first PGS thematic domain applied in the whole data integration plan. The solutions developed within this area will facilitate creation of procedures and standards for multilevel data management in PGS. Twenty years of experience in delivering digital engineering-geological mapping in 1:10 000 scale and archival geotechnical reports acquisition and digitisation allowed gathering of more than 300 thousands engineering-geological boreholes database as well as set of 10 thematic spatial layers (including foundation conditions map, depth to the first groundwater level, bedrock level, geohazards). Historically, the desktop approach was the source form of the geological-engineering data storage, resulting in multiple non-correlated interbase datasets. The need for creation of domain data model emerged and an object-oriented modelling (UML) scheme has been developed. The aim of the aforementioned development was to merge all datasets in one centralised Oracle server and prepare the unified spatial data structure for efficient web presentation and applications development. The presented approach will be the milestone toward creation of the Polish national standard for engineering-geological information management. The paper presents the approach and methodology of data unification, thematic vocabularies harmonisation, assumptions and results of data modelling as well as process of the integration of domain model with enterprise architecture implemented in PGS. Currently, there is no geological data standard in Poland. Lack of guidelines for borehole and spatial data management results in an increasing data dispersion as well as in growing barrier for multilevel data management and implementation of efficient decision support tools. Building the national geological data standard makes geotechnical information accessible to multiple institutions, universities, administration and research organisations and gather their data in the same, unified digital form according to the presented data model. Such approach is compliant with current digital trends and the idea of Spatial Data Infrastructure. Efficient geological data management is essential to support the sustainable development and the economic growth, as they allow implementation of geological information to assist the idea of Smart Cites, deliver information for Building Information Management (BIM) and support modern spatial planning. The engineering-geological domain data model presented in the paper is a scalable solution. Future implementation of developed procedures on other domains of PGS geological data is possible.

Developing an Ecosystem Services Online Decision Support Tool to Assess the Impacts of Climate Change and Urban Growth in the Santa Cruz Watershed: Where We Live, Work, and Play

USGS Publications Warehouse

Norman, Laura; Tallent-Halsell, Nita; Labiosa, William; Weber, Matt; McCoy, Amy; Hirschboeck, Katie; Callegary, James; van Riper, Charles; Gray, Floyd

2010-01-01

Using respective strengths of the biological, physical, and social sciences, we are developing an online decision support tool, the Santa Cruz Watershed Ecosystem Portfolio Model (SCWEPM), to help promote the use of information relevant to water allocation and land management in a binational watershed along the U.S.-Mexico border. The SCWEPM will include an ES valuation system within a suite of linked regional driver-response models and will use a multicriteria scenario-evaluation framework that builds on GIS analysis and spatially-explicit models that characterize important ecological, economic, and societal endpoints and consequences that are sensitive to climate patterns, regional water budgets, and regional LULC change in the SCW.

GIS-based integrated assessment and decision support system for land use planning in consideration of carbon sequestration benefits

NASA Astrophysics Data System (ADS)

Wang, Jun; Chen, J. M.; Li, Manchun; Ju, Weimin

2007-06-01

As the major eligible land use activities in the Clean Development Mechanism (CDM), afforestation and reforestation offer opportunities and potential economic benefits for developing countries to participate in carbon-trade in the potential international carbon (C) sink markets. However, the design and selection of appropriate afforestation and reforestation locations in CDM are complex processes which need integrated assessment (IA) of C sequestration (CS) potential, environmental effects, and socio-economic impacts. This paper promotes the consideration of CS benefits in local land use planning and presents a GIS-based integrated assessment and spatial decision support system (IA-SDSS) to support decision-making on 'where' and 'how' to afforest. It integrates an Integrated Terrestrial Ecosystem Carbon Model (InTEC) and a GIS platform for modeling regional long-term CS potential and assessment of geo-referenced land use criteria including CS consequence, and produces ranking of plantation schemes with different tree species using the Analytic hierarchy process (AHP) method. Three land use scenarios are investigated: (i) traditional land use planning criteria without C benefits, (ii) land use for CS with low C price, and (iii) land use for CS with high price. Different scenarios and consequences will influence the weights of tree-species selection in the AHP decision process.

A Rapidly Prototyped Vegetation Dryness Index Evaluated for Wildfire Risk Assessment at Stennis Space Center

NASA Technical Reports Server (NTRS)

Ross, Kenton; Graham, William; Prados, Don; Spruce, Joseph

2007-01-01

MVDI, which effectively involves the differencing of NDMI and NDVI, appears to display increased noise that is consistent with a differencing technique. This effect masks finer variations in vegetation moisture, preventing MVDI from fulfilling the requirement of giving decision makers insight into spatial variation of fire risk. MVDI shows dependencies on land cover and phenology which also argue against its use as a fire risk proxy in an area of diverse and fragmented land covers. The conclusion of the rapid prototyping effort is that MVDI should not be implemented for SSC decision support.

Application GIS on university planning: building a spatial database aided spatial decision

NASA Astrophysics Data System (ADS)

Miao, Lei; Wu, Xiaofang; Wang, Kun; Nong, Yu

2007-06-01

With the development of university and its size enlarging, kinds of resource need to effective management urgently. Spacial database is the right tool to assist administrator's spatial decision. And it's ready for digital campus with integrating existing OMS. It's researched about the campus planning in detail firstly. Following instanced by south china agriculture university it is practiced that how to build the geographic database of the campus building and house for university administrator's spatial decision.

Integrated planning and spatial evaluation of megasite remediation and reuse options

NASA Astrophysics Data System (ADS)

Schädler, Sebastian; Morio, Maximilian; Bartke, Stephan; Finkel, Michael

2012-01-01

Redevelopment of large contaminated brownfields (megasites) is often hampered by a lack of communication and harmonization among diverse stakeholders with potentially conflicting interests. Decision support is required to provide integrative yet transparent evaluation of often complex spatial information to stakeholders with different areas of expertise. It is considered crucial for successful redevelopment to identify a shared vision of how the respective contaminated site could be remediated and redeveloped. We describe a framework of assessment methods and models that analyzes and visualizes site- and land use-specific spatial information at the screening level, with the aim to support the derivation of recommendable land use layouts and to initiate further and more detailed planning. The framework integrates a GIS-based identification of areas to be remediated, an estimation of associated clean-up costs, a spatially explicit market value appraisal, and an assessment of the planned future land use's contribution to sustainable urban and regional development. Case study results show that derived options are potentially favorable in both a sustainability and an economic sense and that iterative re-planning is facilitated by the evaluation and visualization of economic, ecological and socio-economic aspects. The framework supports an efficient early judgment about whether and how abandoned land may be assigned a sustainable and marketable land use.

Blowing in the wind: evaluating wind energy projects on the national forests

Treesearch

Kerry Schlichting; Evan Mercer

2011-01-01

The 650 million ac of federal lands are facing increased scrutiny for wind energy development. As a result, the US Forest Service has been directed to develop policies and procedures for siting wind energy projects. We incorporate geospatial site suitability analysis with applicable policy and management principles to illustrate the use of a Spatial Decision Support...

Optimizing spatial and temporal treatments to maintain effective fire and non-fire fuels treatments at landscape scales

Treesearch

J. Greg Jones; Woodam Chung; Carl Seielstad; Janet Sullivan; Kurt Krueger

2010-01-01

There is a recognized need to apply and maintain fuel treatments to reduce catastrophic wildland fires. A number of models and decision support systems have been developed for addressing different aspects of fuel treatments while considering other important resource management issues and constraints. Although these models address diverse aspects of the fuel treatment-...

Patentability aspects of computational cancer models

NASA Astrophysics Data System (ADS)

Lishchuk, Iryna

2017-07-01

Multiscale cancer models, implemented in silico, simulate tumor progression at various spatial and temporal scales. Having the innovative substance and possessing the potential of being applied as decision support tools in clinical practice, patenting and obtaining patent rights in cancer models seems prima facie possible. What legal hurdles the cancer models need to overcome for being patented we inquire from this paper.

A Decision Support System for Ecosystem-Based Management of Tropical Coral Reef Environments

NASA Astrophysics Data System (ADS)

Muller-Karger, F. E.; Eakin, C.; Guild, L. S.; Nemani, R. R.; Hu, C.; Lynds, S. E.; Li, J.; Vega-Rodriguez, M.; Coral Reef Watch Decision Support System Team

2010-12-01

We review a new collaborative program established between the National Aeronautics and Space Administration (NASA) and the National Oceanic and Atmospheric Administration (NOAA) to augment the NOAA Coral Reef Watch decision-support system. NOAA has developed a Decision Support System (DSS) under the Coral Reef Watch (CRW) program to forecast environmental stress in coral reef ecosystems around the world. This DSS uses models and 50 km Advanced Very High Resolution Radiometer (AVHRR) to generate “HotSpot” and Degree Heating Week coral bleaching indices. These are used by scientists and resource managers around the world. These users, including National Marine Sanctuary managers, have expressed the need for higher spatial resolution tools to understand local issues. The project will develop a series of coral bleaching products at higher spatial resolution using Moderate Resolution Imaging Spectroradiometer (MODIS) and AVHRR data. We will generate and validate products at 1 km resolution for the Caribbean Sea and Gulf of Mexico, and test global assessments at 4 and 50 km. The project will also incorporate the Global Coral Reef Millennium Map, a 30-m resolution thematic classification of coral reefs developed by the NASA Landsat-7 Science Team, into the CRW. The Millennium Maps help understand the geomorphology of individual reefs around the world. The products will be available through the NOAA CRW and UNEP-WCMC web portals. The products will help users formulate policy options and management decisions. The augmented DSS has a global scope, yet it addresses the needs of local resource managers. The work complements efforts to map and monitor coral reef communities in the U.S. territories by NOAA, NASA, and the USGS, and is a contribution to international efforts in ecological forecasting of coral reefs under changing environments, coral reef research, resource management, and conservation. Acknowledgement: Funding is provided by the NASA Ecological Forecasting application area and by NOAA NESDIS.

Coordination of short-term and long-term mitigation measures of hydro-meteorological risks: the importance of establishing a link between emergency management and spatial planning

NASA Astrophysics Data System (ADS)

Prenger-Berninghoff, Kathrin; Cortes, V. Juliette; Aye, Zar Chi; Sprague, Teresa

2013-04-01

The management of natural hazards involves, as generally known, the four stages of the risk management cycle: Prevention, preparedness, response and recovery. Accordingly, the mitigation of disasters can be performed in terms of short-term and long-term purposes. Whereas emergency management or civil protection helps to strengthen a community's capacity to be better prepared for natural hazards and to better respond in case a disaster strikes, thus addressing the short-term perspective, spatial planning serves long-term planning goals and can therefore implement long-term prevention measures. A purposefully applied risk mitigation strategy requires coordination of short-term and long-term mitigation measures and thus an effective coordination of emergency management and spatial planning. Several actors are involved in risk management and should consequently be linked throughout the whole risk management cycle. However, these actors, partly because of a historically fragmented administrative system, are hardly connected to each other, with spatial planning only having a negligible role compared to other actors1, a problem to which Young (2002) referred to as the "problem of interplay". In contrast, information transfer and decision-taking happen at the same time and are not coordinated among different actors. This applies to the prevention and preparedness phase as well as to the recovery phase, which basically constitutes the prevention phase for the next disaster2. Since investments in both risk prevention and emergency preparedness and response are considered necessary, a better coordination of the two approaches is required. In this regard, Decision Support Systems (DSS) can be useful in order to provide support in the decision-making aspect of risk management. The research work currently undertaken examines the problem of interplay in the four case study areas of the Marie Curie ITN, CHANGES3. The link between different risk management actors will be explored by means of exploratory questionnaires and interviews with government agencies, local administrations, community and research organizations on each study site. First results provided will address the general role of spatial planning in risk management. Additionally, preliminary observations are made in regard to the coordination of emergency preparedness and long-term spatial planning activities. The observations consider that integration facilitates proactive strategies that aim at preventing disaster occurrence and promote interaction between involved parties. Finally, consideration is given to the potential use of a DSS tool to cover both aspects of spatial planning and emergency management in the risk management cycle.

A web platform for integrated surface water - groundwater modeling and data management

NASA Astrophysics Data System (ADS)

Fatkhutdinov, Aybulat; Stefan, Catalin; Junghanns, Ralf

2016-04-01

Model-based decision support systems are considered to be reliable and time-efficient tools for resources management in various hydrology related fields. However, searching and acquisition of the required data, preparation of the data sets for simulations as well as post-processing, visualization and publishing of the simulations results often requires significantly more work and time than performing the modeling itself. The purpose of the developed software is to combine data storage facilities, data processing instruments and modeling tools in a single platform which potentially can reduce time required for performing simulations, hence decision making. The system is developed within the INOWAS (Innovative Web Based Decision Support System for Water Sustainability under a Changing Climate) project. The platform integrates spatially distributed catchment scale rainfall - runoff, infiltration and groundwater flow models with data storage, processing and visualization tools. The concept is implemented in a form of a web-GIS application and is build based on free and open source components, including the PostgreSQL database management system, Python programming language for modeling purposes, Mapserver for visualization and publishing the data, Openlayers for building the user interface and others. Configuration of the system allows performing data input, storage, pre- and post-processing and visualization in a single not disturbed workflow. In addition, realization of the decision support system in the form of a web service provides an opportunity to easily retrieve and share data sets as well as results of simulations over the internet, which gives significant advantages for collaborative work on the projects and is able to significantly increase usability of the decision support system.

A compartmental-spatial system dynamics approach to ground water modeling.

PubMed

Roach, Jesse; Tidwell, Vince

2009-01-01

High-resolution, spatially distributed ground water flow models can prove unsuitable for the rapid, interactive analysis that is increasingly demanded to support a participatory decision environment. To address this shortcoming, we extend the idea of multiple cell (Bear 1979) and compartmental (Campana and Simpson 1984) ground water models developed within the context of spatial system dynamics (Ahmad and Simonovic 2004) for rapid scenario analysis. We term this approach compartmental-spatial system dynamics (CSSD). The goal is to balance spatial aggregation necessary to achieve a real-time integrative and interactive decision environment while maintaining sufficient model complexity to yield a meaningful representation of the regional ground water system. As a test case, a 51-compartment CSSD model was built and calibrated from a 100,0001 cell MODFLOW (McDonald and Harbaugh 1988) model of the Albuquerque Basin in central New Mexico (McAda and Barroll 2002). Seventy-seven percent of historical drawdowns predicted by the MODFLOW model were within 1 m of the corresponding CSSD estimates, and in 80% of the historical model run years the CSSD model estimates of river leakage, reservoir leakage, ground water flow to agricultural drains, and riparian evapotranspiration were within 30% of the corresponding estimates from McAda and Barroll (2002), with improved model agreement during the scenario period. Comparisons of model results demonstrate both advantages and limitations of the CCSD model approach.

Valuing investments in sustainable land management using an integrated modelling framework to support a watershed conservation scheme in the Upper Tana River, Kenya

NASA Astrophysics Data System (ADS)

Hunink, Johannes E.; Bryant, Benjamin P.; Vogl, Adrian; Droogers, Peter

2015-04-01

We analyse the multiple impacts of investments in sustainable land use practices on ecosystem services in the Upper Tana basin (Kenya) to support a watershed conservation scheme (a "water fund"). We apply an integrated modelling framework, building on previous field-based and modelling studies in the basin, and link biophysical outputs to economic benefits for the main actors in the basin. The first step in the modelling workflow is the use of a high-resolution spatial prioritization tool (Resource Investment Optimization System -- RIOS) to allocate the type and location of conservation investments in the different subbasins, subject to budget constraints and stakeholder concerns. We then run the Soil and Water Assessment Tool (SWAT) using the RIOS-identified investment scenarios to produce spatially explicit scenarios that simulate changes in water yield and suspended sediment. Finally, in close collaboration with downstream water users (urban water supply and hydropower) we link those biophysical outputs to monetary metrics, including: reduced water treatment costs, increased hydropower production, and crop yield benefits for upstream farmers in the conservation area. We explore how different budgets and different spatial targeting scenarios influence the return of the investments and the effectiveness of the water fund scheme. This study is novel in that it presents an integrated analysis targeting interventions in a decision context that takes into account local environmental and socio-economic conditions, and then relies on detailed, process-based, biophysical models to demonstrate the economic return on those investments. We conclude that the approach allows for an analysis on different spatial and temporal scales, providing conclusive evidence to stakeholders and decision makers on the contribution and benefits of the land-based investments in this basin. This is serving as foundational work to support the implementation of the Upper Tana-Nairobi Water Fund, a public-private partnership to safeguard ecosystem service provision and food security.

Generic Sensor Data Fusion Services for Web-enabled Environmental Risk Management and Decision-Support Systems

NASA Astrophysics Data System (ADS)

Sabeur, Zoheir; Middleton, Stuart; Veres, Galina; Zlatev, Zlatko; Salvo, Nicola

2010-05-01

The advancement of smart sensor technology in the last few years has led to an increase in the deployment of affordable sensors for monitoring the environment around Europe. This is generating large amounts of sensor observation information and inevitably leading to problems about how to manage large volumes of data as well as making sense out the data for decision-making. In addition, the various European Directives (Water Framework Diectives, Bathing Water Directives, Habitat Directives, etc.. ) which regulate human activities in the environment and the INSPIRE Directive on spatial information management regulations have implicitely led the designated European Member States environment agencies and authorities to put in place new sensor monitoring infrastructure and share information about environmental regions under their statutory responsibilities. They will need to work cross border and collectively reach environmental quality standards. They will also need to regularly report to the EC on the quality of the environments of which they are responsible and make such information accessible to the members of the public. In recent years, early pioneering work on the design of service oriented architecture using sensor networks has been achieved. Information web-services infrastructure using existing data catalogues and web-GIS map services can now be enriched with the deployment of new sensor observation and data fusion and modelling services using OGC standards. The deployment of the new services which describe sensor observations and intelligent data-processing using data fusion techniques can now be implemented and provide added value information with spatial-temporal uncertainties to the next generation of decision support service systems. The new decision support service systems have become key to implement across Europe in order to comply with EU environmental regulations and INSPIRE. In this paper, data fusion services using OGC standards with sensor observation data streams are described in context of a geo-distributed service infrastructure specialising in multiple environmental risk management and decision-support. The sensor data fusion services are deployed and validated in two use cases. These are respectively concerned with: 1) Microbial risks forecast in bathing waters; and 2) Geohazards in urban zones during underground tunneling activities. This research was initiated in the SANY Integrated Project(www.sany-ip.org) and funded by the European Commission under the 6th Framework Programme.

Digital Earth - A sustainable Earth

NASA Astrophysics Data System (ADS)

Mahavir

2014-02-01

All life, particularly human, cannot be sustainable, unless complimented with shelter, poverty reduction, provision of basic infrastructure and services, equal opportunities and social justice. Yet, in the context of cities, it is believed that they can accommodate more and more people, endlessly, regardless to their carrying capacity and increasing ecological footprint. The 'inclusion', for bringing more and more people in the purview of development is often limited to social and economic inclusion rather than spatial and ecological inclusion. Economic investment decisions are also not always supported with spatial planning decisions. Most planning for a sustainable Earth, be at a level of rural settlement, city, region, national or Global, fail on the capacity and capability fronts. In India, for example, out of some 8,000 towns and cities, Master Plans exist for only about 1,800. A chapter on sustainability or environment is neither statutorily compulsory nor a norm for these Master Plans. Geospatial technologies including Remote Sensing, GIS, Indian National Spatial Data Infrastructure (NSDI), Indian National Urban Information Systems (NUIS), Indian Environmental Information System (ENVIS), and Indian National GIS (NGIS), etc. have potential to map, analyse, visualize and take sustainable developmental decisions based on participatory social, economic and social inclusion. Sustainable Earth, at all scales, is a logical and natural outcome of a digitally mapped, conceived and planned Earth. Digital Earth, in fact, itself offers a platform to dovetail the ecological, social and economic considerations in transforming it into a sustainable Earth.

New Decision Support for Landslide and Other Disaster Events

NASA Astrophysics Data System (ADS)

Nair, U. S.; Keiser, K.; Wu, Y.; Kaulfus, A.; Srinivasan, K.; Anderson, E. R.; McEniry, M.

2013-12-01

An Event-Driven Data delivery (ED3) framework has been created that provides reusable services and configurations to support better data preparedness for decision support of disasters and other events by rapidly providing pre-planned access to data, special processing, modeling and other capabilities, all executed in response to criteria-based events. ED3 facilitates decision makers to plan in advance of disasters and other types of events for the data necessary for decisions and response activities. A layer of services provided in the ED3 framework allows systems to support user definition of subscriptions for data plans that will be triggered when events matching specified criteria occur. Pre-planning for data in response to events lessens the burden on decision makers in the aftermath of an event and allows planners to think through the desired processing for specialized data products. Additionally the ED3 framework provides support for listening for event alerts and support for multiple workflow managers that provide data and processing functionality in response to events. Landslides are often costly and, at times, deadly disaster events. Whereas intense and/or sustained rainfall is often the primary trigger for landslides, soil type and slope are also important factors in determining the location and timing of slope failure. Accounting for the substantial spatial variability of these factors is one of the major difficulties when predicting the timing and location of slope failures. A wireless sensor network (WSN), developed by NASA SERVIR and USRA, with peer-to-peer communication capability and low power consumption, is ideal for high spatial in situ monitoring in remote locations. In collaboration with the University of Huntsville at Alabama, WSN equipped with accelerometer, rainfall and soil moisture sensors is being integrated into an end-to-end landslide warning system. The WSN is being tested to ascertain communication capabilities and the density of nodes required depending upon the nature of terrain and land cover. The performance of a water table model, to be utilized in the end-to-end system, is being evaluated by comparing against landslides that occurred during the 6th and 7th of May, 2003 and 20th and 21st of April, 2011. The model provides a deterministic assessment of slope stability by evaluating horizontal and vertical transport of underground water and associated weight bearing capacity. In the proposed end-to-end system, the model will be coupled to the WSN, and the in situ data collected will be used to drive the model. The output from the model could be communicated back to the WSN providing the capability of generating warning of possible events to the ED3 framework to trigger additional data retrieval or the processing of additional models based on decision maker's ED3 preparedness plans. NASA's Applied Science Program has funded a feasibility study of the ED3 technology and as a result the capability is on track be integrated into existing decision support systems, with an initial reference implementation hosted at the Global Hydrology Resource Center, a NASA distributed active archive center (DAAC).

A web-based spatial decision supporting system (S-DSS) for grapevine quality: the viticultural tool of the SOILCONS-WEB Project

NASA Astrophysics Data System (ADS)

Manna, Piero; Bonfante, Antonello; Basile, Angelo; Langella, Giuliano; Agrillo, Antonietta; De Mascellis, Roberto; Florindo Mileti, Antonio; Minieri, Luciana; Orefice, Nadia; Terribile, Fabio

2014-05-01

The SOILCONSWEB Project aims to create a decision support system operating at the landscape scale (Spatial-DSS) for the protection and the management of soils in both agricultural and environmental issues; it is a cyber-infrastructure built on remote servers operating through the web at www.landconsultingweb.eu. It includes - among others - a series of tools specifically designed to a Viticulture aiming at high quality wines production. The system is realized thanks to a collaboration between the University of Naples Federico II, CNR ISAFoM, Ariespace srl and SeSIRCA-Campania Region within a 5-years LIFE+ project funded by European Community. The system includes tools based on modelling procedures at different level of complexity some of which specifically designed for viticulture issues. One of the implemented models arise from the original desktop based SWAP model (Kroes et al, 2008). It can be run "on the fly" through a very user friendly web-interface. The specific tool, thanks to the model based on the Richard's equation can produce data on vineyard water stress, simulating the soil water balances of the different soil types within an area of interest. Thanks to a specific program developed within the project activities, the Spatial-DSS every day acquires punctual weather data and automatically spatialize them with geostatistical approaches in order to use the data as input for the SPA (Soil Plant Atmosphere ) model running. In particular for defining the upper boundary condition (rainfall and temperatures to estimate ET0 by the Hargraves model). Soil hydraulic properties (47 soil profiles within the study area), also essential for modelling simulation, were measured in laboratory using the Wind's approach or estimated through HYPRES PTF. Water retention and hydraulic conductivity relationships were parameterized according to the van Genuchten-Mualem model; Decision makers (individuals, groups of interests and public bodies) through the DSS can have real-time (or near real-time) access to critical, accurate, complete and up-to-date spatial data/output models held/processed in multiple data stores. The system allows the users interested in viticulture to have free, easy and immediate access to a number of environmental data and information very useful for quality wines production and especially for viticulture planning and management in a context of environmental sustainability. It produces detailed spatial documents, report and maps on a series of questions including the identification and description of terroir characteristics. The user once connected to the S-DSS can select an area of interest (i.e. farm, municipality, district) or draw it and obtain in real time a series of detailed information regarding that specific area, including maps and reports of landscape physical factors (i.e. soils, climate, geology, geomorphology, etc.), viticulture suitability, plant disease data and modelling, trends of viticulture years, bioclimatic indexes, etc. The user can also choose between different options such as the time period of the simulation runs or the type of data (maps, report or graphs) to be produced by the system. The S-DSS is being developed, tested and applied in an area of about 20,000 ha in south of Italy (Valle Telesina, in Campania region) mainly vocated to quality wines production (designation of origin DOC and DOCG). Key words: Decision Support System, spatial data, model simulation, soil hydrological properties, cyber infrastructure.

A web based spatial decision supporting system for land management and soil conservation

NASA Astrophysics Data System (ADS)

Terribile, F.; Agrillo, A.; Bonfante, A.; Buscemi, G.; Colandrea, M.; D'Antonio, A.; De Mascellis, R.; De Michele, C.; Langella, G.; Manna, P.; Marotta, L.; Mileti, F. A.; Minieri, L.; Orefice, N.; Valentini, S.; Vingiani, S.; Basile, A.

2015-02-01

Today it is evident that there are many contrasting demands on our landscape (e.g. food security, more sustainable agriculture, higher income in rural areas, etc.) but also many land degradation problems. It has been proved that providing operational answers to these demands and problems is extremely difficult. Here we aim to demonstrate that a Spatial Decision Support System based on geospatial cyber-infrastructure (GCI) can embody all of the above, so producing a smart system for supporting decision making for agriculture, forestry and urban planning with respect to the landscape. In this paper, we discuss methods and results of a special kind of GCI architecture, one that is highly focused on soil and land conservation (SOILCONSWEB-LIFE+ project). The system allows us to obtain dynamic, multidisciplinary, multiscale, and multifunctional answers to agriculture, forestry and urban planning issues through the web. The system has been applied to and tested in an area of about 20 000 ha in the South of Italy, within the framework of a European LIFE+ project. The paper reports - as a case study - results from two different applications dealing with agriculture (olive growth tool) and environmental protection (soil capability to protect groundwater). Developed with the help of end users, the system is starting to be adopted by local communities. The system indirectly explores a change of paradigm for soil and landscape scientists. Indeed, the potential benefit is shown of overcoming current disciplinary fragmentation over landscape issues by offering - through a smart web based system - truly integrated geospatial knowledge that may be directly and freely used by any end user (http://www.landconsultingweb.eu). This may help bridge the last much important divide between scientists working on the landscape and end users.

A Web-based spatial decision supporting system for land management and soil conservation

NASA Astrophysics Data System (ADS)

Terribile, F.; Agrillo, A.; Bonfante, A.; Buscemi, G.; Colandrea, M.; D'Antonio, A.; De Mascellis, R.; De Michele, C.; Langella, G.; Manna, P.; Marotta, L.; Mileti, F. A.; Minieri, L.; Orefice, N.; Valentini, S.; Vingiani, S.; Basile, A.

2015-07-01

Today it is evident that there are many contrasting demands on our landscape (e.g. food security, more sustainable agriculture, higher income in rural areas, etc.) as well as many land degradation problems. It has been proved that providing operational answers to these demands and problems is extremely difficult. Here we aim to demonstrate that a spatial decision support system based on geospatial cyberinfrastructure (GCI) can address all of the above, so producing a smart system for supporting decision making for agriculture, forestry, and urban planning with respect to the landscape. In this paper, we discuss methods and results of a special kind of GCI architecture, one that is highly focused on land management and soil conservation. The system allows us to obtain dynamic, multidisciplinary, multiscale, and multifunctional answers to agriculture, forestry, and urban planning issues through the Web. The system has been applied to and tested in an area of about 20 000 ha in the south of Italy, within the framework of a European LIFE+ project (SOILCONSWEB). The paper reports - as a case study - results from two different applications dealing with agriculture (olive growth tool) and environmental protection (soil capability to protect groundwater). Developed with the help of end users, the system is starting to be adopted by local communities. The system indirectly explores a change of paradigm for soil and landscape scientists. Indeed, the potential benefit is shown of overcoming current disciplinary fragmentation over landscape issues by offering - through a smart Web-based system - truly integrated geospatial knowledge that may be directly and freely used by any end user (www.landconsultingweb.eu). This may help bridge the last very important divide between scientists working on the landscape and end users.

Data-Driven Geospatial Visual Analytics for Real-Time Urban Flooding Decision Support

NASA Astrophysics Data System (ADS)

Liu, Y.; Hill, D.; Rodriguez, A.; Marini, L.; Kooper, R.; Myers, J.; Wu, X.; Minsker, B. S.

2009-12-01

Urban flooding is responsible for the loss of life and property as well as the release of pathogens and other pollutants into the environment. Previous studies have shown that spatial distribution of intense rainfall significantly impacts the triggering and behavior of urban flooding. However, no general purpose tools yet exist for deriving rainfall data and rendering them in real-time at the resolution of hydrologic units used for analyzing urban flooding. This paper presents a new visual analytics system that derives and renders rainfall data from the NEXRAD weather radar system at the sewershed (i.e. urban hydrologic unit) scale in real-time for a Chicago stormwater management project. We introduce a lightweight Web 2.0 approach which takes advantages of scientific workflow management and publishing capabilities developed at NCSA (National Center for Supercomputing Applications), streaming data-aware semantic content management repository, web-based Google Earth/Map and time-aware KML (Keyhole Markup Language). A collection of polygon-based virtual sensors is created from the NEXRAD Level II data using spatial, temporal and thematic transformations at the sewershed level in order to produce persistent virtual rainfall data sources for the animation. Animated color-coded rainfall map in the sewershed can be played in real-time as a movie using time-aware KML inside the web browser-based Google Earth for visually analyzing the spatiotemporal patterns of the rainfall intensity in the sewershed. Such system provides valuable information for situational awareness and improved decision support during extreme storm events in an urban area. Our further work includes incorporating additional data (such as basement flooding events data) or physics-based predictive models that can be used for more integrated data-driven decision support.

Regulating outdoor advertisement boards; employing spatial decision support system to control urban visual pollution

NASA Astrophysics Data System (ADS)

Wakil, K.; Hussnain, MQ; Tahir, A.; Naeem, M. A.

2016-06-01

Unmanaged placement, size, location, structure and contents of outdoor advertisement boards have resulted in severe urban visual pollution and deterioration of the socio-physical living environment in urban centres of Pakistan. As per the regulatory instruments, the approval decision for a new advertisement installation is supposed to be based on the locational density of existing boards and their proximity or remoteness to certain land- uses. In cities, where regulatory tools for the control of advertisement boards exist, responsible authorities are handicapped in effective implementation due to the absence of geospatial analysis capacity. This study presents the development of a spatial decision support system (SDSS) for regularization of advertisement boards in terms of their location and placement. The knowledge module of the proposed SDSS is based on provisions and restrictions prescribed in regulatory documents. While the user interface allows visualization and scenario evaluation to understand if the new board will affect existing linear density on a particular road and if it violates any buffer restrictions around a particular land use. Technically the structure of the proposed SDSS is a web-based solution which includes open geospatial tools such as OpenGeo Suite, GeoExt, PostgreSQL, and PHP. It uses three key data sets including road network, locations of existing billboards and building parcels with land use information to perform the analysis. Locational suitability has been calculated using pairwise comparison through analytical hierarchy process (AHP) and weighted linear combination (WLC). Our results indicate that open geospatial tools can be helpful in developing an SDSS which can assist solving space related iterative decision challenges on outdoor advertisements. Employing such a system will result in effective implementation of regulations resulting in visual harmony and aesthetic improvement in urban communities.

Cells, circuits, and choices: social influences on perceptual decision making.

PubMed

Mojzisch, Andreas; Krug, Kristine

2008-12-01

Making decisions is an integral part of everyday life. Social psychologists have demonstrated in many studies that humans' decisions are frequently and strongly influenced by the opinions of others--even in simple perceptual decisions, where, for example, participants have to judge what an image looks like. However, because the effect of other people's opinions on decision making has remained largely unaddressed by the neuroimaging and neurophysiology literature, we are only beginning to understand how social influence is integrated into the decision-making process. We put forward the thesis that by probing the neurophysiology of social influence with perceptual decision-making tasks similar to those used in the seminal work of Asch (1952, 1956), this gap could be remedied. Perceptual paradigms are already widely used to probe neuronal mechanisms of decision making in nonhuman primates. There is also increasing evidence about how nonhuman primates' behavior is influenced by observing conspecifics. The high spatial and temporal resolution of neurophysiological recordings in awake monkeys could provide insight into where and how social influence modulates decision making, and thus should enable us to develop detailed functional models of the neural mechanisms that support the integration of social influence into the decision-making process.

A mixed integer program to model spatial wildfire behavior and suppression placement decisions

Treesearch

Erin J. Belval; Yu Wei; Michael Bevers

2015-01-01

Wildfire suppression combines multiple objectives and dynamic fire behavior to form a complex problem for decision makers. This paper presents a mixed integer program designed to explore integrating spatial fire behavior and suppression placement decisions into a mathematical programming framework. Fire behavior and suppression placement decisions are modeled using...

The development and application of a decision support system for land management in the Lake Tahoe Basin—The Land Use Simulation Model

USGS Publications Warehouse

Forney, William M.; Oldham, I. Benson; Crescenti, Neil

2013-01-01

This report describes and applies the Land Use Simulation Model (LUSM), the final modeling product for the long-term decision support project funded by the Southern Nevada Public Land Management Act and developed by the U.S. Geological Survey’s Western Geographic Science Center for the Lake Tahoe Basin. Within the context of the natural-resource management and anthropogenic issues of the basin and in an effort to advance land-use and land-cover change science, this report addresses the problem of developing the LUSM as a decision support system. It includes consideration of land-use modeling theory, fire modeling and disturbance in the wildland-urban interface, historical land-use change and its relation to active land management, hydrologic modeling and the impact of urbanization as related to the Lahontan Regional Water Quality Control Board’s recently developed Total Maximum Daily Load report for the basin, and biodiversity in urbanizing areas. The LUSM strives to inform land-management decisions in a complex regulatory environment by simulating parcel-based, land-use transitions with a stochastic, spatially constrained, agent-based model. The tool is intended to be useful for multiple purposes, including the multiagency Pathway 2007 regional planning effort, the Tahoe Regional Planning Agency (TRPA) Regional Plan Update, and complementary research endeavors and natural-resource-management efforts. The LUSM is an Internet-based, scenario-generation decision support tool for allocating retired and developed parcels over the next 20 years. Because USGS staff worked closely with TRPA staff and their “Code of Ordinances” and analyzed datasets of historical management and land-use practices, this report accomplishes the task of providing reasonable default values for a baseline scenario that can be used in the LUSM. One result from the baseline scenario for the model suggests that all vacant parcels could be allocated within 12 years. Results also include: assessment of model functionality, brief descriptions of the 7 basic output tables, assessment of the rate of change in land-use allocation pools over time, locations and amounts of the spatially explicit probabilities of land-use transitions by real estate commodity, and analysis of the state change from today’s existing land cover to potential land uses in the future. Assumptions and limitations of the model are presented. This report concludes with suggested next steps to support the continued utility of the LUSM and additional research avenues.

Geo-portal as a planning instrument: supporting decision making and fostering market potential of Energy efficiency in buildings

NASA Astrophysics Data System (ADS)

Cuca, Branka; Brumana, Raffaella; Oreni, Daniela; Iannaccone, Giuliana; Sesana, Marta Maria

2014-03-01

Steady technological progress has led to a noticeable advancement in disciplines associated with Earth observation. This has enabled information transition regarding changing scenarios, both natural and urban, to occur in (almost) real time. In particular, the need for integration on a local scale with the wider territorial framework has occurred in analysis and monitoring of built environments over the last few decades. The progress of Geographic Information (GI) science has provided significant advancements when it comes to spatial analysis, while the almost free availability of the internet has ensured a fast and constant exchange of geo-information, even for everyday users' requirements. Due to its descriptive and semantic nature, geo-spatial information is capable of providing a complete overview of a certain phenomenon and of predicting the implications within the natural, social and economic context. However, in order to integrate geospatial data into decision making processes, it is necessary to provide a specific context, which is well supported by verified data. This paper investigates the potentials of geo-portals as planning instruments developed to share multi-temporal/multi-scale spatial data, responding to specific end-users' demands in the case of Energy efficiency in Buildings (EeB) across European countries. The case study regards the GeoCluster geo-portal and mapping tool (Project GE2O, FP7), built upon a GeoClustering methodology for mapping of indicators relevant for energy efficiency technologies in the construction sector.

FOODIE: Farm-Oriented Open Data in Europe

NASA Astrophysics Data System (ADS)

Ángel Esbri Palomares, Miguel; Charvat, Karel; Campos, Antonio Manuel; Palma, Raúl

2014-05-01

The agriculture sector is a unique sector due to its strategic importance for both European citizens (consumers) and European economy (regional and global) which, ideally, should make the whole sector a network of interacting organizations. Rural areas are of particular importance with respect to the agro-food sector and should be specifically addressed within this scope. The different groups of stakeholders involved in the agricultural activities have to manage many different and heterogeneous sources of information that need to be combined in order to make economically and environmentally sound decisions, which include (among others) the definition of policies (subsidies, standardisation and regulation, national strategies for rural development, climate change), valuation of ecological performances, development of sustainable agriculture, crop recollection timing and pricing, plagues detection, etc. Such processes are very labour intensive because most parts have to be executed manually and the necessary information is not always available or easily accessible. In this context, future agriculture knowledge management systems have to support not only direct profitability of agriculture or environment protection, but also activities of individuals and groups allowing effective collaboration among groups in agri-food industry, consumers, public administrations and wider stakeholders communities, especially in rural domain. To that end FOODIE project aims at building an open and interoperable agricultural specialized platform hub on the cloud for the management of spatial and non-spatial data relevant for farming production; for discovery of spatial and non-spatial agriculture related data from heterogeneous sources; integration of existing and valuable European open datasets related to agriculture; data publication and data linking of external agriculture data sources contributed by different public and private stakeholders allowing to provide specific and high-value applications and services for the support in the planning and decision-making processes of different stakeholders groups related to the agricultural and environmental domains.

IDESSA: An Integrative Decision Support System for Sustainable Rangeland Management in Southern African Savannas

NASA Astrophysics Data System (ADS)

Meyer, Hanna; Authmann, Christian; Dreber, Niels; Hess, Bastian; Kellner, Klaus; Morgenthal, Theunis; Nauss, Thomas; Seeger, Bernhard; Tsvuura, Zivanai; Wiegand, Kerstin

2017-04-01

Bush encroachment is a syndrome of land degradation that occurs in many savannas including those of southern Africa. The increase in density, cover or biomass of woody vegetation often has negative effects on a range of ecosystem functions and services, which are hardly reversible. However, despite its importance, neither the causes of bush encroachment, nor the consequences of different resource management strategies to combat or mitigate related shifts in savanna states are fully understood. The project "IDESSA" (An Integrative Decision Support System for Sustainable Rangeland Management in Southern African Savannas) aims to improve the understanding of the complex interplays between land use, climate patterns and vegetation dynamics and to implement an integrative monitoring and decision-support system for the sustainable management of different savanna types. For this purpose, IDESSA follows an innovative approach that integrates local knowledge, botanical surveys, remote-sensing and machine-learning based time-series of atmospheric and land-cover dynamics, spatially explicit simulation modeling and analytical database management. The integration of the heterogeneous data will be implemented in a user oriented database infrastructure and scientific workflow system. Accessible via web-based interfaces, this database and analysis system will allow scientists to manage and analyze monitoring data and scenario computations, as well as allow stakeholders (e. g. land users, policy makers) to retrieve current ecosystem information and seasonal outlooks. We present the concept of the project and show preliminary results of the realization steps towards the integrative savanna management and decision-support system.

A GIS-based decision support system for regional eco-security assessment and its application on the Tibetan Plateau.

PubMed

Xiaodan, Wang; Xianghao, Zhong; Pan, Gao

2010-10-01

Regional eco-security assessment is an intricate, challenging task. In previous studies, the integration of eco-environmental models and geographical information systems (GIS) usually takes two approaches: loose coupling and tight coupling. However, the present study used a full coupling approach to develop a GIS-based regional eco-security assessment decision support system (ESDSS). This was achieved by merging the pressure-state-response (PSR) model and the analytic hierarchy process (AHP) into ArcGIS 9 as a dynamic link library (DLL) using ArcObjects in ArcGIS and Visual Basic for Applications. Such an approach makes it easy to capitalize on the GIS visualization and spatial analysis functions, thereby significantly supporting the dynamic estimation of regional eco-security. A case study is presented for the Tibetan Plateau, known as the world's "third pole" after the Arctic and Antarctic. Results verified the usefulness and feasibility of the developed method. As a useful tool, the ESDSS can also help local managers to make scientifically-based and effective decisions about Tibetan eco-environmental protection and land use. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Using ecosystem services in decision-making to support sustainable development: Critiques, model development, a case study, and perspectives.

PubMed

Zagonari, Fabio

2016-04-01

In this paper, I propose a general, consistent, and operational approach that accounts for ecosystem services in a decision-making context: I link ecosystem services to sustainable development criteria; adopt multi-criteria analysis to measure ecosystem services, with weights provided by stakeholders used to account for equity issues; apply both temporal and spatial discount rates; and adopt a technique to order performance of the possible solutions based on their similarity to an ideal solution (TOPSIS) to account for uncertainty about the parameters and functions. Applying this approach in a case study of an offshore research platform in Italy (CNR Acqua Alta) revealed that decisions depend non-linearly on the degree of loss aversion, to a smaller extent on a global focus (as opposed to a local focus), and to the smallest extent on social concerns (as opposed to economic or environmental concerns). Application of the general model to the case study leads to the conclusion that the ecosystem services framework is likely to be less useful in supporting decisions than in identifying the crucial features on which decisions depend, unless experts from different disciplines are involved, stakeholders are represented, and experts and stakeholders achieve mutual understanding. Copyright © 2016 Elsevier B.V. All rights reserved.

The Influence of Endogenous and Exogenous Spatial Attention on Decision Confidence.

PubMed

Kurtz, Phillipp; Shapcott, Katharine A; Kaiser, Jochen; Schmiedt, Joscha T; Schmid, Michael C

2017-07-25

Spatial attention allows us to make more accurate decisions about events in our environment. Decision confidence is thought to be intimately linked to the decision making process as confidence ratings are tightly coupled to decision accuracy. While both spatial attention and decision confidence have been subjected to extensive research, surprisingly little is known about the interaction between these two processes. Since attention increases performance it might be expected that confidence would also increase. However, two studies investigating the effects of endogenous attention on decision confidence found contradictory results. Here we investigated the effects of two distinct forms of spatial attention on decision confidence; endogenous attention and exogenous attention. We used an orientation-matching task, comparing the two attention conditions (endogenous and exogenous) to a control condition without directed attention. Participants performed better under both attention conditions than in the control condition. Higher confidence ratings than the control condition were found under endogenous attention but not under exogenous attention. This finding suggests that while attention can increase confidence ratings, it must be voluntarily deployed for this increase to take place. We discuss possible implications of this relative overconfidence found only during endogenous attention with respect to the theoretical background of decision confidence.

Identifying and assessing critical uncertainty thresholds in a forest pest risk model

Treesearch

Frank H. Koch; Denys Yemshanov

2015-01-01

Pest risk maps can provide helpful decision support for invasive alien species management, but often fail to address adequately the uncertainty associated with their predicted risk values. Th is chapter explores how increased uncertainty in a risk model’s numeric assumptions (i.e. its principal parameters) might aff ect the resulting risk map. We used a spatial...

Modeling forest planning trade-offs on the Colorado Front Range using MAGIS, an optimization, spatial decision support system

Treesearch

Edward B. Butler

2005-01-01

The fires of 2000 and 2002 catalyzed a national mandate for fuel treatment programs to facilitate wildfire mitigation, yet the issues that need to be considered when planning large landscape projects are daunting, often ending in gridlock due to planning conflicts. Hazardous fuels maps help little when planning for integrated, system-wide ecological objectives and fail...

Spatial and Temporal Flood Risk Assessment for Decision Making Approach

NASA Astrophysics Data System (ADS)

Azizat, Nazirah; Omar, Wan-Mohd-Sabki Wan

2018-03-01

Heavy rainfall, adversely impacting inundation areas, depends on the magnitude of the flood. Significantly, location of settlements, infrastructure and facilities in floodplains result in many regions facing flooding risks. A problem faced by the decision maker in an assessment of flood vulnerability and evaluation of adaptation measures is recurrent flooding in the same areas. Identification of recurrent flooding areas and frequency of floods should be priorities for flood risk management. However, spatial and temporal variability become major factors of uncertainty in flood risk management. Therefore, dynamic and spatial characteristics of these changes in flood impact assessment are important in making decisions about the future of infrastructure development and community life. System dynamics (SD) simulation and hydrodynamic modelling are presented as tools for modelling the dynamic characteristics of flood risk and spatial variability. This paper discusses the integration between spatial and temporal information that is required by the decision maker for the identification of multi-criteria decision problems involving multiple stakeholders.

A decision support tool for simulating the effects of alternative policies affecting water resources: an application at the European scale

NASA Astrophysics Data System (ADS)

Fassio, A.; Giupponi, C.; Hiederer, R.; Simota, C.

2005-03-01

This paper presents the methodology applied and results obtained from testing the Decision Support System 'mDSS' developed by the MULINO Project (Multi-sectoral, integrated and operational decision support system for the sustainable use of water resources at the catchment scale), for assessing alternative measures for the reduction of nitrogen pressure from agriculture on water resources at European level. The European policy background is set by the EU Nitrates Directive (91/676/EEC) and the Water Framework Directive (2000/60/EC). The nature of the research is exploratory. It is aimed in particular at testing the usefulness of available official statistics for ex ante evaluations of alternative policy measures at the European scale, and the feasibility of such operations within the newly released mDSS software. Alternative measures for reducing N-pressure and spatial targets were designed and simulated in a GIS environment based on raster maps of 1 km resolution. The geographic extent of the present work is defined as the agricultural land of EU15. Data deriving from official statistics were used to calculate a simplified nitrogen balance, in which the sources of nitrogen are separated into organic (livestock manure) and mineral fertilisers, to distinguish the potential contribution of livestock and crop productions to water pollution at the river basin scale. Spatial indicators and evaluation indices were defined within a conceptual framework. For the study the DPSIR approach (Driving force, Pressure, State, Impact, Response), proposed by the European Environmental Agency, was adopted. The approach was subsequently elaborated by means of the multi-criteria functionality provided by mDSS. The results of this application test at the regional scale highlight the potential of the tool for evaluating the effects of policy measures targeted at different spatial implementation strategies through the application of simple screening models and using available data covering the EU15. The paper also contributes to identifying current strengths and weaknesses of available information, of the adopted methodology and the DSS tool.

LandCaRe DSS--an interactive decision support system for climate change impact assessment and the analysis of potential agricultural land use adaptation strategies.

PubMed

Wenkel, Karl-Otto; Berg, Michael; Mirschel, Wilfried; Wieland, Ralf; Nendel, Claas; Köstner, Barbara

2013-09-01

Decision support to develop viable climate change adaptation strategies for agriculture and regional land use management encompasses a wide range of options and issues. Up to now, only a few suitable tools and methods have existed for farmers and regional stakeholders that support the process of decision-making in this field. The interactive model-based spatial information and decision support system LandCaRe DSS attempts to close the existing methodical gap. This system supports interactive spatial scenario simulations, multi-ensemble and multi-model simulations at the regional scale, as well as the complex impact assessment of potential land use adaptation strategies at the local scale. The system is connected to a local geo-database and via the internet to a climate data server. LandCaRe DSS uses a multitude of scale-specific ecological impact models, which are linked in various ways. At the local scale (farm scale), biophysical models are directly coupled with a farm economy calculator. New or alternative simulation models can easily be added, thanks to the innovative architecture and design of the DSS. Scenario simulations can be conducted with a reasonable amount of effort. The interactive LandCaRe DSS prototype also offers a variety of data analysis and visualisation tools, a help system for users and a farmer information system for climate adaptation in agriculture. This paper presents the theoretical background, the conceptual framework, and the structure and methodology behind LandCaRe DSS. Scenario studies at the regional and local scale for the two Eastern German regions of Uckermark (dry lowlands, 2600 km(2)) and Weißeritz (humid mountain area, 400 km(2)) were conducted in close cooperation with stakeholders to test the functionality of the DSS prototype. The system is gradually being transformed into a web version (http://www.landcare-dss.de) to ensure the broadest possible distribution of LandCaRe DSS to the public. The system will be continuously developed, updated and used in different research projects and as a learning and knowledge-sharing tool for students. The main objective of LandCaRe DSS is to provide information on the complex long-term impacts of climate change and on potential management options for adaptation by answering "what-if" type questions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Habitat risk assessment for regional ocean planning in the U.S. Northeast and Mid-Atlantic.

PubMed

Wyatt, Katherine H; Griffin, Robert; Guerry, Anne D; Ruckelshaus, Mary; Fogarty, Michael; Arkema, Katie K

2017-01-01

Coastal habitats provide important benefits to people, including habitat for species targeted by fisheries and opportunities for tourism and recreation. Yet, such human activities also can imperil these habitats and undermine the ecosystem services they provide to people. Cumulative risk assessment provides an analytical framework for synthesizing the influence of multiple stressors across habitats and decision-support for balancing human uses and ecosystem health. To explore cumulative risk to habitats in the U.S. Northeast and Mid-Atlantic Ocean Planning regions, we apply the open-source InVEST Habitat Risk Assessment model to 13 habitats and 31 stressors in an exposure-consequence framework. In doing so, we advance the science priorities of EBM and both regional planning bodies by synthesizing the wealth of available data to improve our understanding of human uses and how they affect marine resources. We find that risk to ecosystems is greatest first, along the coast, where a large number of stressors occur in close proximity and secondly, along the continental shelf, where fewer, higher consequence activities occur. Habitats at greatest risk include soft and hard-bottom nearshore areas, tidal flats, soft-bottom shelf habitat, and rocky intertidal zones-with the degree of risk varying spatially. Across all habitats, our results indicate that rising sea surface temperatures, commercial fishing, and shipping consistently and disproportionally contribute to risk. Further, our findings suggest that management in the nearshore will require simultaneously addressing the temporal and spatial overlap as well as intensity of multiple human activities and that management in the offshore requires more targeted efforts to reduce exposure from specific threats. We offer a transparent, generalizable approach to evaluating cumulative risk to multiple habitats and illustrate the spatially heterogeneous nature of impacts along the eastern Atlantic coast and the importance of spatial scale in estimating such impacts. These results offer a valuable decision-support tool by helping to constrain the decision space, focus attention on habitats and locations at the greatest risk, and highlight effect management strategies.

Habitat risk assessment for regional ocean planning in the U.S. Northeast and Mid-Atlantic

PubMed Central

Guerry, Anne D.; Ruckelshaus, Mary; Fogarty, Michael; Arkema, Katie K.

2017-01-01

Coastal habitats provide important benefits to people, including habitat for species targeted by fisheries and opportunities for tourism and recreation. Yet, such human activities also can imperil these habitats and undermine the ecosystem services they provide to people. Cumulative risk assessment provides an analytical framework for synthesizing the influence of multiple stressors across habitats and decision-support for balancing human uses and ecosystem health. To explore cumulative risk to habitats in the U.S. Northeast and Mid-Atlantic Ocean Planning regions, we apply the open-source InVEST Habitat Risk Assessment model to 13 habitats and 31 stressors in an exposure-consequence framework. In doing so, we advance the science priorities of EBM and both regional planning bodies by synthesizing the wealth of available data to improve our understanding of human uses and how they affect marine resources. We find that risk to ecosystems is greatest first, along the coast, where a large number of stressors occur in close proximity and secondly, along the continental shelf, where fewer, higher consequence activities occur. Habitats at greatest risk include soft and hard-bottom nearshore areas, tidal flats, soft-bottom shelf habitat, and rocky intertidal zones—with the degree of risk varying spatially. Across all habitats, our results indicate that rising sea surface temperatures, commercial fishing, and shipping consistently and disproportionally contribute to risk. Further, our findings suggest that management in the nearshore will require simultaneously addressing the temporal and spatial overlap as well as intensity of multiple human activities and that management in the offshore requires more targeted efforts to reduce exposure from specific threats. We offer a transparent, generalizable approach to evaluating cumulative risk to multiple habitats and illustrate the spatially heterogeneous nature of impacts along the eastern Atlantic coast and the importance of spatial scale in estimating such impacts. These results offer a valuable decision-support tool by helping to constrain the decision space, focus attention on habitats and locations at the greatest risk, and highlight effect management strategies. PMID:29261672

Implication of the first decision on visual information-sampling in the spatial frequency domain in pulmonary nodule recognition

NASA Astrophysics Data System (ADS)

Pietrzyk, Mariusz W.; Manning, David; Donovan, Tim; Dix, Alan

2010-02-01

Aim: To investigate the impact on visual sampling strategy and pulmonary nodule recognition of image-based properties of background locations in dwelled regions where the first overt decision was made. . Background: Recent studies in mammography show that the first overt decision (TP or FP) has an influence on further image reading including the correctness of the following decisions. Furthermore, the correlation between the spatial frequency properties of the local background following decision sites and the first decision correctness has been reported. Methods: Subjects with different radiological experience were eye tracked during detection of pulmonary nodules from PA chest radiographs. Number of outcomes and the overall quality of performance are analysed in terms of the cases where correct or incorrect decisions were made. JAFROC methodology is applied. The spatial frequency properties of selected local backgrounds related to a certain decisions were studied. ANOVA was used to compare the logarithmic values of energy carried by non redundant stationary wavelet packet coefficients. Results: A strong correlation has been found between the number of TP as a first decision and the JAFROC score (r = 0.74). The number of FP as a first decision was found negatively correlated with JAFROC (r = -0.75). Moreover, the differential spatial frequency profiles outcomes depend on the first choice correctness.

Environmental risk management for radiological accidents: integrating risk assessment and decision analysis for remediation at different spatial scales.

PubMed

Yatsalo, Boris; Sullivan, Terrence; Didenko, Vladimir; Linkov, Igor

2011-07-01

The consequences of the Tohuku earthquake and subsequent tsunami in March 2011 caused a loss of power at the Fukushima Daiichi nuclear power plant, in Japan, and led to the release of radioactive materials into the environment. Although the full extent of the contamination is not currently known, the highly complex nature of the environmental contamination (radionuclides in water, soil, and agricultural produce) typical of nuclear accidents requires a detailed geospatial analysis of information with the ability to extrapolate across different scales with applications to risk assessment models and decision making support. This article briefly summarizes the approach used to inform risk-based land management and remediation decision making after the Chernobyl, Soviet Ukraine, accident in 1986. Copyright © 2011 SETAC.

a Novel Approach to Support Majority Voting in Spatial Group Mcdm Using Density Induced Owa Operator for Seismic Vulnerability Assessment

NASA Astrophysics Data System (ADS)

Moradi, M.; Delavar, M. R.; Moshiri, B.; Khamespanah, F.

2014-10-01

Being one of the most frightening disasters, earthquakes frequently cause huge damages to buildings, facilities and human beings. Although the prediction of characteristics of an earthquake seems to be impossible, its loss and damage is predictable in advance. Seismic loss estimation models tend to evaluate the extent to which the urban areas are vulnerable to earthquakes. Many factors contribute to the vulnerability of urban areas against earthquakes including age and height of buildings, the quality of the materials, the density of population and the location of flammable facilities. Therefore, seismic vulnerability assessment is a multi-criteria problem. A number of multi criteria decision making models have been proposed based on a single expert. The main objective of this paper is to propose a model which facilitates group multi criteria decision making based on the concept of majority voting. The main idea of majority voting is providing a computational tool to measure the degree to which different experts support each other's opinions and make a decision regarding this measure. The applicability of this model is examined in Tehran metropolitan area which is located in a seismically active region. The results indicate that neglecting the experts which get lower degrees of support from others enables the decision makers to avoid the extreme strategies. Moreover, a computational method is proposed to calculate the degree of optimism in the experts' opinions.

'spup' - an R package for uncertainty propagation in spatial environmental modelling

NASA Astrophysics Data System (ADS)

Sawicka, Kasia; Heuvelink, Gerard

2016-04-01

Computer models have become a crucial tool in engineering and environmental sciences for simulating the behaviour of complex static and dynamic systems. However, while many models are deterministic, the uncertainty in their predictions needs to be estimated before they are used for decision support. Currently, advances in uncertainty propagation and assessment have been paralleled by a growing number of software tools for uncertainty analysis, but none has gained recognition for a universal applicability, including case studies with spatial models and spatial model inputs. Due to the growing popularity and applicability of the open source R programming language we undertook a project to develop an R package that facilitates uncertainty propagation analysis in spatial environmental modelling. In particular, the 'spup' package provides functions for examining the uncertainty propagation starting from input data and model parameters, via the environmental model onto model predictions. The functions include uncertainty model specification, stochastic simulation and propagation of uncertainty using Monte Carlo (MC) techniques, as well as several uncertainty visualization functions. Uncertain environmental variables are represented in the package as objects whose attribute values may be uncertain and described by probability distributions. Both numerical and categorical data types are handled. Spatial auto-correlation within an attribute and cross-correlation between attributes is also accommodated for. For uncertainty propagation the package has implemented the MC approach with efficient sampling algorithms, i.e. stratified random sampling and Latin hypercube sampling. The design includes facilitation of parallel computing to speed up MC computation. The MC realizations may be used as an input to the environmental models called from R, or externally. Selected static and interactive visualization methods that are understandable by non-experts with limited background in statistics can be used to summarize and visualize uncertainty about the measured input, model parameters and output of the uncertainty propagation. We demonstrate that the 'spup' package is an effective and easy tool to apply and can be used in multi-disciplinary research and model-based decision support.

'spup' - an R package for uncertainty propagation analysis in spatial environmental modelling

NASA Astrophysics Data System (ADS)

Sawicka, Kasia; Heuvelink, Gerard

2017-04-01

Computer models have become a crucial tool in engineering and environmental sciences for simulating the behaviour of complex static and dynamic systems. However, while many models are deterministic, the uncertainty in their predictions needs to be estimated before they are used for decision support. Currently, advances in uncertainty propagation and assessment have been paralleled by a growing number of software tools for uncertainty analysis, but none has gained recognition for a universal applicability and being able to deal with case studies with spatial models and spatial model inputs. Due to the growing popularity and applicability of the open source R programming language we undertook a project to develop an R package that facilitates uncertainty propagation analysis in spatial environmental modelling. In particular, the 'spup' package provides functions for examining the uncertainty propagation starting from input data and model parameters, via the environmental model onto model predictions. The functions include uncertainty model specification, stochastic simulation and propagation of uncertainty using Monte Carlo (MC) techniques, as well as several uncertainty visualization functions. Uncertain environmental variables are represented in the package as objects whose attribute values may be uncertain and described by probability distributions. Both numerical and categorical data types are handled. Spatial auto-correlation within an attribute and cross-correlation between attributes is also accommodated for. For uncertainty propagation the package has implemented the MC approach with efficient sampling algorithms, i.e. stratified random sampling and Latin hypercube sampling. The design includes facilitation of parallel computing to speed up MC computation. The MC realizations may be used as an input to the environmental models called from R, or externally. Selected visualization methods that are understandable by non-experts with limited background in statistics can be used to summarize and visualize uncertainty about the measured input, model parameters and output of the uncertainty propagation. We demonstrate that the 'spup' package is an effective and easy tool to apply and can be used in multi-disciplinary research and model-based decision support.

Qualitative Description of Spatial Quality in Inclusive Architecture.

PubMed

Ryhl, Camilla; Kajita, Masashi; Sørensen, René

2016-01-01

Universal design (UD) has gained global significance and is in the process of institutionalisation in the Nordic Region. This is despite an urgent necessity for developing the theoretical basis and practical applicability of UD. Reflecting this need for furthering the comprehensive understanding of spatial implication of UD, this paper aims to contribute for articulating a means to assess the quality of UD in architecture. Drawing upon numerous cases from research conducted at the Danish Building Research Institute, the paper focuses on sensory aspects of spatial quality, and discusses as well as reflects an applied method for producing the qualitative description of selected buildings that embody UD through creative solutions. The qualitative description of collected examples appears to be effective in delineating sensory aspects of spatial experience; however the systematic development of assessment criteria is essential in order to support students and designers to make responsible decisions in shaping built environments that are accessible and inclusive but also enjoyable.

Facilitating participatory multilevel decision-making by using interactive mental maps.

PubMed

Pfeiffer, Constanze; Glaser, Stephanie; Vencatesan, Jayshree; Schliermann-Kraus, Elke; Drescher, Axel; Glaser, Rüdiger

2008-11-01

Participation of citizens in political, economic or social decisions is increasingly recognized as a precondition to foster sustainable development processes. Since spatial information is often important during planning and decision making, participatory mapping gains in popularity. However, little attention has been paid to the fact that information must be presented in a useful way to reach city planners and policy makers. Above all, the importance of visualisation tools to support collaboration, analytical reasoning, problem solving and decision-making in analysing and planning processes has been underestimated. In this paper, we describe how an interactive mental map tool has been developed in a highly interdisciplinary disaster management project in Chennai, India. We moved from a hand drawn mental maps approach to an interactive mental map tool. This was achieved by merging socio-economic and geospatial data on infrastructure, local perceptions, coping and adaptation strategies with remote sensing data and modern technology of map making. This newly developed interactive mapping tool allowed for insights into different locally-constructed realities and facilitated the communication of results to the wider public and respective policy makers. It proved to be useful in visualising information and promoting participatory decision-making processes. We argue that the tool bears potential also for health research projects. The interactive mental map can be used to spatially and temporally assess key health themes such as availability of, and accessibility to, existing health care services, breeding sites of disease vectors, collection and storage of water, waste disposal, location of public toilets or defecation sites.

Probabilistic Flood Maps to support decision-making: Mapping the Value of Information

NASA Astrophysics Data System (ADS)

Alfonso, L.; Mukolwe, M. M.; Di Baldassarre, G.

2016-02-01

Floods are one of the most frequent and disruptive natural hazards that affect man. Annually, significant flood damage is documented worldwide. Flood mapping is a common preimpact flood hazard mitigation measure, for which advanced methods and tools (such as flood inundation models) are used to estimate potential flood extent maps that are used in spatial planning. However, these tools are affected, largely to an unknown degree, by both epistemic and aleatory uncertainty. Over the past few years, advances in uncertainty analysis with respect to flood inundation modeling show that it is appropriate to adopt Probabilistic Flood Maps (PFM) to account for uncertainty. However, the following question arises; how can probabilistic flood hazard information be incorporated into spatial planning? Thus, a consistent framework to incorporate PFMs into the decision-making is required. In this paper, a novel methodology based on Decision-Making under Uncertainty theories, in particular Value of Information (VOI) is proposed. Specifically, the methodology entails the use of a PFM to generate a VOI map, which highlights floodplain locations where additional information is valuable with respect to available floodplain management actions and their potential consequences. The methodology is illustrated with a simplified example and also applied to a real case study in the South of France, where a VOI map is analyzed on the basis of historical land use change decisions over a period of 26 years. Results show that uncertain flood hazard information encapsulated in PFMs can aid decision-making in floodplain planning.

Spatial attention during saccade decisions.

PubMed

Jonikaitis, Donatas; Klapetek, Anna; Deubel, Heiner

2017-07-01

Behavioral measures of decision making are usually limited to observations of decision outcomes. In the present study, we made use of the fact that oculomotor and sensory selection are closely linked to track oculomotor decision making before oculomotor responses are made. We asked participants to make a saccadic eye movement to one of two memorized target locations and observed that visual sensitivity increased at both the chosen and the nonchosen saccade target locations, with a clear bias toward the chosen target. The time course of changes in visual sensitivity was related to saccadic latency, with the competition between the chosen and nonchosen targets resolved faster before short-latency saccades. On error trials, we observed an increased competition between the chosen and nonchosen targets. Moreover, oculomotor selection and visual sensitivity were influenced by top-down and bottom-up factors as well as by selection history and predicted the direction of saccades. Our findings demonstrate that saccade decisions have direct visual consequences and show that decision making can be traced in the human oculomotor system well before choices are made. Our results also indicate a strong association between decision making, saccade target selection, and visual sensitivity. NEW & NOTEWORTHY We show that saccadic decisions can be tracked by measuring spatial attention. Spatial attention is allocated in parallel to the two competing saccade targets, and the time course of spatial attention differs for fast-slow and for correct-erroneous decisions. Saccade decisions take the form of a competition between potential saccade goals, which is associated with spatial attention allocation to those locations. Copyright © 2017 the American Physiological Society.

Integrated planning and spatial evaluation of megasite remediation and reuse options.

PubMed

Schädler, Sebastian; Morio, Maximilian; Bartke, Stephan; Finkel, Michael

2012-01-01

Redevelopment of large contaminated brownfields (megasites) is often hampered by a lack of communication and harmonization among diverse stakeholders with potentially conflicting interests. Decision support is required to provide integrative yet transparent evaluation of often complex spatial information to stakeholders with different areas of expertise. It is considered crucial for successful redevelopment to identify a shared vision of how the respective contaminated site could be remediated and redeveloped. We describe a framework of assessment methods and models that analyzes and visualizes site- and land use-specific spatial information at the screening level, with the aim to support the derivation of recommendable land use layouts and to initiate further and more detailed planning. The framework integrates a GIS-based identification of areas to be remediated, an estimation of associated clean-up costs, a spatially explicit market value appraisal, and an assessment of the planned future land use's contribution to sustainable urban and regional development. Case study results show that derived options are potentially favorable in both a sustainability and an economic sense and that iterative re-planning is facilitated by the evaluation and visualization of economic, ecological and socio-economic aspects. The framework supports an efficient early judgment about whether and how abandoned land may be assigned a sustainable and marketable land use. Copyright © 2011 Elsevier B.V. All rights reserved.

Neural time course of visually enhanced echo suppression.

PubMed

Bishop, Christopher W; London, Sam; Miller, Lee M

2012-10-01

Auditory spatial perception plays a critical role in day-to-day communication. For instance, listeners utilize acoustic spatial information to segregate individual talkers into distinct auditory "streams" to improve speech intelligibility. However, spatial localization is an exceedingly difficult task in everyday listening environments with numerous distracting echoes from nearby surfaces, such as walls. Listeners' brains overcome this unique challenge by relying on acoustic timing and, quite surprisingly, visual spatial information to suppress short-latency (1-10 ms) echoes through a process known as "the precedence effect" or "echo suppression." In the present study, we employed electroencephalography (EEG) to investigate the neural time course of echo suppression both with and without the aid of coincident visual stimulation in human listeners. We find that echo suppression is a multistage process initialized during the auditory N1 (70-100 ms) and followed by space-specific suppression mechanisms from 150 to 250 ms. Additionally, we find a robust correlate of listeners' spatial perception (i.e., suppressing or not suppressing the echo) over central electrode sites from 300 to 500 ms. Contrary to our hypothesis, vision's powerful contribution to echo suppression occurs late in processing (250-400 ms), suggesting that vision contributes primarily during late sensory or decision making processes. Together, our findings support growing evidence that echo suppression is a slow, progressive mechanism modifiable by visual influences during late sensory and decision making stages. Furthermore, our findings suggest that audiovisual interactions are not limited to early, sensory-level modulations but extend well into late stages of cortical processing.

Regional risk assessment for contaminated sites part 2: ranking of potentially contaminated sites.

PubMed

Pizzol, Lisa; Critto, Andrea; Agostini, Paola; Marcomini, Antonio

2011-11-01

Environmental risks are traditionally assessed and presented in non spatial ways although the heterogeneity of the contaminants spatial distributions, the spatial positions and relations between receptors and stressors, as well as the spatial distribution of the variables involved in the risk assessment, strongly influence exposure estimations and hence risks. Taking into account spatial variability is increasingly being recognized as a further and essential step in sound exposure and risk assessment. To address this issue an innovative methodology which integrates spatial analysis and a relative risk approach was developed. The purpose of this methodology is to prioritize sites at regional scale where a preliminary site investigation may be required. The methodology aimed at supporting the inventory of contaminated sites was implemented within the spatial decision support sYstem for Regional rIsk Assessment of DEgraded land, SYRIADE, and was applied to the case-study of the Upper Silesia region (Poland). The developed methodology and tool are both flexible and easy to adapt to different regional contexts, allowing the user to introduce the regional relevant parameters identified on the basis of user expertise and regional data availability. Moreover, the used GIS functionalities, integrated with mathematical approaches, allow to take into consideration, all at once, the multiplicity of sources and impacted receptors within the region of concern, to assess the risks posed by all contaminated sites in the region and, finally, to provide a risk-based ranking of the potentially contaminated sites. Copyright © 2011. Published by Elsevier Ltd.

Spatial Preference Modelling for equitable infrastructure provision: an application of Sen's Capability Approach

NASA Astrophysics Data System (ADS)

Wismadi, Arif; Zuidgeest, Mark; Brussel, Mark; van Maarseveen, Martin

2014-01-01

To determine whether the inclusion of spatial neighbourhood comparison factors in Preference Modelling allows spatial decision support systems (SDSSs) to better address spatial equity, we introduce Spatial Preference Modelling (SPM). To evaluate the effectiveness of this model in addressing equity, various standardisation functions in both Non-Spatial Preference Modelling and SPM are compared. The evaluation involves applying the model to a resource location-allocation problem for transport infrastructure in the Special Province of Yogyakarta in Indonesia. We apply Amartya Sen's Capability Approach to define opportunity to mobility as a non-income indicator. Using the extended Moran's I interpretation for spatial equity, we evaluate the distribution output regarding, first, `the spatial distribution patterns of priority targeting for allocation' (SPT) and, second, `the effect of new distribution patterns after location-allocation' (ELA). The Moran's I index of the initial map and its comparison with six patterns for SPT as well as ELA consistently indicates that the SPM is more effective for addressing spatial equity. We conclude that the inclusion of spatial neighbourhood comparison factors in Preference Modelling improves the capability of SDSS to address spatial equity. This study thus proposes a new formal method for SDSS with specific attention on resource location-allocation to address spatial equity.

A task-irrelevant stimulus attribute affects perception and short-term memory

PubMed Central

Huang, Jie; Kahana, Michael J.; Sekuler, Robert

2010-01-01

Selective attention protects cognition against intrusions of task-irrelevant stimulus attributes. This protective function was tested in coordinated psychophysical and memory experiments. Stimuli were superimposed, horizontally and vertically oriented gratings of varying spatial frequency; only one orientation was task relevant. Experiment 1 demonstrated that a task-irrelevant spatial frequency interfered with visual discrimination of the task-relevant spatial frequency. Experiment 2 adopted a two-item Sternberg task, using stimuli that had been scaled to neutralize interference at the level of vision. Despite being visually neutralized, the task-irrelevant attribute strongly influenced recognition accuracy and associated reaction times (RTs). This effect was sharply tuned, with the task-irrelevant spatial frequency having an impact only when the task-relevant spatial frequencies of the probe and study items were highly similar to one another. Model-based analyses of judgment accuracy and RT distributional properties converged on the point that the irrelevant orientation operates at an early stage in memory processing, not at a later one that supports decision making. PMID:19933454

Land-use evaluation for sustainable construction in a protected area: A case of Sara mountain national park.

PubMed

Ristić, Vladica; Maksin, Marija; Nenković-Riznić, Marina; Basarić, Jelena

2018-01-15

The process of making decisions on sustainable development and construction begins in spatial and urban planning when defining the suitability of using land for sustainable construction in a protected area (PA) and its immediate and regional surroundings. The aim of this research is to propose and assess a model for evaluating land-use suitability for sustainable construction in a PA and its surroundings. The methodological approach of Multi-Criteria Decision Analysis was used in the formation of this model and adapted for the research; it was combined with the adapted Analytical hierarchy process and the Delphi process, and supported by a geographical information system (GIS) within the framework of ESRI ArcGIS software - Spatial analyst. The model is applied to the case study of Sara mountain National Park in Kosovo. The result of the model is a "map of integrated assessment of land-use suitability for sustainable construction in a PA for the natural factor". Copyright © 2017 Elsevier Ltd. All rights reserved.

Arbitrary numbers counter fair decisions: trails of markedness in card distribution.

PubMed

Schroeder, Philipp A; Pfister, Roland

2015-01-01

Converging evidence from controlled experiments suggests that the mere processing of a number and its attributes such as value or parity might affect free choice decisions between different actions. For example the spatial numerical associations of response codes (SNARC) effect indicates the magnitude of a digit to be associated with a spatial representation and might therefore affect spatial response choices (i.e., decisions between a "left" and a "right" option). At the same time, other (linguistic) features of a number such as parity are embedded into space and might likewise prime left or right responses through feature words [odd or even, respectively; markedness association of response codes (MARC) effect]. In this experiment we aimed at documenting such influences in a natural setting. We therefore assessed number-space and parity-space association effects by exposing participants to a fair distribution task in a card playing scenario. Participants drew cards, read out loud their number values, and announced their response choice, i.e., dealing it to a left vs. right player, indicated by Playmobil characters. Not only did participants prefer to deal more cards to the right player, the card's digits also affected response choices and led to a slightly but systematically unfair distribution, supported by a regular SNARC effect and counteracted by a reversed MARC effect. The experiment demonstrates the impact of SNARC- and MARC-like biases in free choice behavior through verbal and visual numerical information processing even in a setting with high external validity.

GMDPtoolbox: A Matlab library for designing spatial management policies. Application to the long-term collective management of an airborne disease

PubMed Central

Aubertot, Jean-Noël; Peyrard, Nathalie; Sabbadin, Régis

2017-01-01

Designing management policies in ecology and agroecology is complex. Several components must be managed together while they strongly interact spatially. Decision choices must be made under uncertainty on the results of the actions and on the system dynamics. Furthermore, the objectives pursued when managing ecological systems or agroecosystems are usually long term objectives, such as biodiversity conservation or sustainable crop production. The framework of Graph-Based Markov Decision Processes (GMDP) is well adapted to the qualitative modeling of such problems of sequential decision under uncertainty. Spatial interactions are easily modeled and integrated control policies (combining several action levers) can be designed through optimization. The provided policies are adaptive, meaning that management actions are decided at each time step (for instance yearly) and the chosen actions depend on the current system state. This framework has already been successfully applied to forest management and invasive species management. However, up to now, no “easy-to-use” implementation of this framework was available. We present GMDPtoolbox, a Matlab toolbox which can be used both for the design of new management policies and for comparing policies by simulation. We provide an illustration of the use of the toolbox on a realistic crop disease management problem: the design of long term management policy of blackleg of canola using an optimal combination of three possible cultural levers. This example shows how GMDPtoolbox can be used as a tool to support expert thinking. PMID:28982151

GMDPtoolbox: A Matlab library for designing spatial management policies. Application to the long-term collective management of an airborne disease.

PubMed

Cros, Marie-Josée; Aubertot, Jean-Noël; Peyrard, Nathalie; Sabbadin, Régis

2017-01-01

Designing management policies in ecology and agroecology is complex. Several components must be managed together while they strongly interact spatially. Decision choices must be made under uncertainty on the results of the actions and on the system dynamics. Furthermore, the objectives pursued when managing ecological systems or agroecosystems are usually long term objectives, such as biodiversity conservation or sustainable crop production. The framework of Graph-Based Markov Decision Processes (GMDP) is well adapted to the qualitative modeling of such problems of sequential decision under uncertainty. Spatial interactions are easily modeled and integrated control policies (combining several action levers) can be designed through optimization. The provided policies are adaptive, meaning that management actions are decided at each time step (for instance yearly) and the chosen actions depend on the current system state. This framework has already been successfully applied to forest management and invasive species management. However, up to now, no "easy-to-use" implementation of this framework was available. We present GMDPtoolbox, a Matlab toolbox which can be used both for the design of new management policies and for comparing policies by simulation. We provide an illustration of the use of the toolbox on a realistic crop disease management problem: the design of long term management policy of blackleg of canola using an optimal combination of three possible cultural levers. This example shows how GMDPtoolbox can be used as a tool to support expert thinking.

Spatial design principles for sustainable hydropower development in river basins

DOE PAGES

Jager, Henriëtte I.; Efroymson, Rebecca A.; Opperman, Jeff J.; ...

2015-02-27

How can dams be arranged within a river basin such that they benefit society? Recent interest in this question has grown in response to the worldwide trend toward developing hydropower as a source of renewable energy in Asia and South America, and the movement toward removing unnecessary dams in the US. Environmental and energy sustainability are important practical concerns, and yet river development has rarely been planned with the goal of providing society with a portfolio of ecosystem services into the future. We organized a review and synthesis of the growing research in sustainable river basin design around four spatialmore » decisions: Is it better to build fewer mainstem dams or more tributary dams? Should dams be clustered or distributed among distant subbasins? Where should dams be placed along a river? At what spatial scale should decisions be made? We came up with the following design principles for increasing ecological sustainability: (i) concentrate dams within a subset of tributary watersheds and avoid downstream mainstems of rivers, (ii) disperse freshwater reserves among the remaining tributary catchments, (iii) ensure that habitat provided between dams will support reproduction and retain offspring, and (iv) formulate spatial decision problems at the scale of large river basins. Based on our review, we discuss trade-offs between hydropower and ecological objectives when planning river basin development. We hope that future testing and refinement of principles extracted from our review will define a path toward sustainable river basin design.« less

A decision support tool for setting population objectives for priority landbirds in the Central Hardwoods and West Gulf Coastal Plain/Quachitas Bird Conservation Regions

Treesearch

D. Todd Jones-Farrand; John M. Tirpak; Frank R. Thompson; Daniel J. Twedt; Charles K. Baxter; Jane A. Fitzgerald; William B. Uihlein

2009-01-01

Setting and achieving population objectives for priority landbirds must be informed by, 1) the quantity, quality, and spatial confi guration of available habitat, 2) an explicit linkage between habitat condition and population response, and 3) expected future habitat conditions. Based on this philosophy, the Central Hardwoods and Lower Mississippi Valley Joint Ventures...

Gbm.auto: A software tool to simplify spatial modelling and Marine Protected Area planning

PubMed Central

Officer, Rick; Clarke, Maurice; Reid, David G.; Brophy, Deirdre

2017-01-01

Boosted Regression Trees. Excellent for data-poor spatial management but hard to use Marine resource managers and scientists often advocate spatial approaches to manage data-poor species. Existing spatial prediction and management techniques are either insufficiently robust, struggle with sparse input data, or make suboptimal use of multiple explanatory variables. Boosted Regression Trees feature excellent performance and are well suited to modelling the distribution of data-limited species, but are extremely complicated and time-consuming to learn and use, hindering access for a wide potential user base and therefore limiting uptake and usage. BRTs automated and simplified for accessible general use with rich feature set We have built a software suite in R which integrates pre-existing functions with new tailor-made functions to automate the processing and predictive mapping of species abundance data: by automating and greatly simplifying Boosted Regression Tree spatial modelling, the gbm.auto R package suite makes this powerful statistical modelling technique more accessible to potential users in the ecological and modelling communities. The package and its documentation allow the user to generate maps of predicted abundance, visualise the representativeness of those abundance maps and to plot the relative influence of explanatory variables and their relationship to the response variables. Databases of the processed model objects and a report explaining all the steps taken within the model are also generated. The package includes a previously unavailable Decision Support Tool which combines estimated escapement biomass (the percentage of an exploited population which must be retained each year to conserve it) with the predicted abundance maps to generate maps showing the location and size of habitat that should be protected to conserve the target stocks (candidate MPAs), based on stakeholder priorities, such as the minimisation of fishing effort displacement. Gbm.auto for management in various settings By bridging the gap between advanced statistical methods for species distribution modelling and conservation science, management and policy, these tools can allow improved spatial abundance predictions, and therefore better management, decision-making, and conservation. Although this package was built to support spatial management of a data-limited marine elasmobranch fishery, it should be equally applicable to spatial abundance modelling, area protection, and stakeholder engagement in various scenarios. PMID:29216310

Needs Assessment for the Use of NASA Remote Sensing Data in the Development and Implementation of Estuarine and Coastal Water Quality Standards

NASA Technical Reports Server (NTRS)

Spiering, Bruce; Underwood, Lauren; Ellis, Chris; Lehrter, John; Hagy, Jim; Schaeffer, Blake

2010-01-01

The goals of the project are to provide information from satellite remote sensing to support numeric nutrient criteria development and to determine data processing methods and data quality requirements to support nutrient criteria development and implementation. The approach is to identify water quality indicators that are used by decision makers to assess water quality and that are related to optical properties of the water; to develop remotely sensed data products based on algorithms relating remote sensing imagery to field-based observations of indicator values; to develop methods to assess estuarine water quality, including trends, spatial and temporal variability, and seasonality; and to develop tools to assist in the development and implementation of estuarine and coastal nutrient criteria. Additional slides present process, criteria development, typical data sources and analyses for criteria process, the power of remote sensing data for the process, examples from Pensacola Bay, spatial and temporal variability, pixel matchups, remote sensing validation, remote sensing in coastal waters, requirements for remotely sensed data products, and needs assessment. An additional presentation examines group engagement and information collection. Topics include needs assessment purpose and objectives, understanding water quality decision making, determining information requirements, and next steps.

Analysing urban resilience through alternative stormwater management options: application of the conceptual Spatial Decision Support System model at the neighbourhood scale.

PubMed

Balsells, M; Barroca, B; Amdal, J R; Diab, Y; Becue, V; Serre, D

2013-01-01

Recent changes in cities and their environments, caused by rapid urbanisation and climate change, have increased both flood probability and the severity of flooding. Consequently, there is a need for all cities to adapt to climate and socio-economic changes by developing new strategies for flood risk management. Following a risk paradigm shift from traditional to more integrated approaches, and considering the uncertainties of future urban development, one of the main emerging tasks for city managers becomes the development of resilient cities. However, the meaning of the resilience concept and its operability is still not clear. The goal of this research is to study how urban engineering and design disciplines can improve resilience to floods in urban neighbourhoods. This paper presents the conceptual Spatial Decision Support System (DS3) model which we consider a relevant tool to analyse and then implement resilience into neighbourhood design. Using this model, we analyse and discuss alternative stormwater management options at the neighbourhood scale in two specific areas: Rotterdam and New Orleans. The results obtained demonstrate that the DS3 model confirmed in its framework analysis that stormwater management systems can positively contribute to the improved flood resilience of a neighbourhood.

Web-GIS-based SARS epidemic situation visualization

NASA Astrophysics Data System (ADS)

Lu, Xiaolin

2004-03-01

In order to research, perform statistical analysis and broadcast the information of SARS epidemic situation according to the relevant spatial position, this paper proposed a unified global visualization information platform for SARS epidemic situation based on Web-GIS and scientific virtualization technology. To setup the unified global visual information platform, the architecture of Web-GIS based interoperable information system is adopted to enable public report SARS virus information to health cure center visually by using the web visualization technology. A GIS java applet is used to visualize the relationship between spatial graphical data and virus distribution, and other web based graphics figures such as curves, bars, maps and multi-dimensional figures are used to visualize the relationship between SARS virus tendency with time, patient number or locations. The platform is designed to display the SARS information in real time, simulate visually for real epidemic situation and offer an analyzing tools for health department and the policy-making government department to support the decision-making for preventing against the SARS epidemic virus. It could be used to analyze the virus condition through visualized graphics interface, isolate the areas of virus source, and control the virus condition within shortest time. It could be applied to the visualization field of SARS preventing systems for SARS information broadcasting, data management, statistical analysis, and decision supporting.

A Spatially-Explicit Technique for Evaluation of Alternative ...

EPA Pesticide Factsheets

Ecosystems contribute to maintaining human well-being directly through provision of goods and indirectly through provision of services that support clean water, clean air, flood protection and atmospheric stability. Transparently accounting for biophysical attributes from which humans derive benefit is essential to support dialog among the public, resource managers, decision makers, and scientists. We analyzed the potential ecosystem goods and services production from alternative future land use scenarios in the US Tampa Bay region. Ecosystem goods and service metrics included carbon sequestration, nitrogen removal, air pollutant removal, and stormwater retention. Each scenario was compared to a 2006 baseline land use. Estimated production of denitrification services changed by 28% and carbon sequestration by 20% between 2006 and the “business as usual” scenario. An alternative scenario focused on “natural resource protection” resulted in an estimated 9% loss in air pollution removal. Stormwater retention was estimated to change 18% from 2006 to 2060 projections. Cost effective areas for conservation, almost 1588 ha, beyond current conservation lands, were identified by comparing ecosystem goods and services production to assessed land values. Our ecosystem goods and services approach provides a simple and quantitative way to examine a more complete set of potential outcomes from land use decisions. This study demonstrates an approach for spatially expli

GLIMPSE: A decision support tool for simultaneously achieving our air quality management and climate change mitigation goals

NASA Astrophysics Data System (ADS)

Pinder, R. W.; Akhtar, F.; Loughlin, D. H.; Henze, D. K.; Bowman, K. W.

2012-12-01

Poor air quality, ecosystem damages, and climate change all are caused by the combustion of fossil fuels, yet environmental management often addresses each of these challenges separately. This can lead to sub-optimal strategies and unintended consequences. Here we present GLIMPSE -- a decision support tool for simultaneously achieving our air quality and climate change mitigation goals. GLIMPSE comprises of two types of models, (i) the adjoint of the GEOS-Chem chemical transport model, to calculate the relationship between emissions and impacts at high spatial resolution, and (ii) the MARKAL energy system model, to calculate the relationship between energy technologies and emissions. This presentation will demonstrate how GLIMPSE can be used to explore energy scenarios to better achieve both improved air quality and mitigate climate change. Second, this presentation will discuss how space-based observations can be incorporated into GLIMPSE to improve decision-making. NASA satellite products, namely ozone radiative forcing from the Tropospheric Emission Spectrometer (TES), are used to extend GLIMPSE to include the impact of emissions on ozone radiative forcing. This provides a much needed observational constraint on ozone radiative forcing.

A spatial decision support system (SDSS) for sustainable tourism planning in Cameron Highlands, Malaysia

NASA Astrophysics Data System (ADS)

Aminu, M.; Matori, A. N.; Yusof, K. W.

2014-02-01

The study describes a methodological approach based on an integrated use of Geographic Information System (GIS) and Analytic Network Process (ANP) of Multi Criteria Evaluation (MCE) to determine nature conservation and tourism development priorities among the highland areas. A set of criteria and indicators were defined to evaluate the highlands biodiversity conservation and tourism development. Pair wise comparison technique was used in order to support solution of a decision problem by evaluating possible alternatives from different perspectives. After the weights have been derived from the pairwise comparison technique, the next step was to compute the unweighted supermatrix, weighted supermatrix and the limit matrix. The limit matrix was normalized to obtain the priorities and the results transferred into GIS environment. Elements evaluated and ranked were represented by criterion maps. Map layers reflecting the opinion of different experts involved were summed using the weighted overlay approach of GIS. Subsequently sustainable tourism development scenarios were generated. The generation of scenarios highlighted the critical issues of the decision problem because it allows one to gradually narrow down a problem.

Spatial Bayesian belief networks as a planning decision tool for mapping ecosystem services trade-offs on forested landscapes.

PubMed

Gonzalez-Redin, Julen; Luque, Sandra; Poggio, Laura; Smith, Ron; Gimona, Alessandro

2016-01-01

An integrated methodology, based on linking Bayesian belief networks (BBN) with GIS, is proposed for combining available evidence to help forest managers evaluate implications and trade-offs between forest production and conservation measures to preserve biodiversity in forested habitats. A Bayesian belief network is a probabilistic graphical model that represents variables and their dependencies through specifying probabilistic relationships. In spatially explicit decision problems where it is difficult to choose appropriate combinations of interventions, the proposed integration of a BBN with GIS helped to facilitate shared understanding of the human-landscape relationships, while fostering collective management that can be incorporated into landscape planning processes. Trades-offs become more and more relevant in these landscape contexts where the participation of many and varied stakeholder groups is indispensable. With these challenges in mind, our integrated approach incorporates GIS-based data with expert knowledge to consider two different land use interests - biodiversity value for conservation and timber production potential - with the focus on a complex mountain landscape in the French Alps. The spatial models produced provided different alternatives of suitable sites that can be used by policy makers in order to support conservation priorities while addressing management options. The approach provided provide a common reasoning language among different experts from different backgrounds while helped to identify spatially explicit conflictive areas. Copyright © 2015 Elsevier Inc. All rights reserved.

Tethys: A Platform for Water Resources Modeling and Decision Support Apps

NASA Astrophysics Data System (ADS)

Swain, N. R.; Christensen, S. D.; Jones, N.; Nelson, E. J.

2014-12-01

Cloud-based applications or apps are a promising medium through which water resources models and data can be conveyed in a user-friendly environment—making them more accessible to decision-makers and stakeholders. In the context of this work, a water resources web app is a web application that exposes limited modeling functionality for a scenario exploration activity in a structured workflow (e.g.: land use change runoff analysis, snowmelt runoff prediction, and flood potential analysis). The technical expertise required to develop water resources web apps can be a barrier to many potential developers of water resources apps. One challenge that developers face is in providing spatial storage, analysis, and visualization for the spatial data that is inherent to water resources models. The software projects that provide this functionality are non-standard to web development and there are a large number of free and open source software (FOSS) projects to choose from. In addition, it is often required to synthesize several software projects to provide all of the needed functionality. Another challenge for the developer will be orchestrating the use of several software components. Consequently, the initial software development investment required to deploy an effective water resources cloud-based application can be substantial. The Tethys Platform has been developed to lower the technical barrier and minimize the initial development investment that prohibits many scientists and engineers from making use of the web app medium. Tethys synthesizes several software projects including PostGIS for spatial storage, 52°North WPS for spatial analysis, GeoServer for spatial publishing, Google Earth™, Google Maps™ and OpenLayers for spatial visualization, and Highcharts for plotting tabular data. The software selection came after a literature review of software projects being used to create existing earth sciences web apps. All of the software is linked via a Python-powered software development kit (SDK). Tethys developers use the SDK to build their apps and incorporate the needed functionality from the software suite. The presentation will include several apps that have been developed using Tethys to demonstrate its capabilities. Based upon work supported by the National Science Foundation under Grant No. 1135483.

An Ecosystem Service Evaluation Tool to Support Ridge-to-Reef Management and Conservation in Hawaii

NASA Astrophysics Data System (ADS)

Oleson, K.; Callender, T.; Delevaux, J. M. S.; Falinski, K. A.; Htun, H.; Jin, G.

2014-12-01

Faced with increasing anthropogenic stressors and diverse stakeholders, local managers are adopting a ridge-to-reef and multi-objective management approach to restore declining coral reef health state. An ecosystem services framework, which integrates ecological indicators and stakeholder values, can foster more applied and integrated research, data collection, and modeling, and thus better inform the decision-making process and realize decision outcomes grounded in stakeholders' values. Here, we describe a research program that (i) leverages remotely sensed and empirical data to build an ecosystem services-based decision-support tool geared towards ridge-to-reef management; and (ii) applies it as part of a structured, value-based decision-making process to inform management in west Maui, a NOAA coral reef conservation priority site. The tool links terrestrial and marine biophysical models in a spatially explicit manner to quantify and map changes in ecosystem services delivery resulting from management actions, projected climate change impacts, and adaptive responses. We couple model outputs with localized valuation studies to translate ecosystem service outcomes into benefits and their associated socio-cultural and/or economic values. Managers can use this tool to run scenarios during their deliberations to evaluate trade-offs, cost-effectiveness, and equity implications of proposed policies. Ultimately, this research program aims at improving the effectiveness, efficiency, and equity outcomes of ecosystem-based management. This presentation will describe our approach, summarize initial results from the terrestrial modeling and economic valuations for west Maui, and highlight how this decision support tool benefits managers in west Maui.

Predicting Fire Severity and Hydrogeomorphic Effects for Wildland Fire Decision Support

NASA Astrophysics Data System (ADS)

Hyde, K.; Woods, S. W.; Calkin, D.; Ryan, K.; Keane, R.

2007-12-01

The Wildland Fire Decision Support System (WFDSS) uses the Fire Spread Probability (FSPro) model to predict the spatial extent of fire, and to assess values-at-risk within probable spread zones. This information is used to support Appropriate Management Response (AMR), which involves decision making regarding fire-fighter deployment, fire suppression requirements, and identification of areas where fire may be safely permitted to take its course. Current WFDSS assessments are generally limited to a binary prediction of whether or not a fire will reach a given location and an assessment of the infrastructure which may be damaged or destroyed by fire. However, an emerging challenge is to expand the capabilities of WFDSS so that it also estimates the probable fire severity, and hence the effect on soil, vegetation and on hydrologic and geomorphic processes such as runoff and soil erosion. We present a conceptual framework within which derivatives of predictive fire modelling are used to predict impacts upon vegetation and soil, from which fire severity and probable post-fire watershed response can be inferred, before a fire actually occurs. Fire severity predictions are validated using Burned Area Reflectance Classification imagery. Recent tests indicate that satellite derived BARC images are a simple and effective means to predict post-fire erosion response based on relative vegetation disturbance. A fire severity prediction which reasonably approximates a BARC image may therefore be used to assess post-fire erosion and flood potential before fire reaches an area. This information may provide a new avenue of reliable support for fire management decisions.

Spatial memory in foraging games.

PubMed

Kerster, Bryan E; Rhodes, Theo; Kello, Christopher T

2016-03-01

Foraging and foraging-like processes are found in spatial navigation, memory, visual search, and many other search functions in human cognition and behavior. Foraging is commonly theorized using either random or correlated movements based on Lévy walks, or a series of decisions to remain or leave proximal areas known as "patches". Neither class of model makes use of spatial memory, but search performance may be enhanced when information about searched and unsearched locations is encoded. A video game was developed to test the role of human spatial memory in a canonical foraging task. Analyses of search trajectories from over 2000 human players yielded evidence that foraging movements were inherently clustered, and that clustering was facilitated by spatial memory cues and influenced by memory for spatial locations of targets found. A simple foraging model is presented in which spatial memory is used to integrate aspects of Lévy-based and patch-based foraging theories to perform a kind of area-restricted search, and thereby enhance performance as search unfolds. Using only two free parameters, the model accounts for a variety of findings that individually support competing theories, but together they argue for the integration of spatial memory into theories of foraging. Copyright © 2015 Elsevier B.V. All rights reserved.

What aspects of vision facilitate haptic processing?

PubMed

Millar, Susanna; Al-Attar, Zainab

2005-12-01

We investigate how vision affects haptic performance when task-relevant visual cues are reduced or excluded. The task was to remember the spatial location of six landmarks that were explored by touch in a tactile map. Here, we use specially designed spectacles that simulate residual peripheral vision, tunnel vision, diffuse light perception, and total blindness. Results for target locations differed, suggesting additional effects from adjacent touch cues. These are discussed. Touch with full vision was most accurate, as expected. Peripheral and tunnel vision, which reduce visuo-spatial cues, differed in error pattern. Both were less accurate than full vision, and significantly more accurate than touch with diffuse light perception, and touch alone. The important finding was that touch with diffuse light perception, which excludes spatial cues, did not differ from touch without vision in performance accuracy, nor in location error pattern. The contrast between spatially relevant versus spatially irrelevant vision provides new, rather decisive, evidence against the hypothesis that vision affects haptic processing even if it does not add task-relevant information. The results support optimal integration theories, and suggest that spatial and non-spatial aspects of vision need explicit distinction in bimodal studies and theories of spatial integration.

A Web-Based Decision Support System for Assessing Regional Water-Quality Conditions and Management Actions

NASA Astrophysics Data System (ADS)

Booth, N. L.; Everman, E.; Kuo, I.; Sprague, L.; Murphy, L.

2011-12-01

A new web-based decision support system has been developed as part of the U.S. Geological Survey (USGS) National Water Quality Assessment Program's (NAWQA) effort to provide ready access to Spatially Referenced Regressions On Watershed attributes (SPARROW) results of stream water-quality conditions and to offer sophisticated scenario testing capabilities for research and water-quality planning via an intuitive graphical user interface with a map-based display. The SPARROW Decision Support System (DSS) is delivered through a web browser over an Internet connection, making it widely accessible to the public in a format that allows users to easily display water-quality conditions, distribution of nutrient sources, nutrient delivery to downstream waterbodies, and simulations of altered nutrient inputs including atmospheric and agricultural sources. The DSS offers other features for analysis including various background map layers, model output exports, and the ability to save and share prediction scenarios. SPARROW models currently supported by the DSS are based on the modified digital versions of the 1:500,000-scale River Reach File (RF1) and 1:100,000-scale National Hydrography Dataset (medium-resolution, NHDPlus) stream networks. The underlying modeling framework and server infrastructure illustrate innovations in the information technology and geosciences fields for delivering SPARROW model predictions over the web by performing intensive model computations and map visualizations of the predicted conditions within the stream network.

A Web-Based Decision Support System for Assessing Regional Water-Quality Conditions and Management Actions

USGS Publications Warehouse

Booth, N.L.; Everman, E.J.; Kuo, I.-L.; Sprague, L.; Murphy, L.

2011-01-01

The U.S. Geological Survey National Water Quality Assessment Program has completed a number of water-quality prediction models for nitrogen and phosphorus for the conterminous United States as well as for regional areas of the nation. In addition to estimating water-quality conditions at unmonitored streams, the calibrated SPAtially Referenced Regressions On Watershed attributes (SPARROW) models can be used to produce estimates of yield, flow-weighted concentration, or load of constituents in water under various land-use condition, change, or resource management scenarios. A web-based decision support infrastructure has been developed to provide access to SPARROW simulation results on stream water-quality conditions and to offer sophisticated scenario testing capabilities for research and water-quality planning via a graphical user interface with familiar controls. The SPARROW decision support system (DSS) is delivered through a web browser over an Internet connection, making it widely accessible to the public in a format that allows users to easily display water-quality conditions and to describe, test, and share modeled scenarios of future conditions. SPARROW models currently supported by the DSS are based on the modified digital versions of the 1:500,000-scale River Reach File (RF1) and 1:100,000-scale National Hydrography Dataset (medium-resolution, NHDPlus) stream networks. ?? 2011 American Water Resources Association. This article is a U.S. Government work and is in the public domain in the USA.

Spatial education: improving conservation delivery through space-structured decision making

USGS Publications Warehouse

Moore, Clinton T.; Shaffer, Terry L.; Gannon, Jill J.

2013-01-01

Adaptive management is a form of structured decision making designed to guide management of natural resource systems when their behaviors are uncertain. Where decision making can be replicated across units of a landscape, learning can be accelerated, and biological processes can be understood in a larger spatial context. Broad-based partnerships among land management agencies, exemplified by Landscape Conservation Cooperatives (conservation partnerships created through the U.S. Department of the Interior), are potentially ideal environments for implementing spatially structured adaptive management programs.

Spatial distribution and assessment of nutrient pollution in Lake Toba using 2D-multi layers hydrodynamic model and DPSIR framework

NASA Astrophysics Data System (ADS)

Sunaryani, A.; Harsono, E.; Rustini, H. A.; Nomosatryo, S.

2018-02-01

Lake Toba is the largest lake in Indonesia utilized as a source of life-support for drinking and clean water, energy sources, aquaculture and tourism. Nowadays the water quality in Lake Toba has decreased due to the presence of excessive nutrient (nitrogen: N and phosphorus: P). This study aims to describe the spatial distribution of nutrient pollution and to develop a decision support tool for the identification and evaluation of nutrient pollution control in Lake Toba. Spatial distribution method was conducted by 2D-multi layers hydrodynamic model, while DPSIR Framework is used as a tool for the assessment. The results showed that the concentration of nutrient was low and tended to increase along the water depth, but nutrient concentration in aquaculture zones was very high and the trophic state index has reached eutrophic state. The principal anthropogenic driving forces were population growth and the development of aquaculture, livestock, agriculture, and tourism. The main environmental pressures showed that aquaculture and livestock waste are the most important nutrient sources (93% of N and 87% of P loads). State analysis showed that high nutrient concentration and increased algal growth lead to oxygen depletion. The impacts of these conditions were massive fish kills, loss of amenities and tourism value, also decreased usability of clean water supply. This study can be a useful information for decision-makers to evaluate nutrient pollution control. Nutrient pollution issue in Lake Toba requires the attention of local government and public society to maintain its sustainability.

GIS-based Landing-Site Analysis and Passive Decision Support

NASA Astrophysics Data System (ADS)

van Gasselt, Stephan; Nass, Andrea

2016-04-01

The increase of surface coverage and the availability and accessibility of planetary data allow researchers and engineers to remotely perform detailed studies on surface processes and properties, in particular on objects such as Mars and the Moon for which Terabytes of multi-temporal data at multiple spatial resolution levels have become available during the last 15 years. Orbiters, rovers and landers have been returning information and insights into the surface evolution of the terrestrial planets in unprecedented detail. While rover- and lander-based analyses are one major research aim to obtain ground truth, resource exploration or even potential establishment of bases using autonomous platforms are others and they require detailed investigation of settings in order to identify spots on the surface that are suitable for spacecraft to land and operate safely and over a long period of time. What has been done using hardcopy material in the past is today being carried by using either in-house developments or off-the-shelf spatial information system technology which allows to manage, integrate and analyse data as well as visualize and create user-defined reports for performing assessments. Usually, such analyses can be broken down (manually) by considering scientific wishes, engineering boundary conditions, potential hazards and various tertiary constraints. We here (1) review standard tasks of landing site analyses, (2) discuss issues inherently related to the analysis using integrated spatial analysis systems and (3) demonstrate a modular analysis framework for integration of data and for the evaluation of results from individual tasks in order to support decisions for landing-site selection.

A National Crop Progress Monitoring and Decision Support System Based on NASA Earth Science Results

NASA Astrophysics Data System (ADS)

di, L.; Yang, Z.

2009-12-01

Timely and accurate information on weekly crop progress and development is essential to a dynamic agricultural industry in the U. S. and the world. By law, the National Agricultural Statistics Service (NASS) of the U. S. Department of Agriculture’s (USDA) is responsible for monitoring and assessing U.S. agricultural production. Currently NASS compiles and issues weekly state and national crop progress and development reports based on reports from knowledgeable state and county agricultural officials and farmers. Such survey-based reports are subjectively estimated for an entire county, lack spatial coverage, and are labor intensive. There has been limited use of remote sensing data to assess crop conditions. NASS produces weekly 1-km resolution un-calibrated AVHRR-based NDVI static images to represent national vegetation conditions but there is no quantitative crop progress information. This presentation discusses the early result for developing a National Crop Progress Monitoring and Decision Support System. The system will overcome the shortcomings of the existing systems by integrating NASA satellite and model-based land surface and weather products, NASS’ wealth of internal crop progress and condition data and Cropland Data Layers (CDL), and the Farm Service Agency’s (FSA) Common Land Units (CLU). The system, using service-oriented architecture and web service technologies, will automatically produce and disseminate quantitative national crop progress maps and associated decision support data at 250-m resolution, as well as summary reports to support NASS and worldwide users in their decision-making. It will provide overall and specific crop progress for individual crops from the state level down to CLU field level to meet different users’ needs on all known croplands. This will greatly enhance the effectiveness and accuracy of the NASS aggregated crop condition data and charts of and provides objective and scientific evidence and guidance for the adjustment of NASS survey data. This presentation will discuss the architecture, Earth observation data, and the crop progress model used in the decision support system.

Combining ecosystem services assessment with structured decision making to support ecological restoration planning.

PubMed

Martin, David M; Mazzotta, Marisa; Bousquin, Justin

2018-04-10

Accounting for ecosystem services in environmental decision making is an emerging research topic. Modern frameworks for ecosystem services assessment emphasize evaluating the social benefits of ecosystems, in terms of who benefits and by how much, to aid in comparing multiple courses of action. Structured methods that use decision analytic-approaches are emerging for the practice of ecological restoration. In this article, we combine ecosystem services assessment with structured decision making to estimate and evaluate measures of the potential benefits of ecological restoration with a case study in the Woonasquatucket River watershed, Rhode Island, USA. We partnered with a local watershed management organization to analyze dozens of candidate wetland restoration sites for their abilities to supply five ecosystem services-flood water retention, scenic landscapes, learning opportunities, recreational opportunities, and birds. We developed 22 benefit indicators related to the ecosystem services as well as indicators for social equity and reliability that benefits will sustain in the future. We applied conceptual modeling and spatial analysis to estimate indicator values for each candidate restoration site. Lastly, we developed a decision support tool to score and aggregate the values for the organization to screen the restoration sites. Results show that restoration sites in urban areas can provide greater social benefits than sites in less urban areas. Our research approach is general and can be used to investigate other restoration planning studies that perform ecosystem services assessment and fit into a decision-making process.

Analysis of spatial distribution and transmission characters for highly pathogenic avian influenza in Chinese mainland in 2004

NASA Astrophysics Data System (ADS)

Liu, Y. L.; Wei, C. J.; Yan, L.; Chi, T. H.; Wu, X. B.; Xiao, C. S.

2006-03-01

After the outbreak of highly pathogenic Avian Influenza (HPAI) in South Korea in the end of year 2003, estimates of the impact of HPAI in affected countries vary greatly, the total direct losses are about 3 billion US dollars, and it caused 15 million birds and poultry flocks death. It is significant to understand the spatial distribution and transmission characters of HPAI for its prevention and control. According to 50 outbreak cases for HPAI in Chinese mainland during 2004, this paper introduces the approach of spatial distribution and transmission characters for HPAI and its results. Its approach is based on remote sensing and GIS techniques. Its supporting data set involves normalized difference vegetation index (NDVI) and land surface temperature (Ts) derived from a time-series of remote sensing data of 1 kilometer-resolution NOAA/AVHRR, birds' migration routes, topology geographic map, lake and wetland maps, and meteorological observation data. In order to analyze synthetically using these data, a supporting platform for analysis Avian Influenza epidemic situation (SPAS/AI) was developed. Supporting by SPAS/AI, the integrated information from multi-sources can be easily used to the analysis of the spatial distribution and transmission character of HPAI. The results show that the range of spatial distribution and transmission of HPAI in China during 2004 connected to environment factors NDVI, Ts and the distributions of lake and wetland, and especially to bird migration routes. To some extent, the results provide some suggestions for the macro-decision making for the prevention and control of HPAI in the areas of potential risk and reoccurrence.

Air Quality Response Modeling for Decision Support | Science ...

EPA Pesticide Factsheets

Air quality management relies on photochemical models to predict the responses of pollutant concentrations to changes in emissions. Such modeling is especially important for secondary pollutants such as ozone and fine particulate matter which vary nonlinearly with changes in emissions. Numerous techniques for probing pollutant-emission relationships within photochemical models have been developed and deployed for a variety of decision support applications. However, atmospheric response modeling remains complicated by the challenge of validating sensitivity results against observable data. This manuscript reviews the state of the science of atmospheric response modeling as well as efforts to characterize the accuracy and uncertainty of sensitivity results. The National Exposure Research Laboratory′s (NERL′s) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA′s mission to protect human health and the environment. AMAD′s research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the Nation′s air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being use

Improved Hydrological Decision Support System for the Lower Mekong River Basin Using Satellite-Based Earth Observations.

PubMed

Mohammed, Ibrahim Nourein; Bolten, John D; Srinivasan, Raghavan; Lakshmi, Venkat

2018-06-01

Multiple satellite-based earth observations and traditional station data along with the Soil & Water Assessment Tool (SWAT) hydrologic model were employed to enhance the Lower Mekong River Basin region's hydrological decision support system. A nearest neighbor approximation methodology was introduced to fill the Integrated Multi-satellite Retrieval for the Global Precipitation Measurement mission (IMERG) grid points from 2001 to 2014, together with the Tropical Rainfall Measurement Mission (TRMM) data points for continuous precipitation forcing for our hydrological decision support system. A software tool to access and format satellite-based earth observation systems of precipitation and minimum and maximum air temperatures was developed and is presented. Our results suggest that the model-simulated streamflow utilizing TRMM and IMERG forcing data was able to capture the variability of the observed streamflow patterns in the Lower Mekong better than model-simulated streamflow with in-situ precipitation station data. We also present satellite-based and in-situ precipitation adjustment maps that can serve to correct precipitation data for the Lower Mekong region for use in other applications. The inconsistency, scarcity, poor spatial representation, difficult access and incompleteness of the available in-situ precipitation data for the Mekong region make it imperative to adopt satellite-based earth observations to pursue hydrologic modeling.

Improved Hydrological Decision Support System for the Lower Mekong River Basin Using Satellite-Based Earth Observations

PubMed Central

Mohammed, Ibrahim Nourein; Bolten, John D.; Srinivasan, Raghavan; Lakshmi, Venkat

2018-01-01

Multiple satellite-based earth observations and traditional station data along with the Soil & Water Assessment Tool (SWAT) hydrologic model were employed to enhance the Lower Mekong River Basin region’s hydrological decision support system. A nearest neighbor approximation methodology was introduced to fill the Integrated Multi-satellite Retrieval for the Global Precipitation Measurement mission (IMERG) grid points from 2001 to 2014, together with the Tropical Rainfall Measurement Mission (TRMM) data points for continuous precipitation forcing for our hydrological decision support system. A software tool to access and format satellite-based earth observation systems of precipitation and minimum and maximum air temperatures was developed and is presented. Our results suggest that the model-simulated streamflow utilizing TRMM and IMERG forcing data was able to capture the variability of the observed streamflow patterns in the Lower Mekong better than model-simulated streamflow with in-situ precipitation station data. We also present satellite-based and in-situ precipitation adjustment maps that can serve to correct precipitation data for the Lower Mekong region for use in other applications. The inconsistency, scarcity, poor spatial representation, difficult access and incompleteness of the available in-situ precipitation data for the Mekong region make it imperative to adopt satellite-based earth observations to pursue hydrologic modeling. PMID:29938116

Global Operational Remotely Sensed Evapotranspiration System for Water Resources Management: Case Study for the State of New Mexico

NASA Astrophysics Data System (ADS)

Halverson, G. H.; Fisher, J.; Magnuson, M.; John, L.

2017-12-01

An operational system to produce and disseminate remotely sensed evapotranspiration using the PT-JPL model and support its analysis and use in water resources decision making is being integrated into the New Mexico state government. A partnership between the NASA Western Water Applications Office (WWAO), the Jet Propulsion Laboratory (JPL), and the New Mexico Office of the State Engineer (NMOSE) has enabled collaboration with a variety of state agencies to inform decision making processes for agriculture, rangeland, and forest management. This system improves drought understanding and mobilization, litigation support, and economic, municipal, and ground-water planning through interactive mapping of daily rates of evapotranspiration at 1 km spatial resolution with near real-time latency. This is facilitated by daily remote sensing acquisitions of land-surface temperature and near-surface air temperature and humidity from the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument on the Terra satellite as well as the short-term composites of Normalized Difference Vegetation Index (NDVI) and albedo provided by MODIS. Incorporating evapotranspiration data into agricultural water management better characterizes imbalances between water requirements and supplies. Monitoring evapotranspiration over rangeland areas improves remediation and prevention of aridification. Monitoring forest evapotranspiration improves wildlife management and response to wildfire risk. Continued implementation of this decision support system should enhance water and food security.

Improvements in agricultural water decision support using remote sensing

NASA Astrophysics Data System (ADS)

Marshall, M. T.

2012-12-01

Population driven water scarcity, aggravated by climate-driven evaporative demand in dry regions of the world, has the potential of transforming ecological and social systems to the point of armed conflict. Water shortages will be most severe in agricultural areas, as the priority shifts to urban and industrial use. In order to design, evaluate, and monitor appropriate mitigation strategies, predictive models must be developed that quantify exposure to water shortage. Remote sensing data has been used for more than three decades now to parametrize these models, because field measurements are costly and difficult in remote regions of the world. In the past decade, decision-makers for the first time can make accurate and near real-time evaluations of field conditions with the advent of hyper- spatial and spectral and coarse resolution continuous remote sensing data. Here, we summarize two projects representing diverse applications of remote sensing to improve agricultural water decision support. The first project employs MODIS (coarse resolution continuous data) to drive an evapotranspiration index, which is combined with the Standardized Precipitation Index driven by meteorological satellite data to improve famine early warning in Africa. The combined index is evaluated using district-level crop yield data from Kenya and Malawi and national-level crop yield data from the United Nations Food and Agriculture Organization. The second project utilizes hyper- spatial (GeoEye 1, Quickbird, IKONOS, and RapidEye) and spectral (Hyperion/ALI), as well as multi-spectral (Landsat ETM+, SPOT, and MODIS) data to develop biomass estimates for key crops (alfalfa, corn, cotton, and rice) in the Central Valley of California. Crop biomass is an important indicator of crop water productivity. The remote sensing data is combined using various data fusion techniques and evaluated with field data collected in the summer of 2012. We conclude with a brief discussion on implementation of these tools into two new decision support systems: FEWSNET Early Warning Explorer (http://earlywarning.usgs.gov/fews/ewxindex.php) and the NASA Terrestrial Observation and Prediction System (http://ecocast.arc.nasa.gov/) for the first and second project respectively.

RADSS: an integration of GIS, spatial statistics, and network service for regional data mining

NASA Astrophysics Data System (ADS)

Hu, Haitang; Bao, Shuming; Lin, Hui; Zhu, Qing

2005-10-01

Regional data mining, which aims at the discovery of knowledge about spatial patterns, clusters or association between regions, has widely applications nowadays in social science, such as sociology, economics, epidemiology, crime, and so on. Many applications in the regional or other social sciences are more concerned with the spatial relationship, rather than the precise geographical location. Based on the spatial continuity rule derived from Tobler's first law of geography: observations at two sites tend to be more similar to each other if the sites are close together than if far apart, spatial statistics, as an important means for spatial data mining, allow the users to extract the interesting and useful information like spatial pattern, spatial structure, spatial association, spatial outlier and spatial interaction, from the vast amount of spatial data or non-spatial data. Therefore, by integrating with the spatial statistical methods, the geographical information systems will become more powerful in gaining further insights into the nature of spatial structure of regional system, and help the researchers to be more careful when selecting appropriate models. However, the lack of such tools holds back the application of spatial data analysis techniques and development of new methods and models (e.g., spatio-temporal models). Herein, we make an attempt to develop such an integrated software and apply it into the complex system analysis for the Poyang Lake Basin. This paper presents a framework for integrating GIS, spatial statistics and network service in regional data mining, as well as their implementation. After discussing the spatial statistics methods involved in regional complex system analysis, we introduce RADSS (Regional Analysis and Decision Support System), our new regional data mining tool, by integrating GIS, spatial statistics and network service. RADSS includes the functions of spatial data visualization, exploratory spatial data analysis, and spatial statistics. The tool also includes some fundamental spatial and non-spatial database in regional population and environment, which can be updated by external database via CD or network. Utilizing this data mining and exploratory analytical tool, the users can easily and quickly analyse the huge mount of the interrelated regional data, and better understand the spatial patterns and trends of the regional development, so as to make a credible and scientific decision. Moreover, it can be used as an educational tool for spatial data analysis and environmental studies. In this paper, we also present a case study on Poyang Lake Basin as an application of the tool and spatial data mining in complex environmental studies. At last, several concluding remarks are discussed.

A Spatial Decision Support System to incorporate hydro-economic modeling results in the management of water resources under decentralized institutional arrangements in a semiarid reservoir region in Brazil

NASA Astrophysics Data System (ADS)

Moraes, M. G. A.; Souza da Silva, G.; Siegmund-Schultze, M.

2016-12-01

The integration of economic and hydrological components in models, aimed to support evaluating alternatives of water allocation policies, is promising, though, challenging. Worldwide, these models have been used primarily in academia, and so far seldom by water managers for practical purposes. Ideally, the models should be available through a Decision Support System. The São Francisco River Basin in Northeast of Brazil has around 48% of its area in a semi-arid region. Irrigation and public water supply are the primary water use sectors, along with hydropower utilization. The water for electricity generation is stored in two large reservoirs, built 30 to 50 years ago under the premise of regulating flows for hydropower and controlling floods. Since 20 years, however, the law stipulates the multiple uses paradigm in a participatory and decentralized way. So far, only few rules laid down. Studies revealed that most of the respective institutions still needed to update their routines to the new paradigm.A hydro-economic model was developed and applied in order to determine the economically optimal water allocation of main users in that semiarid reservoir region. In order to make this model available to the decision makers, a minimum required is some form of manipulating data entry and output as well as some graphical interfaces. We propose a Spatial Decision Support System (SDSS) with dedicated hydro-economic modules in a web-based Geographic Information System (GIS) environment for integrated water resource management. The open model platform will include geoprocessing tasks and water user related data management. The hydro-economic geoprocessing will link to generic optimization modeling systems, such as EXCEL Solver, GAMS and MATLAB. The institutions that are deliberating or deciding over water allocation at different scales could use the generated information on potential economic benefits as a transparent basis for discussion. In addition, they can use the SDSS to include constraints into the model in order to account for further objectives, such as preference given to specific uses or timing of uses. This information, and corresponding policies, can foster enhanced economic welfare and sustainable water use, as well as help to solve water use conflicts.

A Spatial Decision Support System to incorporate hydro-economic modeling results in the management of water resources under decentralized institutional arrangements in a semiarid reservoir region in Brazil

NASA Astrophysics Data System (ADS)

Alcoforado de Moraes, Márcia; Silva, Gerald; Siegmund-Schultze, Marianna

2017-04-01

The integration of economic and hydrological components in models, aimed to support evaluating alternatives of water allocation policies, is promising, though, challenging. Worldwide, these models have been used primarily in academia, and so far seldom by water managers for practical purposes. Ideally, the models should be available through a Decision Support System. The São Francisco River Basin in Northeast of Brazil has around 48% of its area in a semi-arid region. Irrigation and public water supply are the primary water use sectors, along with hydropower utilization. The water for electricity generation is stored in two large reservoirs, built 30 to 50 years ago under the premise of regulating flows for hydropower and controlling floods. Since 20 years, however, the law stipulates the multiple uses paradigm in a participatory and decentralized way. So far, only few rules laid down. Studies revealed that most of the respective institutions still needed to update their routines to the new paradigm. A hydro-economic model was developed and applied in order to determine the economically optimal water allocation of main users in that semiarid reservoir region. In order to make this model available to the decision makers, a minimum required is some form of manipulating data entry and output as well as some graphical interfaces. We propose and present the first features of a Spatial Decision Support System (SDSS) with dedicated hydro-economic modules in a web-based Geographic Information System (GIS) environment for integrated water resource management. The open model platform should include geoprocessing tasks and water user related data management. The hydro-economic geoprocessing will link to generic optimization modeling systems, such as EXCEL Solver, GAMS and MATLAB. The institutions are deliberating or deciding over water allocation at different scales could use the generated information on potential economic benefits as a transparent basis for discussion. In addition, they can use the SDSS to include constraints into the model in order to account for further objectives, such as preference given to specific uses or timing of uses. This information, and corresponding policies, can foster enhanced economic welfare and sustainable water use, as well as help to solve water use conflicts.

FlooDSuM - a decision support methodology for assisting local authorities in flood situations

NASA Astrophysics Data System (ADS)

Schwanbeck, Jan; Weingartner, Rolf

2014-05-01

Decision making in flood situations is a difficult task, especially in small to medium-sized mountain catchments (30 - 500 km2) which are usually characterized by complex topography, high drainage density and quick runoff response to rainfall events. Operating hydrological models driven by numerical weather prediction systems, which have a lead-time of several hours up to few even days, would be beneficial in this case as time for prevention could be gained. However, the spatial and quantitative accuracy of such meteorological forecasts usually decrease with increasing lead-time. In addition, the sensitivity of rainfall-runoff models to inaccuracies in estimations of areal rainfall increases with decreasing catchment size. Accordingly, decisions on flood alerts should ideally be based on areal rainfall from high resolution and short-term numerical weather prediction, nowcasts or even real-time measurements, which is transformed into runoff by a hydrological model. In order to benefit from the best possible rainfall data while retaining enough time for alerting and for prevention, the hydrological model should be fast and easily applicable by decision makers within local authorities themselves. The proposed decision support methodology FlooDSuM (Flood Decision Support Methodology) aims to meet those requirements. Applying FlooDSuM, a few successive binary decisions of increasing complexity have to be processed following a flow-chart-like structure. Prepared data and straightforwardly applicable tools are provided for each of these decisions. Maps showing the current flood disposition are used for the first step. While danger of flooding cannot be excluded more and more complex and time consuming methods will be applied. For the final decision, a set of scatter-plots relating areal precipitation to peak flow is provided. These plots take also further decisive parameters into account such as storm duration, distribution of rainfall intensity in time as well as the catchment's antecedent moisture conditions. The proposed approach is currently tested in two catchments in the Swiss Pre-Alps and Alps. We will show the general setup and selected results. The findings of those case studies will lead to further improvements of the proposed approach.

The design and research of poverty alleviation monitoring and evaluation system: a case study in the Jiangxi province

NASA Astrophysics Data System (ADS)

Mo, Hong-yuan; Wang, Ying-jie; Yu, Zhuo-yuan

2009-07-01

The Poverty Alleviation Monitoring and Evaluation System (PAMES) is introduced in this paper. The authors present environment platform selection, and details of system design and realization. Different with traditional research of poverty alleviation, this paper develops a new analytical geo-visualization approach to study the distribution and causes of poverty phenomena within Geographic Information System (GIS). Based on the most detailed poverty population data, the spatial location and population statistical indicators of poverty village in Jiangxi province, the distribution characteristics of poverty population are detailed. The research results can provide much poverty alleviation decision support from a spatial-temporal view. It should be better if the administrative unit of poverty-stricken area to be changed from county to village according to spatial distribution pattern of poverty.

Towards a climate-driven dengue decision support system for Thailand

NASA Astrophysics Data System (ADS)

Lowe, Rachel; Cazelles, Bernard; Paul, Richard; Rodó, Xavier

2014-05-01

Dengue is a peri-urban mosquito-transmitted disease, ubiquitous in the tropics and the subtropics. The geographic distribution of dengue and its more severe form, dengue haemorrhagic fever (DHF), have expanded dramatically in the last decades and dengue is now considered to be the world's most important arboviral disease. Recent demographic changes have greatly contributed to the acceleration and spread of the disease along with uncontrolled urbanization, population growth and increased air travel, which acts as a mechanism for transporting and exchanging dengue viruses between endemic and epidemic populations. The dengue vector and virus are extremely sensitive to environmental conditions such as temperature, humidity and precipitation that influence mosquito biology, abundance and habitat and the virus replication speed. In order to control the spread of dengue and impede epidemics, decision support systems are required that take into account the multi-faceted array of factors that contribute to increased dengue risk. Due to availability of seasonal climate forecasts, that predict the average climate conditions for forthcoming months/seasons in both time and space, there is an opportunity to incorporate precursory climate information in a dengue decision support system to aid epidemic planning months in advance. Furthermore, oceanic indicators from teleconnected areas in the Pacific and Indian Ocean, that can provide some indication of the likely prevailing climate conditions in certain regions, could potentially extend predictive lead time in a dengue early warning system. In this paper we adopt a spatio-temporal Bayesian modelling framework for dengue in Thailand to support public health decision making. Monthly cases of dengue in the 76 provinces of Thailand for the period 1982-2012 are modelled using a multi-layered approach. Environmental explanatory variables at various spatial and temporal resolutions are incorporated into a hierarchical model in order to make spatio-temporal probabilistic predictions of dengue. In order to quantify unknown or unmeasured dengue risk factors, we use spatio-temporal random effects in the model framework. This helps identify those available indicators which could significantly contribute to a dengue early warning system and allows us to quantify the extent to which climate indicators can explain variations in dengue risk. Once accounting for spatial-temporal confounding factors, lagged variables of temperature and precipitation were found to have a statistically significant positive contribution to the relative risk of dengue. Therefore, forecast climate information has potential utility in a dengue decision support system for Thailand. Taking advantage of lead times of several months provided by climate forecasts, public health officials may be able to more efficiently allocate intervention measures, such as targeted vector control activities and provision of medication to deal with more deadly forms of the disease, well ahead of an imminent dengue epidemic.

The Research of Spatial-Temporal Analysis and Decision-Making Assistant System for Disabled Person Affairs Based on Mapworld

NASA Astrophysics Data System (ADS)

Zhang, J. H.; Yang, J.; Sun, Y. S.

2015-06-01

This system combines the Mapworld platform and informationization of disabled person affairs, uses the basic information of disabled person as center frame. Based on the disabled person population database, the affairs management system and the statistical account system, the data were effectively integrated and the united information resource database was built. Though the data analysis and mining, the system provides powerful data support to the decision making, the affairs managing and the public serving. It finally realizes the rationalization, normalization and scientization of disabled person affairs management. It also makes significant contributions to the great-leap-forward development of the informationization of China Disabled Person's Federation.

Policy Implementation Study on Spatial Planning for Environmental Conflict (Study Location: Rembang Regency)

NASA Astrophysics Data System (ADS)

Kusyuniadi, Indraya

2018-02-01

This study aims to see the impact and benefits as an outcome of a policy, where this policy is in the form of spatial planning (Regional Planning). As known RTRW is a product that can be regarded as "the book of development" in every region both in the provincial and regional levels. One of them is as a decision tool for investors (investors) in increasing local development investment, spatial planning (RTRW) is also expected to maintain the environment, in order to support the sustainability of regional development. In reality, there are still many conflicts of interest in the implementation process of regional development, especially between economic and environmental interests. Often the interests of regional sustainability are placed at a lower level (less priority) than investment / economy. Land conversion that is inconsistent with district / city spatial planning RTRW is relatively still occurring, especially for economic purposes. Lack of policy called spatial plan in this case RTRW Province and Regency in responding to existing condition in field. How can a product that is said to be "Scripture" a regional planning is powerless in fulfilling the space for investment in the form of industry, commercial, housing and so forth. There are several results that can be concluded in this study. Basically, the importance of the environment at least can be used as the basis or priority of the main decision makers above economic interests and other politic interests. The current Spatial Plan / RTRW document still holds a big question whether at the time of compilation it follows the norms and rules in a plan (data accuracy, through input process from the community).

The Method of Multiple Spatial Planning Basic Map

NASA Astrophysics Data System (ADS)

Zhang, C.; Fang, C.

2018-04-01

The "Provincial Space Plan Pilot Program" issued in December 2016 pointed out that the existing space management and control information management platforms of various departments were integrated, and a spatial planning information management platform was established to integrate basic data, target indicators, space coordinates, and technical specifications. The planning and preparation will provide supportive decision support, digital monitoring and evaluation of the implementation of the plan, implementation of various types of investment projects and space management and control departments involved in military construction projects in parallel to approve and approve, and improve the efficiency of administrative approval. The space planning system should be set up to delimit the control limits for the development of production, life and ecological space, and the control of use is implemented. On the one hand, it is necessary to clarify the functional orientation between various kinds of planning space. On the other hand, it is necessary to achieve "multi-compliance" of various space planning. Multiple spatial planning intergration need unified and standard basic map(geographic database and technical specificaton) to division of urban, agricultural, ecological three types of space and provide technical support for the refinement of the space control zoning for the relevant planning. The article analysis the main space datum, the land use classification standards, base map planning, planning basic platform main technical problems. Based on the geographic conditions, the results of the census preparation of spatial planning map, and Heilongjiang, Hainan many rules combined with a pilot application.

Building a Lego wall: Sequential action selection.

PubMed

Arnold, Amy; Wing, Alan M; Rotshtein, Pia

2017-05-01

The present study draws together two distinct lines of enquiry into the selection and control of sequential action: motor sequence production and action selection in everyday tasks. Participants were asked to build 2 different Lego walls. The walls were designed to have hierarchical structures with shared and dissociated colors and spatial components. Participants built 1 wall at a time, under low and high load cognitive states. Selection times for correctly completed trials were measured using 3-dimensional motion tracking. The paradigm enabled precise measurement of the timing of actions, while using real objects to create an end product. The experiment demonstrated that action selection was slowed at decision boundary points, relative to boundaries where no between-wall decision was required. Decision points also affected selection time prior to the actual selection window. Dual-task conditions increased selection errors. Errors mostly occurred at boundaries between chunks and especially when these required decisions. The data support hierarchical control of sequenced behavior. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Changes in practice task constraints shape decision-making behaviours of team games players.

PubMed

Correia, Vanda; Araújo, Duarte; Duarte, Ricardo; Travassos, Bruno; Passos, Pedro; Davids, Keith

2012-05-01

This study examined the effects of manipulating relative positioning between defenders (initial distance apart) on emergent decision-making and actions in a 1 vs. 2 rugby union performance sub-phase. Twelve experienced youth players performed 80 trials of a 1 (attacker) vs. 2 (defenders) practice task in which the starting distance between defenders was systematically decreased. Movement displacement trajectories of participants were video recorded to obtain 2D positional data. The independent variable was the starting distance between defenders and dependent variables were: (i) performance outcome (try or tackle), (ii) mean speed of all players during performance, and (iii), time between the first crossover and the end of the trial. Repeated measures ANOVA was used to compare the effects of different starting distances on performance. Shorter starting distances between defenders were associated with a higher frequency of effective tackle outcomes, lower mean speeds of all participants, and a greater time period between the first crossover and the end of the trial. Decision-making behaviours emerged as a function of changes in participants' spatial location during performance. This observation supports the importance of manipulating key spatial-temporal variables in designing representative practice task constraints that induce functional player-environment interactions in team sports training. Copyright © 2011 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

epiDMS: Data Management and Analytics for Decision-Making From Epidemic Spread Simulation Ensembles.

PubMed

Liu, Sicong; Poccia, Silvestro; Candan, K Selçuk; Chowell, Gerardo; Sapino, Maria Luisa

2016-12-01

Carefully calibrated large-scale computational models of epidemic spread represent a powerful tool to support the decision-making process during epidemic emergencies. Epidemic models are being increasingly used for generating forecasts of the spatial-temporal progression of epidemics at different spatial scales and for assessing the likely impact of different intervention strategies. However, the management and analysis of simulation ensembles stemming from large-scale computational models pose challenges, particularly when dealing with multiple interdependent parameters, spanning multiple layers and geospatial frames, affected by complex dynamic processes operating at different resolutions. We describe and illustrate with examples a novel epidemic simulation data management system, epiDMS, that was developed to address the challenges that arise from the need to generate, search, visualize, and analyze, in a scalable manner, large volumes of epidemic simulation ensembles and observations during the progression of an epidemic. epiDMS is a publicly available system that facilitates management and analysis of large epidemic simulation ensembles. epiDMS aims to fill an important hole in decision-making during healthcare emergencies by enabling critical services with significant economic and health impact. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.

The role of the hippocampus in approach-avoidance conflict decision-making: Evidence from rodent and human studies.

PubMed

Ito, Rutsuko; Lee, Andy C H

2016-10-15

The hippocampus (HPC) has been traditionally considered to subserve mnemonic processing and spatial cognition. Over the past decade, however, there has been increasing interest in its contributions to processes beyond these two domains. One question is whether the HPC plays an important role in decision-making under conditions of high approach-avoidance conflict, a scenario that arises when a goal stimulus is simultaneously associated with reward and punishment. This idea has its origins in rodent work conducted in the 1950s and 1960s, and has recently experienced a resurgence of interest in the literature. In this review, we will first provide an overview of classic rodent lesion data that first suggested a role for the HPC in approach-avoidance conflict processing and then proceed to describe a wide range of more recent evidence from studies conducted in rodents and humans. We will demonstrate that there is substantial, converging cross-species evidence to support the idea that the HPC, in particular the ventral (in rodents)/anterior (in humans) portion, contributes to approach-avoidance conflict decision making. Furthermore, we suggest that the seemingly disparate functions of the HPC (e.g. memory, spatial cognition, conflict processing) need not be mutually exclusive. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Exploring complex dynamics in multi agent-based intelligent systems: Theoretical and experimental approaches using the Multi Agent-based Behavioral Economic Landscape (MABEL) model

NASA Astrophysics Data System (ADS)

Alexandridis, Konstantinos T.

This dissertation adopts a holistic and detailed approach to modeling spatially explicit agent-based artificial intelligent systems, using the Multi Agent-based Behavioral Economic Landscape (MABEL) model. The research questions that addresses stem from the need to understand and analyze the real-world patterns and dynamics of land use change from a coupled human-environmental systems perspective. Describes the systemic, mathematical, statistical, socio-economic and spatial dynamics of the MABEL modeling framework, and provides a wide array of cross-disciplinary modeling applications within the research, decision-making and policy domains. Establishes the symbolic properties of the MABEL model as a Markov decision process, analyzes the decision-theoretic utility and optimization attributes of agents towards comprising statistically and spatially optimal policies and actions, and explores the probabilogic character of the agents' decision-making and inference mechanisms via the use of Bayesian belief and decision networks. Develops and describes a Monte Carlo methodology for experimental replications of agent's decisions regarding complex spatial parcel acquisition and learning. Recognizes the gap on spatially-explicit accuracy assessment techniques for complex spatial models, and proposes an ensemble of statistical tools designed to address this problem. Advanced information assessment techniques such as the Receiver-Operator Characteristic curve, the impurity entropy and Gini functions, and the Bayesian classification functions are proposed. The theoretical foundation for modular Bayesian inference in spatially-explicit multi-agent artificial intelligent systems, and the ensembles of cognitive and scenario assessment modular tools build for the MABEL model are provided. Emphasizes the modularity and robustness as valuable qualitative modeling attributes, and examines the role of robust intelligent modeling as a tool for improving policy-decisions related to land use change. Finally, the major contributions to the science are presented along with valuable directions for future research.

Modeling aesthetics to support an ecosystem services approach for natural resource management decision making.

PubMed

Booth, Pieter N; Law, Sheryl A; Ma, Jane; Buonagurio, John; Boyd, James; Turnley, Jessica

2017-09-01

This paper reviews literature on aesthetics and describes the development of vista and landscape aesthetics models. Spatially explicit variables were chosen to represent physical characteristics of natural landscapes that are important to aesthetic preferences. A vista aesthetics model evaluates the aesthetics of natural landscapes viewed from distances of more than 1000 m, and a landscape aesthetics model evaluates the aesthetic value of wetlands and forests within 1000 m from the viewer. Each of the model variables is quantified using spatially explicit metrics on a pixel-specific basis within EcoAIM™, a geographic information system (GIS)-based ecosystem services (ES) decision analysis support tool. Pixel values are "binned" into ranked categories, and weights are assigned to select variables to represent stakeholder preferences. The final aesthetic score is the weighted sum of all variables and is assigned ranked values from 1 to 10. Ranked aesthetic values are displayed on maps by patch type and integrated within EcoAIM. The response of the aesthetic scoring in the models was tested by comparing current conditions in a discrete area of the facility with a Development scenario in the same area. The Development scenario consisted of two 6-story buildings and a trail replacing natural areas. The results of the vista aesthetic model indicate that the viewshed area variable had the greatest effect on the aesthetics overall score. Results from the landscape aesthetics model indicate a 10% increase in overall aesthetics value, attributed to the increase in landscape diversity. The models are sensitive to the weights assigned to certain variables by the user, and these weights should be set to reflect regional landscape characteristics as well as stakeholder preferences. This demonstration project shows that natural landscape aesthetics can be evaluated as part of a nonmonetary assessment of ES, and a scenario-building exercise provides end users with a tradeoff analysis in support of natural resource management decisions. Integr Environ Assess Manag 2017;13:926-938. © 2017 SETAC. © 2017 SETAC.

GIS-assisted spatial analysis for urban regulatory detailed planning: designer's dimension in the Chinese code system

NASA Astrophysics Data System (ADS)

Yu, Yang; Zeng, Zheng

2009-10-01

By discussing the causes behind the high amendments ratio in the implementation of urban regulatory detailed plans in China despite its law-ensured status, the study aims to reconcile conflict between the legal authority of regulatory detailed planning and the insufficient scientific support in its decision-making and compilation by introducing into the process spatial analysis based on GIS technology and 3D modeling thus present a more scientific and flexible approach to regulatory detailed planning in China. The study first points out that the current compilation process of urban regulatory detailed plan in China employs mainly an empirical approach which renders it constantly subjected to amendments; the study then discusses the need and current utilization of GIS in the Chinese system and proposes the framework of a GIS-assisted 3D spatial analysis process from the designer's perspective which can be regarded as an alternating processes between the descriptive codes and physical design in the compilation of regulatory detailed planning. With a case study of the processes and results from the application of the framework, the paper concludes that the proposed framework can be an effective instrument which provides more rationality, flexibility and thus more efficiency to the compilation and decision-making process of urban regulatory detailed plan in China.

Analyzing spatial variability of soil properties in the urban park before and after reconstruction to support decision-making in landscaping

NASA Astrophysics Data System (ADS)

Romzaikina, Olga; Vasenev, Viacheslav; Khakimova, Rita

2017-04-01

On-going urbanization stresses a necessity for structural and aesthetically organized urban landscapes to improve citizen's life quality. Urban soils and vegetation are the main components of urban ecosystems. Urban greenery regulates the climate, controls and air quality and supports biodiversity in urban areas. Soils play a key role in supporting urban greenery. However, soils of urban parks also perform other important environmental functions. Urban soils are influenced by a variety of environmental and anthropogenic factors and, in the result, are highly heterogeneous and dynamic. Reconstructions of green zones and urban parks, usually occurring in cities, alter soil properties. Analyzing spatial variability and dynamics of soil properties is important to support decision-making in landscaping. Therefore, the research aimed to analyze the spatial distribution of the key soil properties (acidity, soil organic carbon (SOC) and nutrient contents) in the urban park before and after reconstruction to support decision-making in selecting ornamental plants for landscaping. The research was conducted in the urban park named after Artyom Borovik in Moscow before (2012) and after (2014) the reconstruction. Urban soil's properties maps for both periods were created by interpolation of the field data. The observed urban soils included recreazems, urbanozems and constuctozems. Before the reconstruction soils were sampled using the uniform design (the net with 100 m side and key plots with 50m size). After the reconstructions the additional samples were collected at locations, where the land cover and functional zones changed in a result of the reconstruction.We sample from the depths 0-30, 30-50 and 50-100 cm. The following soil properties were measured: pH, SOC, K2O and P2O5. The maps of the analyzed properties were developed using open QGIS2.4 software by IDW. The vegetation in the park was examined using the scale of the visual assessment. The results of the visual assessment were processed using QGIS2.4 and the maps of the vegetation condition were created. High spatial variability was shown for observed soil properties with the highest variance reported for nutrient concentrations. High heterogeneity in P2O5 and K2O was obtained both in topsoil and subsoil, before and after reconstruction. We showed that average concentrations of P2O5 and K2O were correspondingly above and below legal threshold taken for the Moscow city. In result of the reconstruction the pH has changed from slightly acid and acidic to neutral and slightly alkaline. The topsoil SOC content has increased in the result of reconstruction but still was below threshold, recommended by municipal regulations. The potassium content and acidity were the main factors, influencing the vegetation condition. The 'weakened' condition of wood vegetation was reported with the lowest values obtained for the Pinus sylvestris, Thuja occidentals and, Sorbus aucuparia. References have developed for planting vegetation. The spatial heterogeneity and high dynamics of urban soils constraints the quantitative assessment of their properties and functions and the use of this information in landscaping. The successful experience of digital soil mapping techniques in urban park allowed solving this problem and highlighted the importance of soil data for creating urban green infrastructure.

Remote-Sensing and Automated Water Resources Tracking: Near Real-Time Decision Support for Water Managers Facing Drought and Flood

NASA Astrophysics Data System (ADS)

Reiter, M. E.; Elliott, N.; Veloz, S.; Love, F.; Moody, D.; Hickey, C.; Fitzgibbon, M.; Reynolds, M.; Esralew, R.

2016-12-01

Innovative approaches for tracking the Earth's natural resources, especially water which is essential for all living things, are essential during a time of rapid environmental change. The Central Valley is a nexus for water resources in California, draining the Sacramento and San Joaquin River watersheds. The distribution of water throughout California and the Central Valley, while dynamic, is highly managed through an extensive regional network of canals, levees, and pumps. Water allocation and delivery is determined through a complex set of rules based on water contracts, historic priority, and other California water policies. Furthermore, urban centers, agriculture, and the environment throughout the state are already competing for water, particularly during drought. Competition for water is likely to intensify as California is projected to experience continued increases in demand due to population growth and more arid growing conditions, while also having reduced or modified water supply due to climate change. As a result, it is difficult to understand or predict how water will be used to fulfill wildlife and wetland conservation needs. A better understanding of the spatial distribution of water in near real-time can facilitate adaptation of water resource management to changing conditions on the landscape, both over the near- and long-term. The Landsat satellite mission delivers imagery every 16-days from nearly every place on the earth at a high spatial resolution. We have integrated remote sensing of satellite data, classification modeling, bioinformatics, optimization, and ecological analyses to develop an automated near real-time water resources tracking and decision-support system for the Central Valley of California. Our innovative system has applications for coordinated water management in the Central Valley to support people, places, and wildlife and is being used to understand the factors that drive variation in the distribution and abundance of water resources, particularly drought and flood, at multiple spatial and temporal scales.

Designing a Hydro-Economic Collaborative Computer Decision Support System: Approaches, Best Practices, Lessons Learned, and Future Trends

NASA Astrophysics Data System (ADS)

Rosenberg, D. E.

2008-12-01

Designing and implementing a hydro-economic computer model to support or facilitate collaborative decision making among multiple stakeholders or users can be challenging and daunting. Collaborative modeling is distinguished and more difficult than non-collaborative efforts because of a large number of users with different backgrounds, disagreement or conflict among stakeholders regarding problem definitions, modeling roles, and analysis methods, plus evolving ideas of model scope and scale and needs for information and analysis as stakeholders interact, use the model, and learn about the underlying water system. This presentation reviews the lifecycle for collaborative model making and identifies some key design decisions that stakeholders and model developers must make to develop robust and trusted, verifiable and transparent, integrated and flexible, and ultimately useful models. It advances some best practices to implement and program these decisions. Among these best practices are 1) modular development of data- aware input, storage, manipulation, results recording and presentation components plus ways to couple and link to other models and tools, 2) explicitly structure both input data and the meta data that describes data sources, who acquired it, gaps, and modifications or translations made to put the data in a form usable by the model, 3) provide in-line documentation on model inputs, assumptions, calculations, and results plus ways for stakeholders to document their own model use and share results with others, and 4) flexibly program with graphical object-oriented properties and elements that allow users or the model maintainers to easily see and modify the spatial, temporal, or analysis scope as the collaborative process moves forward. We draw on examples of these best practices from the existing literature, the author's prior work, and some new applications just underway. The presentation concludes by identifying some future directions for collaborative modeling including geo-spatial display and analysis, real-time operations, and internet-based tools plus the design and programming needed to implement these capabilities.

Spatial distribution and risk assessment of radionuclides in soils around a coal-fired power plant: A case study from the city of Baoji, China

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dai Lijun; Wei Haiyan; Wang Lingqing

2007-06-15

Coal burning may enhance human exposure to the natural radionuclides that occur around coal-fired power plants (CFPP). In this study, the spatial distribution and hazard assessment of radionuclides found in soils around a CFPP were investigated using statistics, geostatistics, and geographic information system (GIS) techniques. The concentrations of {sup 226}Ra, {sup 232}Th, and {sup 40}K in soils range from 12.54 to 40.18, 38.02 to 72.55, and 498.02 to 1126.98 Bq kg{sup -1}, respectively. Ordinary kriging was carried out to map the spatial patterns of radionuclides, and disjunctive kriging was used to quantify the probability of radium equivalent activity (Ra{sub eq})more » higher than the threshold. The maps show that the spatial variability of the natural radionuclide concentrations in soils was apparent. The results of this study could provide valuable information for risk assessment of environmental pollution and decision support.« less

Spatial distribution and risk assessment of radionuclides in soils around a coal-fired power plant: A case study from the city of Baoji, China

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dai, L.J.; Wei, H.Y.; Wang, L.Q.

2007-06-15

Coal burning may enhance human exposure to the natural radionuclides that occur around coal-fired power plants (CFPP). In this study, the spatial distribution and hazard assessment of radionuclides found in soils around a CFPP were investigated using statistics, geostatistics, and geographic information system (GIS) techniques. The concentrations of Ra-226, Th-232, and K-40 in soils range from 12.54 to 40.18, 38.02 to 72.55, and 498.02 to 1126.98 Bq kg{sup -1}, respectively. Ordinary kriging was carried out to map the spatial patterns of radionuclides, and disjunctive kriging was used to quantify the probability of radium equivalent activity (Ra{sub eq}) higher than themore » threshold. The maps show that the spatial variability of the natural radionuclide concentrations in soils was apparent. The results of this study could provide valuable information for risk assessment of environmental pollution and decision support.« less

FEMA's Earthquake Incident Journal: A Web-Based Data Integration and Decision Support Tool for Emergency Management

NASA Astrophysics Data System (ADS)

Jones, M.; Pitts, R.

2017-12-01

For emergency managers, government officials, and others who must respond to rapidly changing natural disasters, timely access to detailed information related to affected terrain, population and infrastructure is critical for planning, response and recovery operations. Accessing, analyzing and disseminating such disparate information in near real-time are critical decision support components. However, finding a way to handle a variety of informative yet complex datasets poses a challenge when preparing for and responding to disasters. Here, we discuss the implementation of a web-based data integration and decision support tool for earthquakes developed by the Federal Emergency Management Agency (FEMA) as a solution to some of these challenges. While earthquakes are among the most well- monitored and measured of natural hazards, the spatially broad impacts of shaking, ground deformation, landslides, liquefaction, and even tsunamis, are extremely difficult to quantify without accelerated access to data, modeling, and analytics. This web-based application, deemed the "Earthquake Incident Journal", provides real-time access to authoritative and event-specific data from external (e.g. US Geological Survey, NASA, state and local governments, etc.) and internal (FEMA) data sources. The journal includes a GIS-based model for exposure analytics, allowing FEMA to assess the severity of an event, estimate impacts to structures and population in near real-time, and then apply planning factors to exposure estimates to answer questions such as: What geographic areas are impacted? Will federal support be needed? What resources are needed to support survivors? And which infrastructure elements or essential facilities are threatened? This presentation reviews the development of the Earthquake Incident Journal, detailing the data integration solutions, the methodology behind the GIS-based automated exposure model, and the planning factors as well as other analytical advances that provide near real-time decision support to the federal government.

Integrating multi-criteria decision analysis for a GIS-based hazardous waste landfill sitting in Kurdistan Province, western Iran

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sharifi, Mozafar; Hadidi, Mosslem; Vessali, Elahe

2009-10-15

The evaluation of a hazardous waste disposal site is a complicated process because it requires data from diverse social and environmental fields. These data often involve processing of a significant amount of spatial information which can be used by GIS as an important tool for land use suitability analysis. This paper presents a multi-criteria decision analysis alongside with a geospatial analysis for the selection of hazardous waste landfill sites in Kurdistan Province, western Iran. The study employs a two-stage analysis to provide a spatial decision support system for hazardous waste management in a typically under developed region. The purpose ofmore » GIS was to perform an initial screening process to eliminate unsuitable land followed by utilization of a multi-criteria decision analysis (MCDA) to identify the most suitable sites using the information provided by the regional experts with reference to new chosen criteria. Using 21 exclusionary criteria, as input layers, masked maps were prepared. Creating various intermediate or analysis map layers a final overlay map was obtained representing areas for hazardous waste landfill sites. In order to evaluate different landfill sites produced by the overlaying a landfill suitability index system was developed representing cumulative effects of relative importance (weights) and suitability values of 14 non-exclusionary criteria including several criteria resulting from field observation. Using this suitability index 15 different sites were visited and based on the numerical evaluation provided by MCDA most suitable sites were determined.« less

Integrating multi-criteria decision analysis for a GIS-based hazardous waste landfill sitting in Kurdistan Province, western Iran.

PubMed

Sharifi, Mozafar; Hadidi, Mosslem; Vessali, Elahe; Mosstafakhani, Parasto; Taheri, Kamal; Shahoie, Saber; Khodamoradpour, Mehran

2009-10-01

The evaluation of a hazardous waste disposal site is a complicated process because it requires data from diverse social and environmental fields. These data often involve processing of a significant amount of spatial information which can be used by GIS as an important tool for land use suitability analysis. This paper presents a multi-criteria decision analysis alongside with a geospatial analysis for the selection of hazardous waste landfill sites in Kurdistan Province, western Iran. The study employs a two-stage analysis to provide a spatial decision support system for hazardous waste management in a typically under developed region. The purpose of GIS was to perform an initial screening process to eliminate unsuitable land followed by utilization of a multi-criteria decision analysis (MCDA) to identify the most suitable sites using the information provided by the regional experts with reference to new chosen criteria. Using 21 exclusionary criteria, as input layers, masked maps were prepared. Creating various intermediate or analysis map layers a final overlay map was obtained representing areas for hazardous waste landfill sites. In order to evaluate different landfill sites produced by the overlaying a landfill suitability index system was developed representing cumulative effects of relative importance (weights) and suitability values of 14 non-exclusionary criteria including several criteria resulting from field observation. Using this suitability index 15 different sites were visited and based on the numerical evaluation provided by MCDA most suitable sites were determined.

Spatial Dependence and Determinants of Dairy Farmers' Adoption of Best Management Practices for Water Protection in New Zealand

NASA Astrophysics Data System (ADS)

Yang, Wei; Sharp, Basil

2017-04-01

This paper analyses spatial dependence and determinants of the New Zealand dairy farmers' adoption of best management practices to protect water quality. A Bayesian spatial durbin probit model is used to survey data collected from farmers in the Waikato region of New Zealand. The results show that farmers located near each other exhibit similar choice behaviour, indicating the importance of farmer interactions in adoption decisions. The results also address that information acquisition is the most important determinant of farmers' adoption of best management practices. Financial problems are considered a significant barrier to adopting best management practices. Overall, the existence of distance decay effect and spatial dependence in farmers' adoption decisions highlights the importance of accounting for spatial effects in farmers' decision-making, which emerges as crucial to the formulation of sustainable agriculture policy.

Spatial Dependence and Determinants of Dairy Farmers' Adoption of Best Management Practices for Water Protection in New Zealand.

PubMed

Yang, Wei; Sharp, Basil

2017-04-01

This paper analyses spatial dependence and determinants of the New Zealand dairy farmers' adoption of best management practices to protect water quality. A Bayesian spatial durbin probit model is used to survey data collected from farmers in the Waikato region of New Zealand. The results show that farmers located near each other exhibit similar choice behaviour, indicating the importance of farmer interactions in adoption decisions. The results also address that information acquisition is the most important determinant of farmers' adoption of best management practices. Financial problems are considered a significant barrier to adopting best management practices. Overall, the existence of distance decay effect and spatial dependence in farmers' adoption decisions highlights the importance of accounting for spatial effects in farmers' decision-making, which emerges as crucial to the formulation of sustainable agriculture policy.

SPATIAL ANALYSIS AND DECISION ASSISTANCE (SADA) TRAINING COURSE

EPA Science Inventory

Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporates tools from environmental assessment into an effective problem-solving environment. SADA was developed by the Institute for Environmental Modeling at the University of Tennessee and inc...

An integrated decision support system for wastewater nutrient recovery and recycling to agriculture

NASA Astrophysics Data System (ADS)

Roy, E. D.; Bomeisl, L.; Cornbrooks, P.; Mo, W.

2017-12-01

Nutrient recovery and recycling has become a key research topic within the wastewater engineering and nutrient management communities. Several technologies now exist that can effectively capture nutrients from wastewater, and innovation in this area continues to be an important research pursuit. However, practical nutrient recycling solutions require more than capable nutrient capture technologies. We also need to understand the role that wastewater nutrient recovery and recycling can play within broader nutrient management schemes at the landscape level, including important interactions at the nexus of food, energy, and water. We are developing an integrated decision support system that combines wastewater treatment data, agricultural data, spatial nutrient balance modeling, life cycle assessment, stakeholder knowledge, and multi-criteria decision making. Our goals are to: (1) help guide design decisions related to the implementation of sustainable nutrient recovery technology, (2) support innovations in watershed nutrient management that operate at the interface of the built environment and agriculture, and (3) aid efforts to protect aquatic ecosystems while supporting human welfare in a circular nutrient economy. These goals will be realized partly through the assessment of plausible alternative scenarios for the future. In this presentation, we will describe the tool and focus on nutrient balance results for the New England region. These results illustrate that both centralized and decentralized wastewater nutrient recovery schemes have potential to transform nutrient flows in many New England watersheds, diverting wastewater N and P away from aquatic ecosystems and toward local or regional agricultural soils where they can offset a substantial percentage of imported fertilizer. We will also highlight feasibility criteria and next steps to integrate stakeholder knowledge, economics, and life cycle assessment into the tool.

Comparing multi-criteria decision analysis and integrated assessment to support long-term water supply planning

PubMed Central

Maurer, Max; Lienert, Judit

2017-01-01

We compare the use of multi-criteria decision analysis (MCDA)–or more precisely, models used in multi-attribute value theory (MAVT)–to integrated assessment (IA) models for supporting long-term water supply planning in a small town case study in Switzerland. They are used to evaluate thirteen system scale water supply alternatives in four future scenarios regarding forty-four objectives, covering technical, social, environmental, and economic aspects. The alternatives encompass both conventional and unconventional solutions and differ regarding technical, spatial and organizational characteristics. This paper focuses on the impact assessment and final evaluation step of the structured MCDA decision support process. We analyze the performance of the alternatives for ten stakeholders. We demonstrate the implications of model assumptions by comparing two IA and three MAVT evaluation model layouts of different complexity. For this comparison, we focus on the validity (ranking stability), desirability (value), and distinguishability (value range) of the alternatives given the five model layouts. These layouts exclude or include stakeholder preferences and uncertainties. Even though all five led us to identify the same best alternatives, they did not produce identical rankings. We found that the MAVT-type models provide higher distinguishability and a more robust basis for discussion than the IA-type models. The needed complexity of the model, however, should be determined based on the intended use of the model within the decision support process. The best-performing alternatives had consistently strong performance for all stakeholders and future scenarios, whereas the current water supply system was outperformed in all evaluation layouts. The best-performing alternatives comprise proactive pipe rehabilitation, adapted firefighting provisions, and decentralized water storage and/or treatment. We present recommendations for possible ways of improving water supply planning in the case study and beyond. PMID:28481881

Developing Flexible, Integrated Hydrologic Modeling Systems for Multiscale Analysis in the Midwest and Great Lakes Region

NASA Astrophysics Data System (ADS)

Hamlet, A. F.; Chiu, C. M.; Sharma, A.; Byun, K.; Hanson, Z.

2016-12-01

Physically based hydrologic modeling of surface and groundwater resources that can be flexibly and efficiently applied to support water resources policy/planning/management decisions at a wide range of spatial and temporal scales are greatly needed in the Midwest, where stakeholder access to such tools is currently a fundamental barrier to basic climate change assessment and adaptation efforts, and also the co-production of useful products to support detailed decision making. Based on earlier pilot studies in the Pacific Northwest Region, we are currently assembling a suite of end-to-end tools and resources to support various kinds of water resources planning and management applications across the region. One of the key aspects of these integrated tools is that the user community can access gridded products at any point along the end-to-end chain of models, looking backwards in time about 100 years (1915-2015), and forwards in time about 85 years using CMIP5 climate model projections. The integrated model is composed of historical and projected future meteorological data based on station observations and statistical and dynamically downscaled climate model output respectively. These gridded meteorological data sets serve as forcing data for the macro-scale VIC hydrologic model implemented over the Midwest at 1/16 degree resolution. High-resolution climate model (4km WRF) output provides inputs for the analyses of urban impacts, hydrologic extremes, agricultural impacts, and impacts to the Great Lakes. Groundwater recharge estimated by the surface water model provides input data for fine-scale and macro-scale groundwater models needed for specific applications. To highlight the multi-scale use of the integrated models in support of co-production of scientific information for decision making, we briefly describe three current case studies addressing different spatial scales of analysis: 1) Effects of climate change on the water balance of the Great Lakes, 2) Future hydropower resources in the St. Joseph River basin, 3) Effects of climate change on carbon cycling in small lakes in the Northern Highland Lakes District.

The Evolving Urban Community and Military Installations: A Dynamic Spatial Decision Support System for Sustainable Military Communities

DTIC Science & Technology

2007-01-01

focus on identifying growth by income and housing costs. These, and other models are focused on the city itself and deal with growth over the course...2. This model employs a set of econometric models to project future population, household, and employment. The landscape is gridded into one... model in LEAM (LEAMecon) forecasts changes in output, employment and income over time based on changes in the market, technology, productivity and

Soldier Perceptions of the Rapid Decision Trainer

DTIC Science & Technology

2005-05-01

utility. "* Integrated 3D spatialized sound, supporting SCORM Integration the most common sound formats including Wav and Midi . A major objective of this...34low" and "very low" ratings in a similar manner for the lowest ratings categories. Pre-LFX Questionnaire Overall training value of the RDT. Lieutenants...on school computers and has issues are similar to ActiveX, however applets issued the RDT on CD-ROM to each IOBC student installed on the client

Bringing ecosystem services into integrated water resources management.

PubMed

Liu, Shuang; Crossman, Neville D; Nolan, Martin; Ghirmay, Hiyoba

2013-11-15

In this paper we propose an ecosystem service framework to support integrated water resource management and apply it to the Murray-Darling Basin in Australia. Water resources in the Murray-Darling Basin have been over-allocated for irrigation use with the consequent degradation of freshwater ecosystems. In line with integrated water resource management principles, Australian Government reforms are reducing the amount of water diverted for irrigation to improve ecosystem health. However, limited understanding of the broader benefits and trade-offs associated with reducing irrigation diversions has hampered the planning process supporting this reform. Ecosystem services offer an integrative framework to identify the broader benefits associated with integrated water resource management in the Murray-Darling Basin, thereby providing support for the Government to reform decision-making. We conducted a multi-criteria decision analysis for ranking regional potentials to provide ecosystem services at river basin scale. We surveyed the wider public about their understanding of, and priorities for, managing ecosystem services and then integrated the results with spatially explicit indicators of ecosystem service provision. The preliminary results of this work identified the sub-catchments with the greatest potential synergies and trade-offs of ecosystem service provision under the integrated water resources management reform process. With future development, our framework could be used as a decision support tool by those grappling with the challenge of the sustainable allocation of water between irrigation and the environment. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Rapid Assessment of Ecosystem Service Co-Benefits of Biodiversity Priority Areas in Madagascar

PubMed Central

Andriamaro, Luciano; Cano, Carlos Andres; Grantham, Hedley S.; Hole, David; Juhn, Daniel; McKinnon, Madeleine; Rasolohery, Andriambolantsoa; Steininger, Marc; Wright, Timothy Max

2016-01-01

The importance of ecosystems for supporting human well-being is increasingly recognized by both the conservation and development sectors. Our ability to conserve ecosystems that people rely on is often limited by a lack of spatially explicit data on the location and distribution of ecosystem services (ES), the benefits provided by nature to people. Thus there is a need to map ES to guide conservation investments, to ensure these co-benefits are maintained. To target conservation investments most effectively, ES assessments must be rigorous enough to support conservation planning, rapid enough to respond to decision-making timelines, and often must rely on existing data. We developed a framework for rapid spatial assessment of ES that relies on expert and stakeholder consultation, available data, and spatial analyses in order to rapidly identify sites providing multiple benefits. We applied the framework in Madagascar, a country with globally significant biodiversity and a high level of human dependence on ecosystems. Our objective was to identify the ES co-benefits of biodiversity priority areas in order to guide the investment strategy of a global conservation fund. We assessed key provisioning (fisheries, hunting and non-timber forest products, and water for domestic use, agriculture, and hydropower), regulating (climate mitigation, flood risk reduction and coastal protection), and cultural (nature tourism) ES. We also conducted multi-criteria analyses to identify sites providing multiple benefits. While our approach has limitations, including the reliance on proximity-based indicators for several ES, the results were useful for targeting conservation investments by the Critical Ecosystem Partnership Fund (CEPF). Because our approach relies on available data, standardized methods for linking ES provision to ES use, and expert validation, it has the potential to quickly guide conservation planning and investment decisions in other data-poor regions. PMID:28006005

Post-traumatic stress symptoms are associated with better performance on a delayed match-to-position task

PubMed Central

2018-01-01

Many individuals with posttraumatic stress disorder (PTSD) report experiencing frequent intrusive memories of the original traumatic event (e.g., flashbacks). These memories can be triggered by situations or stimuli that reflect aspects of the trauma and may reflect basic processes in learning and memory, such as generalization. It is possible that, through increased generalization, non-threatening stimuli that once evoked normal memories become associated with traumatic memories. Previous research has reported increased generalization in PTSD, but the role of visual discrimination processes has not been examined. To investigate visual discrimination in PTSD, 143 participants (Veterans and civilians) self-assessed for symptom severity were grouped according to the presence of severe PTSD symptoms (PTSS) vs. few/no symptoms (noPTSS). Participants were given a visual match-to-sample pattern separation task that varied trials by spatial separation (Low, Medium, High) and temporal delays (5, 10, 20, 30 s). Unexpectedly, the PTSS group demonstrated better discrimination performance than the noPTSS group at the most difficult spatial trials (Low spatial separation). Further assessment of accuracy and reaction time using diffusion drift modeling indicated that the better performance by the PTSS group on the hardest trials was not explained by slower reaction times, but rather a faster accumulation of evidence during decision making in conjunction with a reduced threshold, indicating a tendency in the PTSS group to decide quickly rather than waiting for additional evidence to support the decision. This result supports the need for future studies examining the precise role of discrimination and generalization in PTSD, and how these cognitive processes might contribute to expression and maintenance of PTSD symptoms. PMID:29736339

Towards a conceptual multi-agent-based framework to simulate the spatial group decision-making process

NASA Astrophysics Data System (ADS)

Ghavami, Seyed Morsal; Taleai, Mohammad

2017-04-01

Most spatial problems are multi-actor, multi-issue and multi-phase in nature. In addition to their intrinsic complexity, spatial problems usually involve groups of actors from different organizational and cognitive backgrounds, all of whom participate in a social structure to resolve or reduce the complexity of a given problem. Hence, it is important to study and evaluate what different aspects influence the spatial problem resolution process. Recently, multi-agent systems consisting of groups of separate agent entities all interacting with each other have been put forward as appropriate tools to use to study and resolve such problems. In this study, then in order to generate a better level of understanding regarding the spatial problem group decision-making process, a conceptual multi-agent-based framework is used that represents and specifies all the necessary concepts and entities needed to aid group decision making, based on a simulation of the group decision-making process as well as the relationships that exist among the different concepts involved. The study uses five main influencing entities as concepts in the simulation process: spatial influence, individual-level influence, group-level influence, negotiation influence and group performance measures. Further, it explains the relationship among different concepts in a descriptive rather than explanatory manner. To illustrate the proposed framework, the approval process for an urban land use master plan in Zanjan—a provincial capital in Iran—is simulated using MAS, the results highlighting the effectiveness of applying an MAS-based framework when wishing to study the group decision-making process used to resolve spatial problems.

Research on the decision-making model of land-use spatial optimization

NASA Astrophysics Data System (ADS)

He, Jianhua; Yu, Yan; Liu, Yanfang; Liang, Fei; Cai, Yuqiu

2009-10-01

Using the optimization result of landscape pattern and land use structure optimization as constraints of CA simulation results, a decision-making model of land use spatial optimization is established coupled the landscape pattern model with cellular automata to realize the land use quantitative and spatial optimization simultaneously. And Huangpi district is taken as a case study to verify the rationality of the model.

AHP-based spatial analysis of water quality impact assessment due to change in vehicular traffic caused by highway broadening in Sikkim Himalaya

NASA Astrophysics Data System (ADS)

Banerjee, Polash; Ghose, Mrinal Kanti; Pradhan, Ratika

2018-05-01

Spatial analysis of water quality impact assessment of highway projects in mountainous areas remains largely unexplored. A methodology is presented here for Spatial Water Quality Impact Assessment (SWQIA) due to highway-broadening-induced vehicular traffic change in the East district of Sikkim. Pollution load of the highway runoff was estimated using an Average Annual Daily Traffic-Based Empirical model in combination with mass balance model to predict pollution in the rivers within the study area. Spatial interpolation and overlay analysis were used for impact mapping. Analytic Hierarchy Process-Based Water Quality Status Index was used to prepare a composite impact map. Model validation criteria, cross-validation criteria, and spatial explicit sensitivity analysis show that the SWQIA model is robust. The study shows that vehicular traffic is a significant contributor to water pollution in the study area. The model is catering specifically to impact analysis of the concerned project. It can be an aid for decision support system for the project stakeholders. The applicability of SWQIA model needs to be explored and validated in the context of a larger set of water quality parameters and project scenarios at a greater spatial scale.

Democratic input into the nuclear waste disposal problem: The influence of geographical data on decision making examined through a Web-based GIS

NASA Astrophysics Data System (ADS)

Evans, Andrew J.; Kingston, Richard; Carver, Steve

This paper elucidates the manner in which users of an online decision support system respond to spatially distributed data when assessing the solution to environmental risks, specifically, nuclear waste disposal. It presents tests for revealing whether users are responding to geographical data and whether they are influenced by their home location (Not in My Back Yard - style behavior). The tests specifically cope with problems associated with testing home-to-risk distances where both locations are constrained by the shape of the landmass available. In addition, we detail the users' wider feelings towards such a system, and reflect upon the possibilities such systems offer for participatory democracy initiatives.

Cross-scale phenological data integration to benefit resource management and monitoring

USGS Publications Warehouse

Richardson, Andrew D.; Weltzin, Jake F.; Morisette, Jeffrey T.

2017-01-01

Climate change is presenting new challenges for natural resource managers charged with maintaining sustainable ecosystems and landscapes. Phenology, a branch of science dealing with seasonal natural phenomena (bird migration or plant flowering in response to weather changes, for example), bridges the gap between the biosphere and the climate system. Phenological processes operate across scales that span orders of magnitude—from leaf to globe and from days to seasons—making phenology ideally suited to multiscale, multiplatform data integration and delivery of information at spatial and temporal scales suitable to inform resource management decisions.A workshop report: Workshop held June 2016 to investigate opportunities and challenges facing multi-scale, multi-platform integration of phenological data to support natural resource management decision-making.

Interacting Social and Environmental Predictors for the Spatial Distribution of Conservation Lands

PubMed Central

Baldwin, Robert F.; Leonard, Paul B.

2015-01-01

Conservation decisions should be evaluated for how they meet conservation goals at multiple spatial extents. Conservation easements are land use decisions resulting from a combination of social and environmental conditions. An emerging area of research is the evaluation of spatial distribution of easements and their spatial correlates. We tested the relative influence of interacting social and environmental variables on the spatial distribution of conservation easements by ownership category and conservation status. For the Appalachian region of the United States, an area with a long history of human occupation and complex land uses including public-private conservation, we found that settlement, economic, topographic, and environmental data associated with spatial distribution of easements (N = 4813). Compared to random locations, easements were more likely to be found in lower elevations, in areas of greater agricultural productivity, farther from public protected areas, and nearer other human features. Analysis of ownership and conservation status revealed sources of variation, with important differences between local and state government ownerships relative to non-governmental organizations (NGOs), and among U.S. Geological Survey (USGS) GAP program status levels. NGOs were more likely to have easements nearer protected areas, and higher conservation status, while local governments held easements closer to settlement, and on lands of greater agricultural potential. Logistic interactions revealed environmental variables having effects modified by social correlates, and the strongest predictors overall were social (distance to urban area, median household income, housing density, distance to land trust office). Spatial distribution of conservation lands may be affected by geographic area of influence of conservation groups, suggesting that multi-scale conservation planning strategies may be necessary to satisfy local and regional needs for reserve networks. Our results support previous findings and provide an ecoregion-scale view that conservation easements may provide, at local scales, conservation functions on productive, more developable lands. Conservation easements may complement functions of public protected areas but more research should examine relative landscape-level ecological functions of both forms of protection. PMID:26465155

Interacting Social and Environmental Predictors for the Spatial Distribution of Conservation Lands.

PubMed

Baldwin, Robert F; Leonard, Paul B

2015-01-01

Conservation decisions should be evaluated for how they meet conservation goals at multiple spatial extents. Conservation easements are land use decisions resulting from a combination of social and environmental conditions. An emerging area of research is the evaluation of spatial distribution of easements and their spatial correlates. We tested the relative influence of interacting social and environmental variables on the spatial distribution of conservation easements by ownership category and conservation status. For the Appalachian region of the United States, an area with a long history of human occupation and complex land uses including public-private conservation, we found that settlement, economic, topographic, and environmental data associated with spatial distribution of easements (N = 4813). Compared to random locations, easements were more likely to be found in lower elevations, in areas of greater agricultural productivity, farther from public protected areas, and nearer other human features. Analysis of ownership and conservation status revealed sources of variation, with important differences between local and state government ownerships relative to non-governmental organizations (NGOs), and among U.S. Geological Survey (USGS) GAP program status levels. NGOs were more likely to have easements nearer protected areas, and higher conservation status, while local governments held easements closer to settlement, and on lands of greater agricultural potential. Logistic interactions revealed environmental variables having effects modified by social correlates, and the strongest predictors overall were social (distance to urban area, median household income, housing density, distance to land trust office). Spatial distribution of conservation lands may be affected by geographic area of influence of conservation groups, suggesting that multi-scale conservation planning strategies may be necessary to satisfy local and regional needs for reserve networks. Our results support previous findings and provide an ecoregion-scale view that conservation easements may provide, at local scales, conservation functions on productive, more developable lands. Conservation easements may complement functions of public protected areas but more research should examine relative landscape-level ecological functions of both forms of protection.

Progress in and prospects for fluvial flood modelling.

PubMed

Wheater, H S

2002-07-15

Recent floods in the UK have raised public and political awareness of flood risk. There is an increasing recognition that flood management and land-use planning are linked, and that decision-support modelling tools are required to address issues of climate and land-use change for integrated catchment management. In this paper, the scientific context for fluvial flood modelling is discussed, current modelling capability is considered and research challenges are identified. Priorities include (i) appropriate representation of spatial precipitation, including scenarios of climate change; (ii) development of a national capability for continuous hydrological simulation of ungauged catchments; (iii) improved scientific understanding of impacts of agricultural land-use and land-management change, and the development of new modelling approaches to represent those impacts; (iv) improved representation of urban flooding, at both local and catchment scale; (v) appropriate parametrizations for hydraulic simulation of in-channel and flood-plain flows, assimilating available ground observations and remotely sensed data; and (vi) a flexible decision-support modelling framework, incorporating developments in computing, data availability, data assimilation and uncertainty analysis.

Using Google Earth in Marine Research and Operational Decision Support

NASA Astrophysics Data System (ADS)

Blower, J. D.; Bretherton, D.; Haines, K.; Liu, C.; Rawlings, C.; Santokhee, A.; Smith, I.

2006-12-01

A key advantage of Virtual Globes ("geobrowsers") such as Google Earth is that they can display many different geospatial data types at a huge range of spatial scales. In this demonstration and poster display we shall show how marine data from disparate sources can be brought together in a geobrowser in order to support both scientific research and operational search and rescue activities. We have developed the Godiva2 interactive website for browsing and exploring marine data, mainly output from supercomputer analyses and predictions of ocean circulation. The user chooses a number of parameters (e.g. sea temperature at 100m depth on 1st July 2006) and can load an image of the resulting data in Google Earth. Through the use of an automatically-refreshing NetworkLink the user can explore the whole globe at a very large range of spatial scales: the displayed data will automatically be refreshed to show data at increasingly fine resolution as the user zooms in. This is a valuable research tool for exploring these terabyte- scale datasets. Many coastguard organizations around the world use SARIS, a software application produced by BMT Cordah Ltd., to predict the drift pattern of objects in the sea in order to support search and rescue operations. Different drifting objects have different trajectories depending on factors such as their buoyancy and windage and so a computer model, supported by meteorological and oceanographic data, is needed to help rescuers locate their targets. We shall demonstrate how Google Earth is used to display output from the SARIS model (including the search target location and associated error polygon) alongside meteorological data (wind vectors) and oceanographic data (sea temperature, surface currents) from Godiva2 in order to support decision-making. We shall also discuss the limitations of using Google Earth in this context: these include the difficulties of working with time- dependent data and the need to access data securely. essc.ac.uk:8080/Godiva2

SeaSketch: Implementation of a Decision-Support Platform for a Channel Islands National Marine Sanctuary Multi-sector Working Group

NASA Astrophysics Data System (ADS)

Goldberg, G.; McClintock, W.

2016-12-01

Effective interagency and cross-sector coordination is essential to ecosystem based management which depends on processes characterized by collaboration and science-based information. Many technological barriers that exist in the development of science-based management plans are closely tied to process challenges, such as the sharing of data and information or the inclusion of parties with varied levels of technical experience. The Channel Islands National Marine Sanctuary has convened a diverse working group to develop recommendations for the management of marine shipping in and around the Santa Barbara Channel, as well as recommendations regarding research needs and outreach strategies. Working group members take a multi-issue approach with four distinct goals related to the reduction of ship strikes on whales, emissions and air quality, conflicting ocean uses, and issues of navigational safety. Members range from industry representatives, scientists, and multiple local and federal government entities. The recommended management plans will be based in the best-available science, and will build off of previous efforts, making this an interesting case study of adaptive management. In addition to support from the Sanctuary and professional facilitators, the group is using a decision-support platform, SeaSketch (safepassage.seasketch.org). SeaSketch is a web-based GIS that supports collaborative science-based marine spatial planning (MSP). Each feature supports a step of the MSP process, from data gathering, identification of data needs, the design of spatial plans, evaluation of those plans with analytics, and map-based forums that facilitate data-driven discussions. Working group members are able to access these tools to explore management options and collaborate remotely, in addition to using the platform during in-person meetings and webinars. Empowering diverse audiences to engage in the design of science-based plans is of key importance to developing ecosystem-based management plans where multi-sector participation and inter-agency coordination are critical.

SeaSketch: Implementation of a Decision-Support Platform for a Channel Islands National Marine Sanctuary Multi-sector Working Group

NASA Astrophysics Data System (ADS)

Goldberg, G.; McClintock, W.

2016-02-01

Effective interagency and cross-sector coordination is essential to ecosystem based management which depends on processes characterized by collaboration and science-based information. Many technological barriers that exist in the development of science-based management plans are closely tied to process challenges, such as the sharing of data and information or the inclusion of parties with varied levels of technical experience. The Channel Islands National Marine Sanctuary has convened a diverse working group to develop recommendations for the management of marine shipping in and around the Santa Barbara Channel, as well as recommendations regarding research needs and outreach strategies. Working group members take a multi-issue approach with four distinct goals related to the reduction of ship strikes on whales, emissions and air quality, conflicting ocean uses, and issues of navigational safety. Members range from industry representatives, scientists, and multiple local and federal government entities. The recommended management plans will be based in the best-available science, and will build off of previous efforts, making this an interesting case study of adaptive management. In addition to support from the Sanctuary and professional facilitators, the group is using a decision-support platform, SeaSketch (safepassage.seasketch.org). SeaSketch is a web-based GIS that supports collaborative science-based marine spatial planning (MSP). Each feature supports a step of the MSP process, from data gathering, identification of data needs, the design of spatial plans, evaluation of those plans with analytics, and map-based forums that facilitate data-driven discussions. Working group members are able to access these tools to explore management options and collaborate remotely, in addition to using the platform during in-person meetings and webinars. Empowering diverse audiences to engage in the design of science-based plans is of key importance to developing ecosystem-based management plans where multi-sector participation and inter-agency coordination are critical.

Online Hydrologic Impact Assessment Decision Support System using Internet and Web-GIS Capability

NASA Astrophysics Data System (ADS)

Choi, J.; Engel, B. A.; Harbor, J.

2002-05-01

Urban sprawl and the corresponding land use change from lower intensity uses, such as agriculture and forests, to higher intensity uses including high density residential and commercial has various long- and short-term environment impacts on ground water recharge, water pollution, and storm water drainage. A web-based Spatial Decision Support System, SDSS, for Web-based operation of long-term hydrologic impact modeling and analysis was developed. The system combines a hydrologic model, databases, web-GIS capability and HTML user interfaces to create a comprehensive hydrologic analysis system. The hydrologic model estimates daily direct runoff using the NRCS Curve Number technique and annual nonpoint source pollution loading by an event mean concentration approach. This is supported by a rainfall database with over 30 years of daily rainfall for the continental US. A web-GIS interface and a robust Web-based watershed delineation capability were developed to simplify the spatial data preparation task that is often a barrier to hydrologic model operation. The web-GIS supports browsing of map layers including hydrologic soil groups, roads, counties, streams, lakes and railroads, as well as on-line watershed delineation for any geographic point the user selects with a simple mouse click. The watershed delineation results can also be used to generate data for the hydrologic and water quality models available in the DSS. This system is already being used by city and local government planners for hydrologic impact evaluation of land use change from urbanization, and can be found at http://pasture.ecn.purdue.edu/~watergen/hymaps. This system can assist local community, city and watershed planners, and even professionals when they are examining impacts of land use change on water resources. They can estimate the hydrologic impact of possible land use changes using this system with readily available data supported through the Internet. This system provides a cost effective approach to serve potential users who require easy-to-use tools.

Easier surveillance of climate-related health vulnerabilities through a Web-based spatial OLAP application.

PubMed

Bernier, Eveline; Gosselin, Pierre; Badard, Thierry; Bédard, Yvan

2009-04-03

Climate change has a significant impact on population health. Population vulnerabilities depend on several determinants of different types, including biological, psychological, environmental, social and economic ones. Surveillance of climate-related health vulnerabilities must take into account these different factors, their interdependence, as well as their inherent spatial and temporal aspects on several scales, for informed analyses. Currently used technology includes commercial off-the-shelf Geographic Information Systems (GIS) and Database Management Systems with spatial extensions. It has been widely recognized that such OLTP (On-Line Transaction Processing) systems were not designed to support complex, multi-temporal and multi-scale analysis as required above. On-Line Analytical Processing (OLAP) is central to the field known as BI (Business Intelligence), a key field for such decision-support systems. In the last few years, we have seen a few projects that combine OLAP and GIS to improve spatio-temporal analysis and geographic knowledge discovery. This has given rise to SOLAP (Spatial OLAP) and a new research area. This paper presents how SOLAP and climate-related health vulnerability data were investigated and combined to facilitate surveillance. Based on recent spatial decision-support technologies, this paper presents a spatio-temporal web-based application that goes beyond GIS applications with regard to speed, ease of use, and interactive analysis capabilities. It supports the multi-scale exploration and analysis of integrated socio-economic, health and environmental geospatial data over several periods. This project was meant to validate the potential of recent technologies to contribute to a better understanding of the interactions between public health and climate change, and to facilitate future decision-making by public health agencies and municipalities in Canada and elsewhere. The project also aimed at integrating an initial collection of geo-referenced multi-scale indicators that were identified by Canadian specialists and end-users as relevant for the surveillance of the public health impacts of climate change. This system was developed in a multidisciplinary context involving researchers, policy makers and practitioners, using BI and web-mapping concepts (more particularly SOLAP technologies), while exploring new solutions for frequent automatic updating of data and for providing contextual warnings for users (to minimize the risk of data misinterpretation). According to the project participants, the final system succeeds in facilitating surveillance activities in a way not achievable with today's GIS. Regarding the experiments on frequent automatic updating and contextual user warnings, the results obtained indicate that these are meaningful and achievable goals but they still require research and development for their successful implementation in the context of surveillance and multiple organizations. Surveillance of climate-related health vulnerabilities may be more efficiently supported using a combination of BI and GIS concepts, and more specifically, SOLAP technologies (in that it facilitates and accelerates multi-scale spatial and temporal analysis to a point where a user can maintain an uninterrupted train of thought by focussing on "what" she/he wants (not on "how" to get it) and always obtain instant answers, including to the most complex queries that take minutes or hours with OLTP systems (e.g., aggregated, temporal, comparative)). The developed system respects Newell's cognitive band of 10 seconds when performing knowledge discovery (exploring data, looking for hypotheses, validating models). The developed system provides new operators for easily and rapidly exploring multidimensional data at different levels of granularity, for different regions and epochs, and for visualizing the results in synchronized maps, tables and charts. It is naturally adapted to deal with multiscale indicators such as those used in the surveillance community, as confirmed by this project's end-users.

Implementation of EcoAIM (trademark) - A Multi-Objective Decision Support Tool for Ecosystem Services at Department of Defense Installations

DTIC Science & Technology

2014-09-26

neotropical birds , as well as its high-quality habitat for resident birds in the Chesapeake Bay watershed, such as bald eagles and several species of...Duelli and Obrist 2003). Several papers have developed methods that relate measurable habitat features at various spatial scales to species richness ...advised to first establish a baseline in which a species adheres to patterns of ideal habitat selection (Johnson 2007). In the case of the APG bird

Interactive Management and Updating of Spatial Data Bases

NASA Technical Reports Server (NTRS)

French, P.; Taylor, M.

1982-01-01

The decision making process, whether for power plant siting, load forecasting or energy resource planning, invariably involves a blend of analytical methods and judgement. Management decisions can be improved by the implementation of techniques which permit an increased comprehension of results from analytical models. Even where analytical procedures are not required, decisions can be aided by improving the methods used to examine spatially and temporally variant data. How the use of computer aided planning (CAP) programs and the selection of a predominant data structure, can improve the decision making process is discussed.

Validating a spatially distributed hydrological model with soil morphology data

NASA Astrophysics Data System (ADS)

Doppler, T.; Honti, M.; Zihlmann, U.; Weisskopf, P.; Stamm, C.

2014-09-01

Spatially distributed models are popular tools in hydrology claimed to be useful to support management decisions. Despite the high spatial resolution of the computed variables, calibration and validation is often carried out only on discharge time series at specific locations due to the lack of spatially distributed reference data. Because of this restriction, the predictive power of these models, with regard to predicted spatial patterns, can usually not be judged. An example of spatial predictions in hydrology is the prediction of saturated areas in agricultural catchments. These areas can be important source areas for inputs of agrochemicals to the stream. We set up a spatially distributed model to predict saturated areas in a 1.2 km2 catchment in Switzerland with moderate topography and artificial drainage. We translated soil morphological data available from soil maps into an estimate of the duration of soil saturation in the soil horizons. This resulted in a data set with high spatial coverage on which the model predictions were validated. In general, these saturation estimates corresponded well to the measured groundwater levels. We worked with a model that would be applicable for management decisions because of its fast calculation speed and rather low data requirements. We simultaneously calibrated the model to observed groundwater levels and discharge. The model was able to reproduce the general hydrological behavior of the catchment in terms of discharge and absolute groundwater levels. However, the the groundwater level predictions were not accurate enough to be used for the prediction of saturated areas. Groundwater level dynamics were not adequately reproduced and the predicted spatial saturation patterns did not correspond to those estimated from the soil map. Our results indicate that an accurate prediction of the groundwater level dynamics of the shallow groundwater in our catchment that is subject to artificial drainage would require a model that better represents processes at the boundary between the unsaturated and the saturated zone. However, data needed for such a more detailed model are not generally available. This severely hampers the practical use of such models despite their usefulness for scientific purposes.

Decision support system based on DPSIR framework for a low flow Mediterranean river basin

NASA Astrophysics Data System (ADS)

Bangash, Rubab Fatima; Kumar, Vikas; Schuhmacher, Marta

2013-04-01

The application of decision making practices are effectively enhanced by adopting a procedural approach setting out a general methodological framework within which specific methods, models and tools can be integrated. Integrated Catchment Management is a process that recognizes the river catchment as a basic organizing unit for understanding and managing ecosystem process. Decision support system becomes more complex by considering unavoidable human activities within a catchment that are motivated by multiple and often competing criteria and/or constraints. DPSIR is a causal framework for describing the interactions between society and the environment. This framework has been adopted by the European Environment Agency and the components of this model are: Driving forces, Pressures, States, Impacts and Responses. The proposed decision support system is a two step framework based on DPSIR. Considering first three component of DPSIR, Driving forces, Pressures and States, hydrological and ecosystem services models are developed. The last two components, Impact and Responses, helped to develop Bayesian Network to integrate the models. This decision support system also takes account of social, economic and environmental aspects. A small river of Catalonia (Northeastern Spain), Francoli River with a low flow (~2 m3/s) is selected for integration of catchment assessment models and to improve knowledge transfer from research to the stakeholders with a view to improve decision making process. DHI's MIKE BASIN software is used to evaluate the low-flow Francolí River with respect to the water bodies' characteristics and also to assess the impact of human activities aiming to achieve good water status for all waters to comply with the WFD's River Basin Management Plan. Based on ArcGIS, MIKE BASIN is a versatile decision support tool that provides a simple and powerful framework for managers and stakeholders to address multisectoral allocation and environmental issues in river basins. While InVEST is a spatially explicit tool, used to model and map a suite of ecosystem services caused by land cover changes or climate change impacts. Moreover, results obtained from low-flow hydrological simulation and ecosystem services models serves as useful tools to develop decision support system based on DPSIR framework by integrating models. Bayesian Networks is used as a knowledge integration and visualization tool to summarize the outcomes of hydrological and ecosystem services models at the "Response" stage of DPSIR. Bayesian Networks provide a framework for modelling the logical relationship between catchment variables and decision objectives by quantifying the strength of these relationships using conditional probabilities. Participatory nature of this framework can provide better communication of water research, particularly in the context of a perceived lack of future awareness-raising with the public that helps to develop more sustainable water management strategies. Acknowledgements The present study was financially supported by Spanish Ministry of Economy and Competitiveness for its financial support through the project SCARCE (Consolider-Ingenio 2010 CSD2009-00065). R. F. Bangash also received PhD fellowship from AGAUR (Commissioner for Universities and Research of the Department of Innovation, Universities and Enterprise of the "Generalitat de Catalunya" and the European Social Fund).

Multiple memory systems as substrates for multiple decision systems

PubMed Central

Doll, Bradley B.; Shohamy, Daphna; Daw, Nathaniel D.

2014-01-01

It has recently become widely appreciated that value-based decision making is supported by multiple computational strategies. In particular, animal and human behavior in learning tasks appears to include habitual responses described by prominent model-free reinforcement learning (RL) theories, but also more deliberative or goal-directed actions that can be characterized by a different class of theories, model-based RL. The latter theories evaluate actions by using a representation of the contingencies of the task (as with a learned map of a spatial maze), called an “internal model.” Given the evidence of behavioral and neural dissociations between these approaches, they are often characterized as dissociable learning systems, though they likely interact and share common mechanisms. In many respects, this division parallels a longstanding dissociation in cognitive neuroscience between multiple memory systems, describing, at the broadest level, separate systems for declarative and procedural learning. Procedural learning has notable parallels with model-free RL: both involve learning of habits and both are known to depend on parts of the striatum. Declarative memory, by contrast, supports memory for single events or episodes and depends on the hippocampus. The hippocampus is thought to support declarative memory by encoding temporal and spatial relations among stimuli and thus is often referred to as a relational memory system. Such relational encoding is likely to play an important role in learning an internal model, the representation that is central to model-based RL. Thus, insofar as the memory systems represent more general-purpose cognitive mechanisms that might subserve performance on many sorts of tasks including decision making, these parallels raise the question whether the multiple decision systems are served by multiple memory systems, such that one dissociation is grounded in the other. Here we investigated the relationship between model-based RL and relational memory by comparing individual differences across behavioral tasks designed to measure either capacity. Human subjects performed two tasks, a learning and generalization task (acquired equivalence) which involves relational encoding and depends on the hippocampus; and a sequential RL task that could be solved by either a model-based or model-free strategy. We assessed the correlation between subjects’ use of flexible, relational memory, as measured by generalization in the acquired equivalence task, and their differential reliance on either RL strategy in the decision task. We observed a significant positive relationship between generalization and model-based, but not model-free, choice strategies. These results are consistent with the hypothesis that model-based RL, like acquired equivalence, relies on a more general-purpose relational memory system. PMID:24846190

Biasing moral decisions by exploiting the dynamics of eye gaze.

PubMed

Pärnamets, Philip; Johansson, Petter; Hall, Lars; Balkenius, Christian; Spivey, Michael J; Richardson, Daniel C

2015-03-31

Eye gaze is a window onto cognitive processing in tasks such as spatial memory, linguistic processing, and decision making. We present evidence that information derived from eye gaze can be used to change the course of individuals' decisions, even when they are reasoning about high-level, moral issues. Previous studies have shown that when an experimenter actively controls what an individual sees the experimenter can affect simple decisions with alternatives of almost equal valence. Here we show that if an experimenter passively knows when individuals move their eyes the experimenter can change complex moral decisions. This causal effect is achieved by simply adjusting the timing of the decisions. We monitored participants' eye movements during a two-alternative forced-choice task with moral questions. One option was randomly predetermined as a target. At the moment participants had fixated the target option for a set amount of time we terminated their deliberation and prompted them to choose between the two alternatives. Although participants were unaware of this gaze-contingent manipulation, their choices were systematically biased toward the target option. We conclude that even abstract moral cognition is partly constituted by interactions with the immediate environment and is likely supported by gaze-dependent decision processes. By tracking the interplay between individuals, their sensorimotor systems, and the environment, we can influence the outcome of a decision without directly manipulating the content of the information available to them.

Building an Intelligent Water Information System - American River Prototype

NASA Astrophysics Data System (ADS)

Glaser, S. D.; Bales, R. C.; Conklin, M. H.

2013-12-01

With better management, California's existing water supplies could go further to meeting the needs of the state's urban and agricultural uses. For example, California's water reservoirs are currently controlled and regulated using forecasts based upon more than 75 years of historical data. In the face of global climate change, these forecasts are becoming increasingly inadequate to precisely manage water resources. We propose implementing Leveraging the newest frontiers of information technology, we are developing a basin-scale real-time intelligent water infrastructure system that enables more information-intensive decision support. The complete system is made up of four key components. First, a strategically deployed ground-observation system will complement satellite measurements and provide continuous and accurate estimates of snowpack, soil moisture, vegetation state and energy balance across watersheds. Using our recently developed but mature technologies, we deliver measurements of hydrologic variables over a multi- tiered network of wireless sensor arrays, with a granularity of time and space previously unheard of. Second, satellite and aircraft remote sensing provide the only practical means of spatially continuous basin-wide measurement and monitoring of snow properties, vegetation characteristics and other watershed conditions. The ground-based system is designed to blend with remote sensing data on Sierra Nevada snow properties, and provide value-added products of unprecedented spatial detail and accuracy that are useable on a watershed level. Third, together the satellite and ground-based data make possible the updating of forecast tools, and routine use of physically based hydrologic models. The decision-support framework will provide tools to extract and visualize information of interest from the measured and modeled data, to assess uncertainties, and to optimize operations. Fourth, the advanced cyber infrastructure blends and transforms the numbers recorded by sensors into information in the form that is useful for decision-making. In a sense it 'monetizes' the data. It is the cyber infrastructure that links measurements, data processing, models and users. System software must provide flexibility for multiple types of access from user queries to automated and direct links with analysis tools and decision-support systems. We are currently installing a basin-scale ground-based sensor network focusing on measurements of snowpack, solar radiation, temperature, rH and soil moisture across the American River basin. Although this is a research network, it also provides core elements of a full ground-based operational system.

A Comprehensive Optimization Strategy for Real-time Spatial Feature Sharing and Visual Analytics in Cyberinfrastructure

NASA Astrophysics Data System (ADS)

Li, W.; Shao, H.

2017-12-01

For geospatial cyberinfrastructure enabled web services, the ability of rapidly transmitting and sharing spatial data over the Internet plays a critical role to meet the demands of real-time change detection, response and decision-making. Especially for the vector datasets which serve as irreplaceable and concrete material in data-driven geospatial applications, their rich geometry and property information facilitates the development of interactive, efficient and intelligent data analysis and visualization applications. However, the big-data issues of vector datasets have hindered their wide adoption in web services. In this research, we propose a comprehensive optimization strategy to enhance the performance of vector data transmitting and processing. This strategy combines: 1) pre- and on-the-fly generalization, which automatically determines proper simplification level through the introduction of appropriate distance tolerance (ADT) to meet various visualization requirements, and at the same time speed up simplification efficiency; 2) a progressive attribute transmission method to reduce data size and therefore the service response time; 3) compressed data transmission and dynamic adoption of a compression method to maximize the service efficiency under different computing and network environments. A cyberinfrastructure web portal was developed for implementing the proposed technologies. After applying our optimization strategies, substantial performance enhancement is achieved. We expect this work to widen the use of web service providing vector data to support real-time spatial feature sharing, visual analytics and decision-making.

On the Science-Policy Bridge: Do Spatial Heat Vulnerability Assessment Studies Influence Policy?

PubMed

Wolf, Tanja; Chuang, Wen-Ching; McGregor, Glenn

2015-10-23

Human vulnerability to heat varies at a range of spatial scales, especially within cities where there can be noticeable intra-urban differences in heat risk factors. Mapping and visualizing intra-urban heat vulnerability offers opportunities for presenting information to support decision-making. For example the visualization of the spatial variation of heat vulnerability has the potential to enable local governments to identify hot spots of vulnerability and allocate resources and increase assistance to people in areas of greatest need. Recently there has been a proliferation of heat vulnerability mapping studies, all of which, to varying degrees, justify the process of vulnerability mapping in a policy context. However, to date, there has not been a systematic review of the extent to which the results of vulnerability mapping studies have been applied in decision-making. Accordingly we undertook a comprehensive review of 37 recently published papers that use geospatial techniques for assessing human vulnerability to heat. In addition, we conducted an anonymous survey of the lead authors of the 37 papers in order to establish the level of interaction between the researchers as science information producers and local authorities as information users. Both paper review and author survey results show that heat vulnerability mapping has been used in an attempt to communicate policy recommendations, raise awareness and induce institutional networking and learning, but has not as yet had a substantive influence on policymaking or preventive action.

Robustness of risk maps and survey networks to knowledge gaps about a new invasive pest.

PubMed

Yemshanov, Denys; Koch, Frank H; Ben-Haim, Yakov; Smith, William D

2010-02-01

In pest risk assessment it is frequently necessary to make management decisions regarding emerging threats under severe uncertainty. Although risk maps provide useful decision support for invasive alien species, they rarely address knowledge gaps associated with the underlying risk model or how they may change the risk estimates. Failure to recognize uncertainty leads to risk-ignorant decisions and miscalculation of expected impacts as well as the costs required to minimize these impacts. Here we use the information gap concept to evaluate the robustness of risk maps to uncertainties in key assumptions about an invading organism. We generate risk maps with a spatial model of invasion that simulates potential entries of an invasive pest via international marine shipments, their spread through a landscape, and establishment on a susceptible host. In particular, we focus on the question of how much uncertainty in risk model assumptions can be tolerated before the risk map loses its value. We outline this approach with an example of a forest pest recently detected in North America, Sirex noctilio Fabricius. The results provide a spatial representation of the robustness of predictions of S. noctilio invasion risk to uncertainty and show major geographic hotspots where the consideration of uncertainty in model parameters may change management decisions about a new invasive pest. We then illustrate how the dependency between the extent of uncertainties and the degree of robustness of a risk map can be used to select a surveillance network design that is most robust to knowledge gaps about the pest.

Enhancing stakeholder involvement in environmental decision making: Active Response Geographic Information System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Faber, B.G.; Thomas, V.L.; Thomas, M.R.

This paper describes a spatial decision support system that facilitates land-related negotiations and resolving conflicts. This system, called Active Response Geographic Information System (AR/GIS), uses a geographic information system to examine land resource management issues which involve multiple stakeholder groups. In this process, participants are given the opportunity and tools needed to share ideas in a facilitated land resource allocation negotiation session. Participants are able to assess current land status, develop objectives, propose alternative planning scenarios, and evaluate the effects or impacts of each alternative. AR/GIS is a unique tool that puts geographic information directly at the fingertips of non-technicalmore » policy analysts, decision makers, and representatives of stakeholder groups during the negotiation process. AR/GIS enhances individual comprehension and ownership of the decision making process and increasing the efficiency and effectiveness of group debate. It is most beneficial to planning tasks which are inherently geographic in nature, which require consideration of a large number of physical constraints and economic implications, and which involve publicly sensitive tradeoffs.« less

Land Cover Applications, Landscape Dynamics, and Global Change

USGS Publications Warehouse

Tieszen, Larry L.

2007-01-01

The Land Cover Applications, Landscape Dynamics, and Global Change project at U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS) seeks to integrate remote sensing and simulation models to better understand and seek solutions to national and global issues. Modeling processes related to population impacts, natural resource management, climate change, invasive species, land use changes, energy development, and climate mitigation all pose significant scientific opportunities. The project activities use remotely sensed data to support spatial monitoring, provide sensitivity analyses across landscapes and large regions, and make the data and results available on the Internet with data access and distribution, decision support systems, and on-line modeling. Applications support sustainable natural resource use, carbon cycle science, biodiversity conservation, climate change mitigation, and robust simulation modeling approaches that evaluate ecosystem and landscape dynamics.

Integrating Multi-Sensor Remote Sensing and In-situ Measurements for Africa Drought Monitoring and Food Security Assessment

NASA Astrophysics Data System (ADS)

Hao, X.; Qu, J. J.; Motha, R. P.; Stefanski, R.; Malherbe, J.

2014-12-01

Drought is one of the most complicated natural hazards, and causes serious environmental, economic and social consequences. Agricultural production systems, which are highly susceptible to weather and climate extremes, are often the first and most vulnerable sector to be affected by drought events. In Africa, crop yield potential and grazing quality are already nearing their limit of temperature sensitivity, and, rapid population growth and frequent drought episodes pose serious complications for food security. It is critical to promote sustainable agriculture development in Africa under conditions of climate extremes. Soil moisture is one of the most important indicators for agriculture drought, and is a fundamentally critical parameter for decision support in crop management, including planting, water use efficiency and irrigation. While very significant technological advances have been introduced for remote sensing of surface soil moisture from space, in-situ measurements are still critical for calibration and validation of soil moisture estimation algorithms. For operational applications, synergistic collaboration is needed to integrate measurements from different sensors at different spatial and temporal scales. In this presentation, a collaborative effort is demonstrated for drought monitoring in Africa, supported and coordinated by WMO, including surface soil moisture and crop status monitoring. In-situ measurements of soil moisture, precipitation and temperature at selected sites are provided by local partners in Africa. Measurements from the Soil Moisture and Ocean Salinity (SMOS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) are integrated with in-situ observations to derive surface soil moisture at high spatial resolution. Crop status is estimated through temporal analysis of current and historical MODIS measurements. Integrated analysis of soil moisture data and crop status provides both in-depth understanding of drought conditions and potential impacts on crop yield. This information is extremely useful in local decision support for agricultural management.

Integrating Multi-Sensor Remote Sensing and In-situ Measurements for Africa Drought Monitoring and Food Security Assessment

NASA Astrophysics Data System (ADS)

Hao, X.; Qu, J. J.; Motha, R. P.; Stefanski, R.; Malherbe, J.

2015-12-01

Drought is one of the most complicated natural hazards, and causes serious environmental, economic and social consequences. Agricultural production systems, which are highly susceptible to weather and climate extremes, are often the first and most vulnerable sector to be affected by drought events. In Africa, crop yield potential and grazing quality are already nearing their limit of temperature sensitivity, and, rapid population growth and frequent drought episodes pose serious complications for food security. It is critical to promote sustainable agriculture development in Africa under conditions of climate extremes. Soil moisture is one of the most important indicators for agriculture drought, and is a fundamentally critical parameter for decision support in crop management, including planting, water use efficiency and irrigation. While very significant technological advances have been introduced for remote sensing of surface soil moisture from space, in-situ measurements are still critical for calibration and validation of soil moisture estimation algorithms. For operational applications, synergistic collaboration is needed to integrate measurements from different sensors at different spatial and temporal scales. In this presentation, a collaborative effort is demonstrated for drought monitoring in Africa, supported and coordinated by WMO, including surface soil moisture and crop status monitoring. In-situ measurements of soil moisture, precipitation and temperature at selected sites are provided by local partners in Africa. Measurements from the Soil Moisture and Ocean Salinity (SMOS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) are integrated with in-situ observations to derive surface soil moisture at high spatial resolution. Crop status is estimated through temporal analysis of current and historical MODIS measurements. Integrated analysis of soil moisture data and crop status provides both in-depth understanding of drought conditions and potential impacts on crop yield. This information is extremely useful in local decision support for agricultural management.

A Web-based environmental decision support system (WEDSS) for environmental planning and watershed management

NASA Astrophysics Data System (ADS)

Sugumaran, Ramanathan; Meyer, James C.; Davis, Jim

2004-10-01

Local governments often struggle to balance competing demands for residential, commercial and industrial development with imperatives to minimize environmental degradation. In order to effectively manage this development process on a sustainable basis, local planners and government agencies are increasingly seeking better tools and techniques. In this paper, we describe the development of a Web-Based Environmental Decision Support System (WEDSS), which helps to prioritize local watersheds in terms of environmental sensitivity using multiple criteria identified by planners and local government staff in the city of Columbia, and Boone County, Missouri. The development of the system involved three steps, the first was to establish the relevant environmental criteria and develop data layers for each criterion, then a spatial model was developed for analysis, and lastly a Web-based interface with analysis tools was developed using client-server technology. The WEDSS is an example of a way to run spatial models over the Web and represents a significant increase in capability over other WWW-based GIS applications that focus on database querying and map display. The WEDSS seeks to aid in the development of agreement regarding specific local areas deserving increased protection and the public policies to be pursued in minimizing the environmental impact of future development. The tool is also intended to assist ongoing public information and education efforts concerning watershed management and water quality issues for the City of Columbia, Missouri and adjacent developing areas within Boone County, Missouri.

Remote sensing and GIS based information system for sustainable resources planning at Panchayat level

NASA Astrophysics Data System (ADS)

Velmurugan, A.; Bhatt, S.; Dadhwal, V. K.

2006-12-01

Spatial databases of natural resources are very much essential to ensure enhanced productivity by conserving soil and water and to maintain ecological integrity of any region. Integration of various thematic layers prepared from high resolution data and detailed field survey would be preferred for grass root level planning (Panchayat) aimed to realize the potential of production system on a sustained basis. In this study, a detailed spatial data base was created for part of Kasaragod dist., Kerala, India. Detailed soil survey was carried out using cadastral map and registered over high resolution satellite data (IRS LISS-IV) which helped to identify problems and potentials of the area. Nearly 600 ha of land were found to be at higher erosion risk category out of ten soil series identified in the study area. Remote sensing data was used to prepare land use/land cover map and coconut (53%) followed by mixed vegetation type (16%) were found to be dominant. Soil site suitability assessment for major crops of the area was carried out and crossed with present land use to get the mismatch in land use/land utilization type. Alternate land use plan was prepared considering the potentials and problems of various available resources. Decision Support System (DSS) along with user interface is developed to support decision and extract relevant information. As organic carbon is one of the most important indicators of soil fertility C stock in the present and proposed land use was also estimated to understand the environmental significance.

Spatial Learning and Action Planning in a Prefrontal Cortical Network Model

PubMed Central

Martinet, Louis-Emmanuel; Sheynikhovich, Denis; Benchenane, Karim; Arleo, Angelo

2011-01-01

The interplay between hippocampus and prefrontal cortex (PFC) is fundamental to spatial cognition. Complementing hippocampal place coding, prefrontal representations provide more abstract and hierarchically organized memories suitable for decision making. We model a prefrontal network mediating distributed information processing for spatial learning and action planning. Specific connectivity and synaptic adaptation principles shape the recurrent dynamics of the network arranged in cortical minicolumns. We show how the PFC columnar organization is suitable for learning sparse topological-metrical representations from redundant hippocampal inputs. The recurrent nature of the network supports multilevel spatial processing, allowing structural features of the environment to be encoded. An activation diffusion mechanism spreads the neural activity through the column population leading to trajectory planning. The model provides a functional framework for interpreting the activity of PFC neurons recorded during navigation tasks. We illustrate the link from single unit activity to behavioral responses. The results suggest plausible neural mechanisms subserving the cognitive “insight” capability originally attributed to rodents by Tolman & Honzik. Our time course analysis of neural responses shows how the interaction between hippocampus and PFC can yield the encoding of manifold information pertinent to spatial planning, including prospective coding and distance-to-goal correlates. PMID:21625569

The use of GIS to support sustainable management of vineyards in Plovdiv, Bulgaria.

PubMed

Arnaudova, Zh; Bileva, T

2011-01-01

Vine is a traditional branch of plant growing in Bulgaria. The exact location of the vine culture is a specific complex of environmental factors influencing its development, such as climate, soil, landscape and traditions of the region. GIS is a platform to better manage, evaluate and present spatial data in a useful visual form. It's improves the decision-making by combining data with accurate location and management the vineyards. In the present survey were studied and analyzed the factors in choosing an appropriate location for the cultivation of vine varieties in selected regions of Plovdiv. Climatic and soil characteristics, topography and environmental factors as well as presence of virus vector nematodes from family Longidoridae in creating the vines through GIS spatial analysis are taken into account.

PREFER: a European service providing forest fire management support products

NASA Astrophysics Data System (ADS)

Eftychidis, George; Laneve, Giovanni; Ferrucci, Fabrizio; Sebastian Lopez, Ana; Lourenco, Louciano; Clandillon, Stephen; Tampellini, Lucia; Hirn, Barbara; Diagourtas, Dimitris; Leventakis, George

2015-06-01

PREFER is a Copernicus project of the EC-FP7 program which aims developing spatial information products that may support fire prevention and burned areas restoration decisions and establish a relevant web-based regional service for making these products available to fire management stakeholders. The service focuses to the Mediterranean region, where fire risk is high and damages from wildfires are quite important, and develop its products for pilot areas located in Spain, Portugal, Italy, France and Greece. PREFER aims to allow fire managers to have access to online resources, which shall facilitate fire prevention measures, fire hazard and risk assessment, estimation of fire impact and damages caused by wildfire as well as support monitoring of post-fire regeneration and vegetation recovery. It makes use of a variety of products delivered by space borne sensors and develop seasonal and daily products using multi-payload, multi-scale and multi-temporal analysis of EO data. The PREFER Service portfolio consists of two main suite of products. The first refers to mapping products for supporting decisions concerning the Preparedness/Prevention Phase (ISP Service). The service delivers Fuel, Hazard and Fire risk maps for this purpose. Furthermore the PREFER portfolio includes Post-fire vegetation recovery, burn scar maps, damage severity and 3D fire damage assessment products in order to support relative assessments required in context of the Recovery/Reconstruction Phase (ISR Service) of fire management.

Dynamic simulation of crime perpetration and reporting to examine community intervention strategies.

PubMed

Yonas, Michael A; Burke, Jessica G; Brown, Shawn T; Borrebach, Jeffrey D; Garland, Richard; Burke, Donald S; Grefenstette, John J

2013-10-01

To develop a conceptual computational agent-based model (ABM) to explore community-wide versus spatially focused crime reporting interventions to reduce community crime perpetrated by youth. Agents within the model represent individual residents and interact on a two-dimensional grid representing an abstract nonempirically grounded community setting. Juvenile agents are assigned initial random probabilities of perpetrating a crime and adults are assigned random probabilities of witnessing and reporting crimes. The agents' behavioral probabilities modify depending on the individual's experience with criminal behavior and punishment, and exposure to community crime interventions. Cost-effectiveness analyses assessed the impact of activating different percentages of adults to increase reporting and reduce community crime activity. Community-wide interventions were compared with spatially focused interventions, in which activated adults were focused in areas of highest crime prevalence. The ABM suggests that both community-wide and spatially focused interventions can be effective in reducing overall offenses, but their relative effectiveness may depend on the intensity and cost of the interventions. Although spatially focused intervention yielded localized reductions in crimes, such interventions were shown to move crime to nearby communities. Community-wide interventions can achieve larger reductions in overall community crime offenses than spatially focused interventions, as long as sufficient resources are available. The ABM demonstrates that community-wide and spatially focused crime strategies produce unique intervention dynamics influencing juvenile crime behaviors through the decisions and actions of community adults. It shows how such models might be used to investigate community-supported crime intervention programs by integrating community input and expertise and provides a simulated setting for assessing dimensions of cost comparison and intervention effect sustainability. ABM illustrates how intervention models might be used to investigate community-supported crime intervention programs.

A work-centered cognitively based architecture for decision support: the work-centered infomediary layer (WIL) model

NASA Astrophysics Data System (ADS)

Zachary, Wayne; Eggleston, Robert; Donmoyer, Jason; Schremmer, Serge

2003-09-01

Decision-making is strongly shaped and influenced by the work context in which decisions are embedded. This suggests that decision support needs to be anchored by a model (implicit or explicit) of the work process, in contrast to traditional approaches that anchor decision support to either context free decision models (e.g., utility theory) or to detailed models of the external (e.g., battlespace) environment. An architecture for cognitively-based, work centered decision support called the Work-centered Informediary Layer (WIL) is presented. WIL separates decision support into three overall processes that build and dynamically maintain an explicit context model, use the context model to identify opportunities for decision support and tailor generic decision-support strategies to the current context and offer them to the system-user/decision-maker. The generic decision support strategies include such things as activity/attention aiding, decision process structuring, work performance support (selective, contextual automation), explanation/ elaboration, infosphere data retrieval, and what if/action-projection and visualization. A WIL-based application is a work-centered decision support layer that provides active support without intent inferencing, and that is cognitively based without requiring classical cognitive task analyses. Example WIL applications are detailed and discussed.

A Decision Analysis Tool for Climate Impacts, Adaptations, and Vulnerabilities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Omitaomu, Olufemi A; Parish, Esther S; Nugent, Philip J

Climate change related extreme events (such as flooding, storms, and drought) are already impacting millions of people globally at a cost of billions of dollars annually. Hence, there are urgent needs for urban areas to develop adaptation strategies that will alleviate the impacts of these extreme events. However, lack of appropriate decision support tools that match local applications is limiting local planning efforts. In this paper, we present a quantitative analysis and optimization system with customized decision support modules built on geographic information system (GIS) platform to bridge this gap. This platform is called Urban Climate Adaptation Tool (Urban-CAT). Formore » all Urban-CAT models, we divide a city into a grid with tens of thousands of cells; then compute a list of metrics for each cell from the GIS data. These metrics are used as independent variables to predict climate impacts, compute vulnerability score, and evaluate adaptation options. Overall, the Urban-CAT system has three layers: data layer (that contains spatial data, socio-economic and environmental data, and analytic data), middle layer (that handles data processing, model management, and GIS operation), and application layer (that provides climate impacts forecast, adaptation optimization, and site evaluation). The Urban-CAT platform can guide city and county governments in identifying and planning for effective climate change adaptation strategies.« less

Overcoming barriers to cancer-helpline professionals providing decision support for callers: an implementation study.

PubMed

Stacey, Dawn; Chambers, Suzanne K; Jacobsen, Mary Jane; Dunn, Jeff

2008-11-01

To evaluate the effect of an intervention on healthcare professionals' perceptions of barriers influencing their provision of decision support for callers facing cancer-related decisions. A pre- and post-test study guided by the Ottawa Model of Research Use. Australian statewide cancer call center that provides public access to information and supportive cancer services. 34 nurses, psychologists, and other allied healthcare professionals at the cancer call center. Participants completed baseline measures and, subsequently, were exposed to an intervention that included a decision support tutorial, coaching protocol, and skill-building workshop. Strategies were implemented to address organizational barriers. Perceived barriers and facilitators influencing provision of decision support, decision support knowledge, quality of decision support provided to standardized callers, and call length. Postintervention participants felt more prepared, confident in providing decision support, and aware of decision support resources. They had a stronger belief that providing decision support was within their role. Participants significantly improved their knowledge and provided higher-quality decision support to standardized callers without changing call length. The implementation intervention overcame several identified barriers that influenced call center professionals when providing decision support. Nurses and other helpline professionals have the potential to provide decision support designed to help callers understand cancer information, clarify their values associated with their options, and reduce decisional conflict. However, they require targeted education and organizational interventions to reduce their perceived barriers to providing decision support.

Theoretical Approaches in the Context of Spatial Planning Decisions and the Relation with Urban Sustainability

NASA Astrophysics Data System (ADS)

Kumlu, Kadriye Burcu Yavuz; Tüdeş, Şule

2017-10-01

The sustainability agenda has maintained its importance since the days, when the production system took its capitalist form, as well as the population in the urban areas started to rise. Increasing number of both goods and the people have caused the degradation of the certain systems, which generate the urban areas. These systems could mainly be classified as social, environmental, physical and economical systems. Today, urban areas still have difficulty to protect those systems, due to the significant demand of the population. Therefore, studies related with the sustainable issues are significant in the sense of continuity of the urban systems. Therefore, in this paper, those studies in the context of the effects of physical decisions taken in the spatial planning process on urban sustainability, will be examined. The components of the physical decisions are limited to land use, density and design. Land use decisions will be examined in the context of mixed land use. On the other hand, decisions related with density will be analyzed in the sense of population density and floor area ratio (FAR). Besides, design decisions will be examined, by linking them with neighborhood design criteria. Additionally, the term of urban sustainability will only be limited to its social and environmental contexts in this study. Briefly stated, studies in the sustainable literature concerned with the effects of land use, density and design decisions taken in the spatial planning process on the social and environmental sustainability will be examined in this paper. After the compilation and the analyze of those studies, a theoretical approach will be proposed to determine social and environmental sustainability in the context of land use, density and design decisions, taken in the spatial planning process.

Design and implementation of intelligent electronic warfare decision making algorithm

NASA Astrophysics Data System (ADS)

Peng, Hsin-Hsien; Chen, Chang-Kuo; Hsueh, Chi-Shun

2017-05-01

Electromagnetic signals and the requirements of timely response have been a rapid growth in modern electronic warfare. Although jammers are limited resources, it is possible to achieve the best electronic warfare efficiency by tactical decisions. This paper proposes the intelligent electronic warfare decision support system. In this work, we develop a novel hybrid algorithm, Digital Pheromone Particle Swarm Optimization, based on Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and Shuffled Frog Leaping Algorithm (SFLA). We use PSO to solve the problem and combine the concept of pheromones in ACO to accumulate more useful information in spatial solving process and speed up finding the optimal solution. The proposed algorithm finds the optimal solution in reasonable computation time by using the method of matrix conversion in SFLA. The results indicated that jammer allocation was more effective. The system based on the hybrid algorithm provides electronic warfare commanders with critical information to assist commanders in effectively managing the complex electromagnetic battlefield.

A management-oriented framework for selecting metrics used to assess habitat- and path-specific quality in spatially structured populations

USGS Publications Warehouse

Nicol, Sam; Wiederholt, Ruscena; Diffendorfer, James E.; Mattsson, Brady; Thogmartin, Wayne E.; Semmens, Darius J.; Laura Lopez-Hoffman,; Norris, Ryan

2016-01-01

Mobile species with complex spatial dynamics can be difficult to manage because their population distributions vary across space and time, and because the consequences of managing particular habitats are uncertain when evaluated at the level of the entire population. Metrics to assess the importance of habitats and pathways connecting habitats in a network are necessary to guide a variety of management decisions. Given the many metrics developed for spatially structured models, it can be challenging to select the most appropriate one for a particular decision. To guide the management of spatially structured populations, we define three classes of metrics describing habitat and pathway quality based on their data requirements (graph-based, occupancy-based, and demographic-based metrics) and synopsize the ecological literature relating to these classes. Applying the first steps of a formal decision-making approach (problem framing, objectives, and management actions), we assess the utility of metrics for particular types of management decisions. Our framework can help managers with problem framing, choosing metrics of habitat and pathway quality, and to elucidate the data needs for a particular metric. Our goal is to help managers to narrow the range of suitable metrics for a management project, and aid in decision-making to make the best use of limited resources.

Information gathering, management and transfering for geospacial intelligence

NASA Astrophysics Data System (ADS)

Nunes, Paulo; Correia, Anacleto; Teodoro, M. Filomena

2017-07-01

Information is a key subject in modern organization operations. The success of joint and combined operations with organizations partners depends on the accurate information and knowledge flow concerning the operations theatre: provision of resources, environment evolution, markets location, where and when an event occurred. As in the past and nowadays we cannot conceive modern operations without maps and geo-spatial information (GI). Information and knowledge management is fundamental to the success of organizational decisions in an uncertainty environment. The georeferenced information management is a process of knowledge management, it begins in the raw data and ends on generating knowledge. GI and intelligence systems allow us to integrate all other forms of intelligence and can be a main platform to process and display geo-spatial-time referenced events. Combining explicit knowledge with peoples know-how to generate a continuous learning cycle that supports real time decisions mitigates the influences of fog of everyday competition and provides the knowledge supremacy. Extending the preliminary analysis done in [1], this work applies the exploratory factor analysis to a questionnaire about the GI and intelligence management in an organization company allowing to identify future lines of action to improve information process sharing and exploration of all the potential of this important resource.

The profile of executive function in OCD hoarders and hoarding disorder☆

PubMed Central

Morein-Zamir, Sharon; Papmeyer, Martina; Pertusa, Alberto; Chamberlain, Samuel R.; Fineberg, Naomi A.; Sahakian, Barbara J.; Mataix-Cols, David; Robbins, Trevor W.

2014-01-01

Hoarding disorder is a new mental disorder in DSM-5. It is classified alongside OCD and other presumably related disorders in the Obsessive-Compulsive and Related Disorders chapter. We examined cognitive performance in two distinct groups comprising individuals with both OCD and severe hoarding, and individuals with hoarding disorder without comorbid OCD. Participants completed executive function tasks assessing inhibitory control, cognitive flexibility, spatial planning, probabilistic learning and reversal and decision making. Compared to a matched healthy control group, OCD hoarders showed significantly worse performance on measures of response inhibition, set shifting, spatial planning, probabilistic learning and reversal, with intact decision making. Despite having a strikingly different clinical presentation, individuals with only hoarding disorder did not differ significantly from OCD hoarders on any cognitive measure suggesting the two hoarding groups have a similar pattern of cognitive difficulties. Tests of cognitive flexibility were least similar across the groups, but differences were small and potentially reflected subtle variation in underlying brain pathology together with psychometric limitations. These results highlight both commonalities and potential differences between OCD and hoarding disorder, and together with other lines of evidence, support the inclusion of the new disorder within the new Obsessive-Compulsive and Related Disorders chapter in DSM-5. PMID:24467873

Questioning the Relevance of Model-Based Probability Statements on Extreme Weather and Future Climate

NASA Astrophysics Data System (ADS)

Smith, L. A.

2007-12-01

We question the relevance of climate-model based Bayesian (or other) probability statements for decision support and impact assessment on spatial scales less than continental and temporal averages less than seasonal. Scientific assessment of higher resolution space and time scale information is urgently needed, given the commercial availability of "products" at high spatiotemporal resolution, their provision by nationally funded agencies for use both in industry decision making and governmental policy support, and their presentation to the public as matters of fact. Specifically we seek to establish necessary conditions for probability forecasts (projections conditioned on a model structure and a forcing scenario) to be taken seriously as reflecting the probability of future real-world events. We illustrate how risk management can profitably employ imperfect models of complicated chaotic systems, following NASA's study of near-Earth PHOs (Potentially Hazardous Objects). Our climate models will never be perfect, nevertheless the space and time scales on which they provide decision- support relevant information is expected to improve with the models themselves. Our aim is to establish a set of baselines of internal consistency; these are merely necessary conditions (not sufficient conditions) that physics based state-of-the-art models are expected to pass if their output is to be judged decision support relevant. Probabilistic Similarity is proposed as one goal which can be obtained even when our models are not empirically adequate. In short, probabilistic similarity requires that, given inputs similar to today's empirical observations and observational uncertainties, we expect future models to produce similar forecast distributions. Expert opinion on the space and time scales on which we might reasonably expect probabilistic similarity may prove of much greater utility than expert elicitation of uncertainty in parameter values in a model that is not empirically adequate; this may help to explain the reluctance of experts to provide information on "parameter uncertainty." Probability statements about the real world are always conditioned on some information set; they may well be conditioned on "False" making them of little value to a rational decision maker. In other instances, they may be conditioned on physical assumptions not held by any of the modellers whose model output is being cast as a probability distribution. Our models will improve a great deal in the next decades, and our insight into the likely climate fifty years hence will improve: maintaining the credibility of the science and the coherence of science based decision support, as our models improve, require a clear statement of our current limitations. What evidence do we have that today's state-of-the-art models provide decision-relevant probability forecasts? What space and time scales do we currently have quantitative, decision-relevant information on for 2050? 2080?

A multi-analysis approach for space-time and economic evaluation of risks related with livestock diseases: the example of FMD in Peru.

PubMed

Martínez-López, B; Ivorra, B; Fernández-Carrión, E; Perez, A M; Medel-Herrero, A; Sánchez-Vizcaíno, F; Gortázar, C; Ramos, A M; Sánchez-Vizcaíno, J M

2014-04-01

This study presents a multi-disciplinary decision-support tool, which integrates geo-statistics, social network analysis (SNA), spatial-stochastic spread model, economic analysis and mapping/visualization capabilities for the evaluation of the sanitary and socio-economic impact of livestock diseases under diverse epidemiologic scenarios. We illustrate the applicability of this tool using foot-and-mouth disease (FMD) in Peru as an example. The approach consisted on a flexible, multistep process that may be easily adapted based on data availability. The first module (mI) uses a geo-statistical approach for the estimation (if needed) of the distribution and abundance of susceptible population (in the example here, cattle, swine, sheep, goats, and camelids) at farm-level in the region or country of interest (Peru). The second module (mII) applies SNA for evaluating the farm-to-farm contact patterns and for exploring the structure and frequency of between-farm animal movements as a proxy for potential disease introduction or spread. The third module (mIII) integrates mI-II outputs into a spatial-stochastic model that simulates within- and between-farm FMD-transmission. The economic module (mIV) connects outputs from mI-III to provide an estimate of associated direct and indirect costs. A visualization module (mV) is also implemented to graph and map the outputs of module I-IV. After 1000 simulated epidemics, the mean (95% probability interval) number of outbreaks, infected animals, epidemic duration, and direct costs were 37 (1, 1164), 2152 (1, 13, 250), 63 days (0, 442), and US$ 1.2 million (1072, 9.5 million), respectively. Spread of disease was primarily local (<4.5km), but geolocation and type of index farm strongly influenced the extent and spatial patterns of an epidemic. The approach is intended to support decisions in the last phase of the FMD eradication program in Peru, in particular to inform and support the implementation of risk-based surveillance and livestock insurance systems that may help to prevent and control potential FMD virus incursions into Peru. Copyright © 2014 Elsevier B.V. All rights reserved.

An overview of data integration methods for regional assessment.

PubMed

Locantore, Nicholas W; Tran, Liem T; O'Neill, Robert V; McKinnis, Peter W; Smith, Elizabeth R; O'Connell, Michael

2004-06-01

The U.S. Environmental Protections Agency's (U.S. EPA) Regional Vulnerability Assessment(ReVA) program has focused much of its research over the last five years on developing and evaluating integration methods for spatial data. An initial strategic priority was to use existing data from monitoring programs, model results, and other spatial data. Because most of these data were not collected with an intention of integrating into a regional assessment of conditions and vulnerabilities, issues exist that may preclude the use of some methods or require some sort of data preparation. Additionally, to support multi-criteria decision-making, methods need to be able to address a series of assessment questions that provide insights into where environmental risks are a priority. This paper provides an overview of twelve spatial integration methods that can be applied towards regional assessment, along with preliminary results as to how sensitive each method is to data issues that will likely be encountered with the use of existing data.

High Performance Geostatistical Modeling of Biospheric Resources

NASA Astrophysics Data System (ADS)

Pedelty, J. A.; Morisette, J. T.; Smith, J. A.; Schnase, J. L.; Crosier, C. S.; Stohlgren, T. J.

2004-12-01

We are using parallel geostatistical codes to study spatial relationships among biospheric resources in several study areas. For example, spatial statistical models based on large- and small-scale variability have been used to predict species richness of both native and exotic plants (hot spots of diversity) and patterns of exotic plant invasion. However, broader use of geostastics in natural resource modeling, especially at regional and national scales, has been limited due to the large computing requirements of these applications. To address this problem, we implemented parallel versions of the kriging spatial interpolation algorithm. The first uses the Message Passing Interface (MPI) in a master/slave paradigm on an open source Linux Beowulf cluster, while the second is implemented with the new proprietary Xgrid distributed processing system on an Xserve G5 cluster from Apple Computer, Inc. These techniques are proving effective and provide the basis for a national decision support capability for invasive species management that is being jointly developed by NASA and the US Geological Survey.

Nursing Homes and their Spatial Contexts - Findings from Austria

NASA Astrophysics Data System (ADS)

Fischer, Tatjana

2017-10-01

Against the background of aging and the increasing number of persons in need of care on one hand and the decreasing potential of family support on the other hand, in-patient facilities both in rural areas as well as urban areas of Austria receive importance as final residence. The decision on a facility is challenging. That is why the Austrian Federal Ministry of Labour, Social Affairs and Consumer Protection edits a brochure in three volumes that provides interested persons with information on each residential and nursing home for elderly people. Basing on data from the year 2014, this contribution aims at analysing relevant spatial related information on 885 residential and nursing homes in urban and rural contexts in order to demonstrate how spatial related aspects are considered in the facilities’ presentations and how they illustrate the level of community integration of these in-patient offers, to understand facility-specific future plans as well as to reveal important questions and define urgent research demand and to stimulate the interdisciplinary and cross-cutting dialogue.

Multisensor satellite data for water quality analysis and water pollution risk assessment: decision making under deep uncertainty with fuzzy algorithm in framework of multimodel approach

NASA Astrophysics Data System (ADS)

Kostyuchenko, Yuriy V.; Sztoyka, Yulia; Kopachevsky, Ivan; Artemenko, Igor; Yuschenko, Maxim

2017-10-01

Multi-model approach for remote sensing data processing and interpretation is described. The problem of satellite data utilization in multi-modeling approach for socio-ecological risks assessment is formally defined. Observation, measurement and modeling data utilization method in the framework of multi-model approach is described. Methodology and models of risk assessment in framework of decision support approach are defined and described. Method of water quality assessment using satellite observation data is described. Method is based on analysis of spectral reflectance of aquifers. Spectral signatures of freshwater bodies and offshores are analyzed. Correlations between spectral reflectance, pollutions and selected water quality parameters are analyzed and quantified. Data of MODIS, MISR, AIRS and Landsat sensors received in 2002-2014 have been utilized verified by in-field spectrometry and lab measurements. Fuzzy logic based approach for decision support in field of water quality degradation risk is discussed. Decision on water quality category is making based on fuzzy algorithm using limited set of uncertain parameters. Data from satellite observations, field measurements and modeling is utilizing in the framework of the approach proposed. It is shown that this algorithm allows estimate water quality degradation rate and pollution risks. Problems of construction of spatial and temporal distribution of calculated parameters, as well as a problem of data regularization are discussed. Using proposed approach, maps of surface water pollution risk from point and diffuse sources are calculated and discussed.

The Modular Modeling System (MMS): A modeling framework for water- and environmental-resources management

USGS Publications Warehouse

Leavesley, G.H.; Markstrom, S.L.; Viger, R.J.

2004-01-01

The interdisciplinary nature and increasing complexity of water- and environmental-resource problems require the use of modeling approaches that can incorporate knowledge from a broad range of scientific disciplines. The large number of distributed hydrological and ecosystem models currently available are composed of a variety of different conceptualizations of the associated processes they simulate. Assessment of the capabilities of these distributed models requires evaluation of the conceptualizations of the individual processes, and the identification of which conceptualizations are most appropriate for various combinations of criteria, such as problem objectives, data constraints, and spatial and temporal scales of application. With this knowledge, "optimal" models for specific sets of criteria can be created and applied. The U.S. Geological Survey (USGS) Modular Modeling System (MMS) is an integrated system of computer software that has been developed to provide these model development and application capabilities. MMS supports the integration of models and tools at a variety of levels of modular design. These include individual process models, tightly coupled models, loosely coupled models, and fully-integrated decision support systems. A variety of visualization and statistical tools are also provided. MMS has been coupled with the Bureau of Reclamation (BOR) object-oriented reservoir and river-system modeling framework, RiverWare, under a joint USGS-BOR program called the Watershed and River System Management Program. MMS and RiverWare are linked using a shared relational database. The resulting database-centered decision support system provides tools for evaluating and applying optimal resource-allocation and management strategies to complex, operational decisions on multipurpose reservoir systems and watersheds. Management issues being addressed include efficiency of water-resources management, environmental concerns such as meeting flow needs for endangered species, and optimizing operations within the constraints of multiple objectives such as power generation, irrigation, and water conservation. This decision support system approach is being developed, tested, and implemented in the Gunni-son, Yakima, San Juan, Rio Grande, and Truckee River basins of the western United States. Copyright ASCE 2004.

SPATIAL PREDICTION USING COMBINED SOURCES OF DATA

EPA Science Inventory

For improved environmental decision-making, it is important to develop new models for spatial prediction that accurately characterize important spatial and temporal patterns of air pollution. As the U .S. Environmental Protection Agency begins to use spatial prediction in the reg...

Modeling spatial decisions with graph theory: logging roads and forest fragmentation in the Brazilian Amazon.

PubMed

Walker, Robert; Arima, Eugenio; Messina, Joe; Soares-Filho, Britaldo; Perz, Stephen; Vergara, Dante; Sales, Marcio; Pereira, Ritaumaria; Castro, Williams

2013-01-01

This article addresses the spatial decision-making of loggers and implications for forest fragmentation in the Amazon basin. It provides a behavioral explanation for fragmentation by modeling how loggers build road networks, typically abandoned upon removal of hardwoods. Logging road networks provide access to land, and the settlers who take advantage of them clear fields and pastures that accentuate their spatial signatures. In shaping agricultural activities, these networks organize emergent patterns of forest fragmentation, even though the loggers move elsewhere. The goal of the article is to explicate how loggers shape their road networks, in order to theoretically explain an important type of forest fragmentation found in the Amazon basin, particularly in Brazil. This is accomplished by adapting graph theory to represent the spatial decision-making of loggers, and by implementing computational algorithms that build graphs interpretable as logging road networks. The economic behavior of loggers is conceptualized as a profit maximization problem, and translated into spatial decision-making by establishing a formal correspondence between mathematical graphs and road networks. New computational approaches, adapted from operations research, are used to construct graphs and simulate spatial decision-making as a function of discount rates, land tenure, and topographic constraints. The algorithms employed bracket a range of behavioral settings appropriate for areas of terras de volutas, public lands that have not been set aside for environmental protection, indigenous peoples, or colonization. The simulation target sites are located in or near so-called Terra do Meio, once a major logging frontier in the lower Amazon Basin. Simulation networks are compared to empirical ones identified by remote sensing and then used to draw inferences about factors influencing the spatial behavior of loggers. Results overall suggest that Amazonia's logging road networks induce more fragmentation than necessary to access fixed quantities of wood. The paper concludes by considering implications of the approach and findings for Brazil's move to a system of concession logging.

Development, deployment and usability of a point-of-care decision support system for chronic disease management using the recently-approved HL7 decision support service standard.

PubMed

Lobach, David F; Kawamoto, Kensaku; Anstrom, Kevin J; Russell, Michael L; Woods, Peter; Smith, Dwight

2007-01-01

Clinical decision support is recognized as one potential remedy for the growing crisis in healthcare quality in the United States and other industrialized nations. While decision support systems have been shown to improve care quality and reduce errors, these systems are not widely available. This lack of availability arises in part because most decision support systems are not portable or scalable. The Health Level 7 international standard development organization recently adopted a draft standard known as the Decision Support Service standard to facilitate the implementation of clinical decision support systems using software services. In this paper, we report the first implementation of a clinical decision support system using this new standard. This system provides point-of-care chronic disease management for diabetes and other conditions and is deployed throughout a large regional health system. We also report process measures and usability data concerning the system. Use of the Decision Support Service standard provides a portable and scalable approach to clinical decision support that could facilitate the more extensive use of decision support systems.

How Decision Support Systems Can Benefit from a Theory of Change Approach.

PubMed

Allen, Will; Cruz, Jennyffer; Warburton, Bruce

2017-06-01

Decision support systems are now mostly computer and internet-based information systems designed to support land managers with complex decision-making. However, there is concern that many environmental and agricultural decision support systems remain underutilized and ineffective. Recent efforts to improve decision support systems use have focused on enhancing stakeholder participation in their development, but a mismatch between stakeholders' expectations and the reality of decision support systems outputs continues to limit uptake. Additional challenges remain in problem-framing and evaluation. We propose using an outcomes-based approach called theory of change in conjunction with decision support systems development to support both wider problem-framing and outcomes-based monitoring and evaluation. The theory of change helps framing by placing the decision support systems within a wider context. It highlights how decision support systems use can "contribute" to long-term outcomes, and helps align decision support systems outputs with these larger goals. We illustrate the benefits of linking decision support systems development and application with a theory of change approach using an example of pest rabbit management in Australia. We develop a theory of change that outlines the activities required to achieve the outcomes desired from an effective rabbit management program, and two decision support systems that contribute to specific aspects of decision making in this wider problem context. Using a theory of change in this way should increase acceptance of the role of decision support systems by end-users, clarify their limitations and, importantly, increase effectiveness of rabbit management. The use of a theory of change should benefit those seeking to improve decision support systems design, use and, evaluation.

How Decision Support Systems Can Benefit from a Theory of Change Approach

NASA Astrophysics Data System (ADS)

Allen, Will; Cruz, Jennyffer; Warburton, Bruce

2017-06-01

Decision support systems are now mostly computer and internet-based information systems designed to support land managers with complex decision-making. However, there is concern that many environmental and agricultural decision support systems remain underutilized and ineffective. Recent efforts to improve decision support systems use have focused on enhancing stakeholder participation in their development, but a mismatch between stakeholders' expectations and the reality of decision support systems outputs continues to limit uptake. Additional challenges remain in problem-framing and evaluation. We propose using an outcomes-based approach called theory of change in conjunction with decision support systems development to support both wider problem-framing and outcomes-based monitoring and evaluation. The theory of change helps framing by placing the decision support systems within a wider context. It highlights how decision support systems use can "contribute" to long-term outcomes, and helps align decision support systems outputs with these larger goals. We illustrate the benefits of linking decision support systems development and application with a theory of change approach using an example of pest rabbit management in Australia. We develop a theory of change that outlines the activities required to achieve the outcomes desired from an effective rabbit management program, and two decision support systems that contribute to specific aspects of decision making in this wider problem context. Using a theory of change in this way should increase acceptance of the role of decision support systems by end-users, clarify their limitations and, importantly, increase effectiveness of rabbit management. The use of a theory of change should benefit those seeking to improve decision support systems design, use and, evaluation.

Decision Support Tool Evaluation Report for General NOAA Oil Modeling Environment(GNOME) Version 2.0

NASA Technical Reports Server (NTRS)

Spruce, Joseph P.; Hall, Callie; Zanoni, Vicki; Blonski, Slawomir; D'Sa, Eurico; Estep, Lee; Holland, Donald; Moore, Roxzana F.; Pagnutti, Mary; Terrie, Gregory

2004-01-01

NASA's Earth Science Applications Directorate evaluated the potential of NASA remote sensing data and modeling products to enhance the General NOAA Oil Modeling Environment (GNOME) decision support tool. NOAA's Office of Response and Restoration (OR&R) Hazardous Materials (HAZMAT) Response Division is interested in enhancing GNOME with near-realtime (NRT) NASA remote sensing products on oceanic winds and ocean circulation. The NASA SeaWinds sea surface wind and Jason-1 sea surface height NRT products have potential, as do sea surface temperature and reflectance products from the Moderate Resolution Imaging Spectroradiometer and sea surface reflectance products from Landsat and the Advanced Spaceborne Thermal Emission and Reflectance Radiometer. HAZMAT is also interested in the Advanced Circulation model and the Ocean General Circulation Model. Certain issues must be considered, including lack of data continuity, marginal data redundancy, and data formatting problems. Spatial resolution is an issue for near-shore GNOME applications. Additional work will be needed to incorporate NASA inputs into GNOME, including verification and validation of data products, algorithms, models, and NRT data.

Application of an enhanced spill management information system to inland waterways.

PubMed

Camp, Janey S; LeBoeuf, Eugene J; Abkowitz, Mark D

2010-03-15

Spill response managers on inland waterways have indicated the need for an improved decision-support system, one that provides advanced modeling technology within a visual framework. Efforts to address these considerations led the authors to develop an enhanced version of the Spill Management Information System (SMIS 2.0). SMIS 2.0 represents a state-of-the-art 3D hydrodynamic and chemical spill modeling system tool that provides for improved predictive spill fate and transport capability, combined with a geographic information systems (GIS) spatial environment in which to communicate propagation risks and locate response resources. This paper focuses on the application of SMIS 2.0 in a case study of several spill scenarios involving the release of diesel fuel and trichloroethylene (TCE) that were simulated on the Kentucky Lake portion of the Tennessee River, each analyzed at low, average, and high flow conditions. A discussion of the decision-support implications of the model results is also included, as are suggestions for future enhancements to this evolving platform. (c) 2009 Elsevier B.V. All rights reserved.

Multi-criteria GIS-based siting of an incineration plant for municipal solid waste.

PubMed

Tavares, Gilberto; Zsigraiová, Zdena; Semiao, Viriato

2011-01-01

Siting a municipal solid waste (MSW) incineration plant requires a comprehensive evaluation to identify the best available location(s) that can simultaneously meet the requirements of regulations and minimise economic, environmental, health, and social costs. A spatial multi-criteria evaluation methodology is presented to assess land suitability for a plant siting and applied to Santiago Island of Cape Verde. It combines the analytical hierarchy process (AHP) to estimate the selected evaluation criteria weights with Geographic Information Systems (GIS) for spatial data analysis that avoids the subjectivity of the judgements of decision makers in establishing the influences between some criteria or clusters of criteria. An innovative feature of the method lies in incorporating the environmental impact assessment of the plant operation as a criterion in the decision-making process itself rather than as an a posteriori assessment. Moreover, a two-scale approach is considered. At a global scale an initial screening identifies inter-municipal zones satisfying the decisive requirements (socio-economic, technical and environmental issues, with weights respectively, of 48%, 41% and 11%). A detailed suitability ranking inside the previously identified zones is then performed at a local scale in two phases and includes environmental assessment of the plant operation. Those zones are ranked by combining the non-environmental feasibility of Phase 1 (with a weight of 75%) with the environmental assessment of the plant operation impact of Phase 2 (with a weight of 25%). The reliability and robustness of the presented methodology as a decision supporting tool is assessed through a sensitivity analysis. The results proved the system effectiveness in the ranking process. Copyright © 2011 Elsevier Ltd. All rights reserved.

Decision Support | Solar Research | NREL

Science.gov Websites

informed solar decision making with credible, objective, accessible, and timely resources. Solar Energy Decision Support Decision Support NREL provides technical and analytical support to support provide unbiased information on solar policies and issues for state and local government decision makers

User needs elicitation via analytic hierarchy process (AHP). A case study on a Computed Tomography (CT) scanner.

PubMed

Pecchia, Leandro; Martin, Jennifer L; Ragozzino, Angela; Vanzanella, Carmela; Scognamiglio, Arturo; Mirarchi, Luciano; Morgan, Stephen P

2013-01-05

The rigorous elicitation of user needs is a crucial step for both medical device design and purchasing. However, user needs elicitation is often based on qualitative methods whose findings can be difficult to integrate into medical decision-making. This paper describes the application of AHP to elicit user needs for a new CT scanner for use in a public hospital. AHP was used to design a hierarchy of 12 needs for a new CT scanner, grouped into 4 homogenous categories, and to prepare a paper questionnaire to investigate the relative priorities of these. The questionnaire was completed by 5 senior clinicians working in a variety of clinical specialisations and departments in the same Italian public hospital. Although safety and performance were considered the most important issues, user needs changed according to clinical scenario. For elective surgery, the five most important needs were: spatial resolution, processing software, radiation dose, patient monitoring, and contrast medium. For emergency, the top five most important needs were: patient monitoring, radiation dose, contrast medium control, speed run, spatial resolution. AHP effectively supported user need elicitation, helping to develop an analytic and intelligible framework of decision-making. User needs varied according to working scenario (elective versus emergency medicine) more than clinical specialization. This method should be considered by practitioners involved in decisions about new medical technology, whether that be during device design or before deciding whether to allocate budgets for new medical devices according to clinical functions or according to hospital department.

Barriers to and facilitators of implementing shared decision making and decision support in a paediatric hospital: A descriptive study.

PubMed

Boland, Laura; McIsaac, Daniel I; Lawson, Margaret L

2016-04-01

To explore multiple stakeholders' perceived barriers to and facilitators of implementing shared decision making and decision support in a tertiary paediatric hospital. An interpretive descriptive qualitative study was conducted using focus groups and interviews to examine senior hospital administrators', clinicians', parents' and youths' perceived barriers to and facilitators of shared decision making and decision support implementation. Data were analyzed using inductive thematic analysis. Fifty-seven stakeholders participated. Six barrier and facilitator themes emerged. The main barrier was gaps in stakeholders' knowledge of shared decision making and decision support. Facilitators included compatibility between shared decision making and the hospital's culture and ideal practices, perceptions of positive patient and family outcomes associated with shared decision making, and positive attitudes regarding shared decision making and decision support. However, youth attitudes regarding the necessity and usefulness of a decision support program were a barrier. Two themes were both a barrier and a facilitator. First, stakeholder groups were uncertain which clinical situations are suitable for shared decision making (eg, new diagnoses, chronic illnesses, complex decisions or urgent decisions). Second, the clinical process may be hindered if shared decision making and decision support decrease efficiency and workflow; however, shared decision making may reduce repeat visits and save time over the long term. Specific knowledge translation strategies that improve shared decision making knowledge and match specific barriers identified by each stakeholder group may be required to promote successful shared decision making and decision support implementation in the authors' paediatric hospital.

Mathematical models application for mapping soils spatial distribution on the example of the farm from the North of Udmurt Republic of Russia

NASA Astrophysics Data System (ADS)

Dokuchaev, P. M.; Meshalkina, J. L.; Yaroslavtsev, A. M.

2018-01-01

Comparative analysis of soils geospatial modeling using multinomial logistic regression, decision trees, random forest, regression trees and support vector machines algorithms was conducted. The visual interpretation of the digital maps obtained and their comparison with the existing map, as well as the quantitative assessment of the individual soil groups detection overall accuracy and of the models kappa showed that multiple logistic regression, support vector method, and random forest models application with spatial prediction of the conditional soil groups distribution can be reliably used for mapping of the study area. It has shown the most accurate detection for sod-podzolics soils (Phaeozems Albic) lightly eroded and moderately eroded soils. In second place, according to the mean overall accuracy of the prediction, there are sod-podzolics soils - non-eroded and warp one, as well as sod-gley soils (Umbrisols Gleyic) and alluvial soils (Fluvisols Dystric, Umbric). Heavy eroded sod-podzolics and gray forest soils (Phaeozems Albic) were detected by methods of automatic classification worst of all.

Navigating Monogamy: Nonapeptide Sensitivity in a Memory Neural Circuit May Shape Social Behavior and Mating Decisions.

PubMed

Ophir, Alexander G

2017-01-01

The role of memory in mating systems is often neglected despite the fact that most mating systems are defined in part by how animals use space. Monogamy, for example, is usually characterized by affiliative (e.g., pairbonding) and defensive (e.g., mate guarding) behaviors, but a high degree of spatial overlap in home range use is the easiest defining feature of monogamous animals in the wild. The nonapeptides vasopressin and oxytocin have been the focus of much attention for their importance in modulating social behavior, however this work has largely overshadowed their roles in learning and memory. To date, the understanding of memory systems and mechanisms governing social behavior have progressed relatively independently. Bridging these two areas will provide a deeper appreciation for understanding behavior, and in particular the mechanisms that mediate reproductive decision-making. Here, I argue that the ability to mate effectively as monogamous individuals is linked to the ability to track conspecifics in space. I discuss the connectivity across some well-known social and spatial memory nuclei, and propose that the nonapeptide receptors within these structures form a putative "socio-spatial memory neural circuit." This purported circuit may function to integrate social and spatial information to shape mating decisions in a context-dependent fashion. The lateral septum and/or the nucleus accumbens, and neuromodulation therein, may act as an intermediary to relate socio-spatial information with social behavior. Identifying mechanisms responsible for relating information about the social world with mechanisms mediating mating tactics is crucial to fully appreciate the suite of factors driving reproductive decisions and social decision-making.

Performance evaluation of the machine learning algorithms used in inference mechanism of a medical decision support system.

PubMed

Bal, Mert; Amasyali, M Fatih; Sever, Hayri; Kose, Guven; Demirhan, Ayse

2014-01-01

The importance of the decision support systems is increasingly supporting the decision making process in cases of uncertainty and the lack of information and they are widely used in various fields like engineering, finance, medicine, and so forth, Medical decision support systems help the healthcare personnel to select optimal method during the treatment of the patients. Decision support systems are intelligent software systems that support decision makers on their decisions. The design of decision support systems consists of four main subjects called inference mechanism, knowledge-base, explanation module, and active memory. Inference mechanism constitutes the basis of decision support systems. There are various methods that can be used in these mechanisms approaches. Some of these methods are decision trees, artificial neural networks, statistical methods, rule-based methods, and so forth. In decision support systems, those methods can be used separately or a hybrid system, and also combination of those methods. In this study, synthetic data with 10, 100, 1000, and 2000 records have been produced to reflect the probabilities on the ALARM network. The accuracy of 11 machine learning methods for the inference mechanism of medical decision support system is compared on various data sets.

GIS-Based Suitability Model for Assessment of Forest Biomass Energy Potential in a Region of Portugal

NASA Astrophysics Data System (ADS)

Quinta-Nova, Luis; Fernandez, Paulo; Pedro, Nuno

2017-12-01

This work focuses on developed a decision support system based on multicriteria spatial analysis to assess the potential for generation of biomass residues from forestry sources in a region of Portugal (Beira Baixa). A set of environmental, economic and social criteria was defined, evaluated and weighted in the context of Saaty’s analytic hierarchies. The best alternatives were obtained after applying Analytic Hierarchy Process (AHP). The model was applied to the central region of Portugal where forest and agriculture are the most representative land uses. Finally, sensitivity analysis of the set of factors and their associated weights was performed to test the robustness of the model. The proposed evaluation model provides a valuable reference for decision makers in establishing a standardized means of selecting the optimal location for new biomass plants.

On the Science-Policy Bridge: Do Spatial Heat Vulnerability Assessment Studies Influence Policy?

PubMed Central

Wolf, Tanja; Chuang, Wen-Ching; McGregor, Glenn

2015-01-01

Human vulnerability to heat varies at a range of spatial scales, especially within cities where there can be noticeable intra-urban differences in heat risk factors. Mapping and visualizing intra-urban heat vulnerability offers opportunities for presenting information to support decision-making. For example the visualization of the spatial variation of heat vulnerability has the potential to enable local governments to identify hot spots of vulnerability and allocate resources and increase assistance to people in areas of greatest need. Recently there has been a proliferation of heat vulnerability mapping studies, all of which, to varying degrees, justify the process of vulnerability mapping in a policy context. However, to date, there has not been a systematic review of the extent to which the results of vulnerability mapping studies have been applied in decision-making. Accordingly we undertook a comprehensive review of 37 recently published papers that use geospatial techniques for assessing human vulnerability to heat. In addition, we conducted an anonymous survey of the lead authors of the 37 papers in order to establish the level of interaction between the researchers as science information producers and local authorities as information users. Both paper review and author survey results show that heat vulnerability mapping has been used in an attempt to communicate policy recommendations, raise awareness and induce institutional networking and learning, but has not as yet had a substantive influence on policymaking or preventive action. PMID:26512681

The End-to-end Demonstrator for improved decision making in the water sector in Europe (EDgE)

NASA Astrophysics Data System (ADS)

Wood, Eric; Wanders, Niko; Pan, Ming; Sheffield, Justin; Samaniego, Luis; Thober, Stephan; Kumar, Rohinni; Prudhomme, Christel; Houghton-Carr, Helen

2017-04-01

High-resolution simulations of water resources from hydrological models are vital to supporting important climate services. Apart from a high level of detail, both spatially and temporally, it is important to provide simulations that consistently cover a range of timescales, from historical reanalysis to seasonal forecast and future projections. In the new EDgE project commissioned by the ECMWF (C3S) we try to fulfill these requirements. EDgE is a proof-of-concept project which combines climate data and state-of-the-art hydrological modelling to demonstrate a water-oriented information system implemented through a web application. EDgE is working with key European stakeholders representative of private and public sectors to jointly develop and tailor approaches and techniques. With these tools, stakeholders are assisted in using improved climate information in decision-making, and supported in the development of climate change adaptation and mitigation policies. Here, we present the first results of the EDgE modelling chain, which is divided into three main processes: 1) pre-processing and downscaling; 2) hydrological modelling; 3) post-processing. Consistent downscaling and bias corrections for historical simulations, seasonal forecasts and climate projections ensure that the results across scales are robust. The daily temporal resolution and 5km spatial resolution ensure locally relevant simulations. With the use of four hydrological models (PCR-GLOBWB, VIC, mHM, Noah-MP), uncertainty between models is properly addressed, while consistency is guaranteed by using identical input data for static land surface parameterizations. The forecast results are communicated to stakeholders via Sectoral Climate Impact Indicators (SCIIs) that have been created in collaboration with the end-user community of the EDgE project. The final product of this project is composed of 15 years of seasonal forecast and 10 climate change projections, all combined with four hydrological models. These unique high-resolution climate information simulations in the EDgE project provide an unprecedented information system for decision-making over Europe.

Causal modelling applied to the risk assessment of a wastewater discharge.

PubMed

Paul, Warren L; Rokahr, Pat A; Webb, Jeff M; Rees, Gavin N; Clune, Tim S

2016-03-01

Bayesian networks (BNs), or causal Bayesian networks, have become quite popular in ecological risk assessment and natural resource management because of their utility as a communication and decision-support tool. Since their development in the field of artificial intelligence in the 1980s, however, Bayesian networks have evolved and merged with structural equation modelling (SEM). Unlike BNs, which are constrained to encode causal knowledge in conditional probability tables, SEMs encode this knowledge in structural equations, which is thought to be a more natural language for expressing causal information. This merger has clarified the causal content of SEMs and generalised the method such that it can now be performed using standard statistical techniques. As it was with BNs, the utility of this new generation of SEM in ecological risk assessment will need to be demonstrated with examples to foster an understanding and acceptance of the method. Here, we applied SEM to the risk assessment of a wastewater discharge to a stream, with a particular focus on the process of translating a causal diagram (conceptual model) into a statistical model which might then be used in the decision-making and evaluation stages of the risk assessment. The process of building and testing a spatial causal model is demonstrated using data from a spatial sampling design, and the implications of the resulting model are discussed in terms of the risk assessment. It is argued that a spatiotemporal causal model would have greater external validity than the spatial model, enabling broader generalisations to be made regarding the impact of a discharge, and greater value as a tool for evaluating the effects of potential treatment plant upgrades. Suggestions are made on how the causal model could be augmented to include temporal as well as spatial information, including suggestions for appropriate statistical models and analyses.

Solutions Network Formulation Report. NASA's Potential Contributions using ASTER Data in Marine Hazard Mitigation

NASA Technical Reports Server (NTRS)

Fletcher, Rose

2010-01-01

The 28-foot storm surge from Hurricane Katrina pushed inland along bays and rivers for a distance of 12 miles in some areas, contributing to the damage or destruction of about half of the fleet of boats in coastal Mississippi. Most of those boats had sought refuge in back bays and along rivers. Some boats were spared damage because the owners chose their mooring site well. Gulf mariners need a spatial analysis tool that provides guidance on the safest places to anchor their boats during future hurricanes. This product would support NOAA s mission to minimize the effects of coastal hazards through awareness, education, and mitigation strategies and could be incorporated in the Coastal Risk Atlas decision support tool.

Episodic Future Thinking: Mechanisms and Functions.

PubMed

Schacter, Daniel L; Benoit, Roland G; Szpunar, Karl K

2017-10-01

Episodic future thinking refers to the capacity to imagine or simulate experiences that might occur in one's personal future. Cognitive, neuropsychological, and neuroimaging research concerning episodic future thinking has accelerated during recent years. This article discusses research that has delineated cognitive and neural mechanisms that support episodic future thinking as well as the functions that episodic future thinking serves. Studies focused on mechanisms have identified a core brain network that underlies episodic future thinking and have begun to tease apart the relative contributions of particular regions in this network, and the specific cognitive processes that they support. Studies concerned with functions have identified several domains in which episodic future thinking produces performance benefits, including decision making, emotion regulation, prospective memory, and spatial navigation.

Developing and Testing an Online Tool for Teaching GIS Concepts Applied to Spatial Decision-Making

ERIC Educational Resources Information Center

Carver, Steve; Evans, Andy; Kingston, Richard

2004-01-01

The development and testing of a Web-based GIS e-learning resource is described. This focuses on the application of GIS for siting a nuclear waste disposal facility and the associated principles of spatial decision-making using Boolean and weighted overlay methods. Initial student experiences in using the system are analysed as part of a research…

Catching the right wave: evaluating wave energy resources and potential compatibility with existing marine and coastal uses.

PubMed

Kim, Choong-Ki; Toft, Jodie E; Papenfus, Michael; Verutes, Gregory; Guerry, Anne D; Ruckelshaus, Marry H; Arkema, Katie K; Guannel, Gregory; Wood, Spencer A; Bernhardt, Joanna R; Tallis, Heather; Plummer, Mark L; Halpern, Benjamin S; Pinsky, Malin L; Beck, Michael W; Chan, Francis; Chan, Kai M A; Levin, Phil S; Polasky, Stephen

2012-01-01

Many hope that ocean waves will be a source for clean, safe, reliable and affordable energy, yet wave energy conversion facilities may affect marine ecosystems through a variety of mechanisms, including competition with other human uses. We developed a decision-support tool to assist siting wave energy facilities, which allows the user to balance the need for profitability of the facilities with the need to minimize conflicts with other ocean uses. Our wave energy model quantifies harvestable wave energy and evaluates the net present value (NPV) of a wave energy facility based on a capital investment analysis. The model has a flexible framework and can be easily applied to wave energy projects at local, regional, and global scales. We applied the model and compatibility analysis on the west coast of Vancouver Island, British Columbia, Canada to provide information for ongoing marine spatial planning, including potential wave energy projects. In particular, we conducted a spatial overlap analysis with a variety of existing uses and ecological characteristics, and a quantitative compatibility analysis with commercial fisheries data. We found that wave power and harvestable wave energy gradually increase offshore as wave conditions intensify. However, areas with high economic potential for wave energy facilities were closer to cable landing points because of the cost of bringing energy ashore and thus in nearshore areas that support a number of different human uses. We show that the maximum combined economic benefit from wave energy and other uses is likely to be realized if wave energy facilities are sited in areas that maximize wave energy NPV and minimize conflict with existing ocean uses. Our tools will help decision-makers explore alternative locations for wave energy facilities by mapping expected wave energy NPV and helping to identify sites that provide maximal returns yet avoid spatial competition with existing ocean uses.

A GIS-based tool for an integrated assessment of spatial planning trade-offs with aquaculture.

PubMed

Gimpel, Antje; Stelzenmüller, Vanessa; Töpsch, Sandra; Galparsoro, Ibon; Gubbins, Matthew; Miller, David; Murillas, Arantza; Murray, Alexander G; Pınarbaşı, Kemal; Roca, Guillem; Watret, Robert

2018-06-15

The increasing demand for protein from aquaculture will trigger a global expansion of the sector in coastal and offshore waters. While contributing to food security, potential conflicts with other traditional activities such as fisheries or tourism are inevitable, thus calling for decision-support tools to assess aquaculture planning scenarios in a multi-use context. Here we introduce the AquaSpace tool, one of the first Geographic Information System (GIS)-based planning tools empowering an integrated assessment and mapping of 30 indicators reflecting economic, environmental, inter-sectorial and socio-cultural risks and opportunities for proposed aquaculture systems in a marine environment. A bottom-up process consulting more than 350 stakeholders from 10 countries across southern and northern Europe enabled the direct consideration of stakeholder needs when developing the GIS AddIn. The AquaSpace tool is an open source product and builds in the prospective use of open source datasets at a European scale, hence aiming to improve reproducibility and collaboration in aquaculture science and research. Tool outputs comprise detailed reports and graphics allowing key stakeholders such as planners or licensing authorities to evaluate and communicate alternative planning scenarios and to take more informed decisions. With the help of the German North Sea case study we demonstrate here the tool application at multiple spatial scales with different aquaculture systems and under a range of space-related development constraints. The computation of these aquaculture planning scenarios and the assessment of their trade-offs showed that it is entirely possible to identify aquaculture sites, that correspondent to multifarious potential challenges, for instance by a low conflict potential, a low risk of disease spread, a comparable high economic profit and a low impact on touristic attractions. We believe that a transparent visualisation of risks and opportunities of aquaculture planning scenarios helps an effective Marine Spatial Planning (MSP) process, supports the licensing process and simplifies investments. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Trade-offs across space, time, and ecosystem services

USGS Publications Warehouse

Rodriguez, J.P.; Beard, T.D.; Bennett, E.M.; Cumming, Graeme S.; Cork, S.J.; Agard, J.; Dobson, A.P.; Peterson, G.D.

2006-01-01

Ecosystem service (ES) trade-offs arise from management choices made by humans, which can change the type, magnitude, and relative mix of services provided by ecosystems. Trade-offs occur when the provision of one ES is reduced as a consequence of increased use of another ES. In some cases, a trade-off may be an explicit choice; but in others, trade-offs arise without premeditation or even awareness that they are taking place. Trade-offs in ES can be classified along three axes: spatial scale, temporal scale, and reversibility. Spatial scale refers to whether the effects of the trade-off are felt locally or at a distant location. Temporal scale refers to whether the effects take place relatively rapidly or slowly. Reversibility expresses the likelihood that the perturbed ES may return to its original state if the perturbation ceases. Across all four Millennium Ecosystem Assessment scenarios and selected case study examples, trade-off decisions show a preference for provisioning, regulating, or cultural services (in that order). Supporting services are more likely to be "taken for granted." Cultural ES are almost entirely unquantified in scenario modeling; therefore, the calculated model results do not fully capture losses of these services that occur in the scenarios. The quantitative scenario models primarily capture the services that are perceived by society as more important - provisioning and regulating ecosystem services - and thus do not fully capture trade-offs of cultural and supporting services. Successful management policies will be those that incorporate lessons learned from prior decisions into future management actions. Managers should complement their actions with monitoring programs that, in addition to monitoring the short-term provisions of services, also monitor the long-term evolution of slowly changing variables. Policies can then be developed to take into account ES trade-offs at multiple spatial and temporal scales. Successful strategies will recognize the inherent complexities of ecosystem management and will work to develop policies that minimize the effects of ES trade-offs. Copyright ?? 2006 by the author(s).

Mapping for the management of diffuse pollution risks related to agricultural plant protection practices: case of the Etang de l'Or catchment area in France.

PubMed

Mghirbi, Oussama; Bord, Jean-Paul; Le Grusse, Philippe; Mandart, Elisabeth; Fabre, Jacques

2018-03-08

Faced with health, environmental, and socio-economic issues related to the heavy use of pesticides, diffuse phytosanitary pollution becomes a major concern shared by all the field actors. These actors, namely the farmers and territorial managers, have expressed the need to implement decision support tools for the territorial management of diffuse pollution resulting from the plant protection practices and their impacts. To meet these steadily increasing requests, a cartographic analysis approach was implemented based on GIS which allows the spatialization of the diffuse pollution impacts related to plant protection practices on the Etang de l'Or catchment area in the South of France. Risk mapping represents a support-decision tool that enables the different field actors to identify and locate vulnerable areas, so as to determine action plans and agri-environmental measures depending on the context of the natural environment. This work shows that mapping is helpful for managing risks related to the use of pesticides in agriculture by employing indicators of pressure (TFI) and risk on the applicator's health (IRSA) and on the environment (IRTE). These indicators were designed to assess the impact of plant protection practices at various spatial scales (field, farm, etc.). The cartographic analysis of risks related to plant protection practices shows that diffuse pollution is unequally located in the North (known for its abundant garrigues and vineyards) and in the South of the Etang de l'Or catchment area (the Mauguio-Lunel agricultural plain known for its diversified cropping systems). This spatial inequity is essentially related to land use and agricultural production system. Indeed, the agricultural lands cover about 60% of the total catchment area. Consequently, this cartographic analysis helps the territorial actors with the implementation of strategies for managing risks of diffuse pollution related to pesticides use in agriculture, based on environmental and socio-economic issues and the characteristics of the natural environment.

Catching the Right Wave: Evaluating Wave Energy Resources and Potential Compatibility with Existing Marine and Coastal Uses

PubMed Central

Kim, Choong-Ki; Toft, Jodie E.; Papenfus, Michael; Verutes, Gregory; Guerry, Anne D.; Ruckelshaus, Marry H.; Arkema, Katie K.; Guannel, Gregory; Wood, Spencer A.; Bernhardt, Joanna R.; Tallis, Heather; Plummer, Mark L.; Halpern, Benjamin S.; Pinsky, Malin L.; Beck, Michael W.; Chan, Francis; Chan, Kai M. A.; Levin, Phil S.; Polasky, Stephen

2012-01-01

Many hope that ocean waves will be a source for clean, safe, reliable and affordable energy, yet wave energy conversion facilities may affect marine ecosystems through a variety of mechanisms, including competition with other human uses. We developed a decision-support tool to assist siting wave energy facilities, which allows the user to balance the need for profitability of the facilities with the need to minimize conflicts with other ocean uses. Our wave energy model quantifies harvestable wave energy and evaluates the net present value (NPV) of a wave energy facility based on a capital investment analysis. The model has a flexible framework and can be easily applied to wave energy projects at local, regional, and global scales. We applied the model and compatibility analysis on the west coast of Vancouver Island, British Columbia, Canada to provide information for ongoing marine spatial planning, including potential wave energy projects. In particular, we conducted a spatial overlap analysis with a variety of existing uses and ecological characteristics, and a quantitative compatibility analysis with commercial fisheries data. We found that wave power and harvestable wave energy gradually increase offshore as wave conditions intensify. However, areas with high economic potential for wave energy facilities were closer to cable landing points because of the cost of bringing energy ashore and thus in nearshore areas that support a number of different human uses. We show that the maximum combined economic benefit from wave energy and other uses is likely to be realized if wave energy facilities are sited in areas that maximize wave energy NPV and minimize conflict with existing ocean uses. Our tools will help decision-makers explore alternative locations for wave energy facilities by mapping expected wave energy NPV and helping to identify sites that provide maximal returns yet avoid spatial competition with existing ocean uses. PMID:23144824

a Case Study: Exploring Industrial Agglomeration of Manufacturing Industries in Shanghai Using Duranton and Overman's K-Density Function

NASA Astrophysics Data System (ADS)

Tian, S.; Wang, J.; Gui, Z.; Wu, H.; Wang, Y.

2017-09-01

There has wide academic and policy attention on the issue of scale economy and industrial agglomeration, with most of the attention paid to industrial geography concentration. This paper adopted a scale-independent and distance-based measurement method, K-density function or known as Duranton and Overman (DO) index, to study the manufacturing industries localization in Shanghai, which is the most representative economic development zone in China and East Asia. The result indicates the industry has a growing tendency of localization, and various spatial distribution patterns in different distances. Furthermore, the class of industry also show significant influence on the concentration pattern. Besides, the method has been coded and published on GeoCommerce, a visualization and analysis portal for industrial big data, to provide geoprocessing and spatial decision support.

Vulnerability assessment of urban ecosystems driven by water resources, human health and atmospheric environment

NASA Astrophysics Data System (ADS)

Shen, Jing; Lu, Hongwei; Zhang, Yang; Song, Xinshuang; He, Li

2016-05-01

As ecosystem management is a hotspot and urgent topic with increasing population growth and resource depletion. This paper develops an urban ecosystem vulnerability assessment method representing a new vulnerability paradigm for decision makers and environmental managers, as it's an early warning system to identify and prioritize the undesirable environmental changes in terms of natural, human, economic and social elements. The whole idea is to decompose a complex problem into sub-problem, and analyze each sub-problem, and then aggregate all sub-problems to solve this problem. This method integrates spatial context of Geographic Information System (GIS) tool, multi-criteria decision analysis (MCDA) method, ordered weighted averaging (OWA) operators, and socio-economic elements. Decision makers can find out relevant urban ecosystem vulnerability assessment results with different vulnerable attitude. To test the potential of the vulnerability methodology, it has been applied to a case study area in Beijing, China, where it proved to be reliable and consistent with the Beijing City Master Plan. The results of urban ecosystem vulnerability assessment can support decision makers in evaluating the necessary of taking specific measures to preserve the quality of human health and environmental stressors for a city or multiple cities, with identifying the implications and consequences of their decisions.

Visual scanning with or without spatial uncertainty and time-sharing performance

NASA Technical Reports Server (NTRS)

Liu, Yili; Wickens, Christopher D.

1989-01-01

An experiment is reported that examines the pattern of task interference between visual scanning as a sequential and selective attention process and other concurrent spatial or verbal processing tasks. A distinction is proposed between visual scanning with or without spatial uncertainty regarding the possible differential effects of these two types of scanning on interference with other concurrent processes. The experiment required the subject to perform a simulated primary tracking task, which was time-shared with a secondary spatial or verbal decision task. The relevant information that was needed to perform the decision tasks were displayed with or without spatial uncertainty. The experiment employed a 2 x 2 x 2 design with types of scanning (with or without spatial uncertainty), expected scanning distance (low/high), and codes of concurrent processing (spatial/verbal) as the three experimental factors. The results provide strong evidence that visual scanning as a spatial exploratory activity produces greater task interference with concurrent spatial tasks than with concurrent verbal tasks. Furthermore, spatial uncertainty in visual scanning is identified to be the crucial factor in producing this differential effect.

Spatial frequency characteristics at image decision-point locations for observers with different radiological backgrounds in lung nodule detection

NASA Astrophysics Data System (ADS)

Pietrzyk, Mariusz W.; Manning, David J.; Dix, Alan; Donovan, Tim

2009-02-01

Aim: The goal of the study is to determine the spatial frequency characteristics at locations in the image of overt and covert observers' decisions and find out if there are any similarities in different observers' groups: the same radiological experience group or the same accuracy scored level. Background: The radiological task is described as a visual searching decision making procedure involving visual perception and cognitive processing. Humans perceive the world through a number of spatial frequency channels, each sensitive to visual information carried by different spatial frequency ranges and orientations. Recent studies have shown that particular physical properties of local and global image-based elements are correlated with the performance and the level of experience of human observers in breast cancer and lung nodule detections. Neurological findings in visual perception were an inspiration for wavelet applications in vision research because the methodology tries to mimic the brain processing algorithms. Methods: The wavelet approach to the set of postero-anterior chest radiographs analysis has been used to characterize perceptual preferences observers with different levels of experience in the radiological task. Psychophysical methodology has been applied to track eye movements over the image, where particular ROIs related to the observers' fixation clusters has been analysed in the spaces frame by Daubechies functions. Results: Significance differences have been found between the spatial frequency characteristics at the location of different decisions.

The Teaching Decisions Simulation: An Interactive Vehicle for Mapping Teaching Decisions.

ERIC Educational Resources Information Center

Strang, Harold R.

1996-01-01

Describes the Teaching Decisions Simulation, a program that allows participants to make decisions regarding lesson plan activities and student and teacher spatial arrangement or interactions. Postlesson feedback includes variables such as completion time and performance measures. Experienced teachers exhibited more deliberation in completing the…

Creating and sharing clinical decision support content with Web 2.0: Issues and examples.

PubMed

Wright, Adam; Bates, David W; Middleton, Blackford; Hongsermeier, Tonya; Kashyap, Vipul; Thomas, Sean M; Sittig, Dean F

2009-04-01

Clinical decision support is a powerful tool for improving healthcare quality and patient safety. However, developing a comprehensive package of decision support interventions is costly and difficult. If used well, Web 2.0 methods may make it easier and less costly to develop decision support. Web 2.0 is characterized by online communities, open sharing, interactivity and collaboration. Although most previous attempts at sharing clinical decision support content have worked outside of the Web 2.0 framework, several initiatives are beginning to use Web 2.0 to share and collaborate on decision support content. We present case studies of three efforts: the Clinfowiki, a world-accessible wiki for developing decision support content; Partners Healthcare eRooms, web-based tools for developing decision support within a single organization; and Epic Systems Corporation's Community Library, a repository for sharing decision support content for customers of a single clinical system vendor. We evaluate the potential of Web 2.0 technologies to enable collaborative development and sharing of clinical decision support systems through the lens of three case studies; analyzing technical, legal and organizational issues for developers, consumers and organizers of clinical decision support content in Web 2.0. We believe the case for Web 2.0 as a tool for collaborating on clinical decision support content appears strong, particularly for collaborative content development within an organization.

Barriers to and facilitators of implementing shared decision making and decision support in a paediatric hospital: A descriptive study

PubMed Central

Boland, Laura; McIsaac, Daniel I; Lawson, Margaret L

2016-01-01

OBJECTIVE: To explore multiple stakeholders’ perceived barriers to and facilitators of implementing shared decision making and decision support in a tertiary paediatric hospital. METHODS: An interpretive descriptive qualitative study was conducted using focus groups and interviews to examine senior hospital administrators’, clinicians’, parents’ and youths’ perceived barriers to and facilitators of shared decision making and decision support implementation. Data were analyzed using inductive thematic analysis. RESULTS: Fifty-seven stakeholders participated. Six barrier and facilitator themes emerged. The main barrier was gaps in stakeholders’ knowledge of shared decision making and decision support. Facilitators included compatibility between shared decision making and the hospital’s culture and ideal practices, perceptions of positive patient and family outcomes associated with shared decision making, and positive attitudes regarding shared decision making and decision support. However, youth attitudes regarding the necessity and usefulness of a decision support program were a barrier. Two themes were both a barrier and a facilitator. First, stakeholder groups were uncertain which clinical situations are suitable for shared decision making (eg, new diagnoses, chronic illnesses, complex decisions or urgent decisions). Second, the clinical process may be hindered if shared decision making and decision support decrease efficiency and workflow; however, shared decision making may reduce repeat visits and save time over the long term. CONCLUSIONS: Specific knowledge translation strategies that improve shared decision making knowledge and match specific barriers identified by each stakeholder group may be required to promote successful shared decision making and decision support implementation in the authors’ paediatric hospital. PMID:27398058

A Satellite Data-Driven, Client-Server Decision Support Application for Agricultural Water Resources Management

NASA Technical Reports Server (NTRS)

Johnson, Lee F.; Maneta, Marco P.; Kimball, John S.

2016-01-01

Water cycle extremes such as droughts and floods present a challenge for water managers and for policy makers responsible for the administration of water supplies in agricultural regions. In addition to the inherent uncertainties associated with forecasting extreme weather events, water planners need to anticipate water demands and water user behavior in a typical circumstances. This requires the use decision support systems capable of simulating agricultural water demand with the latest available data. Unfortunately, managers from local and regional agencies often use different datasets of variable quality, which complicates coordinated action. In previous work we have demonstrated novel methodologies to use satellite-based observational technologies, in conjunction with hydro-economic models and state of the art data assimilation methods, to enable robust regional assessment and prediction of drought impacts on agricultural production, water resources, and land allocation. These methods create an opportunity for new, cost-effective analysis tools to support policy and decision-making over large spatial extents. The methods can be driven with information from existing satellite-derived operational products, such as the Satellite Irrigation Management Support system (SIMS) operational over California, the Cropland Data Layer (CDL), and using a modified light-use efficiency algorithm to retrieve crop yield from the synergistic use of MODIS and Landsat imagery. Here we present an integration of this modeling framework in a client-server architecture based on the Hydra platform. Assimilation and processing of resource intensive remote sensing data, as well as hydrologic and other ancillary information occur on the server side. This information is processed and summarized as attributes in water demand nodes that are part of a vector description of the water distribution network. With this architecture, our decision support system becomes a light weight 'app' that connects to the server to retrieve the latest information regarding water demands, land use, yields and hydrologic information required to run different management scenarios. Furthermore, this architecture ensures all agencies and teams involved in water management use the same, up-to-date information in their simulations.

A satellite data-driven, client-server decision support application for agricultural water resources management

NASA Astrophysics Data System (ADS)

Maneta, M. P.; Johnson, L.; Kimball, J. S.

2016-12-01

Water cycle extremes such as droughts and floods present a challenge for water managers and for policy makers responsible for the administration of water supplies in agricultural regions. In addition to the inherent uncertainties associated with forecasting extreme weather events, water planners need to anticipate water demands and water user behavior in atypical circumstances. This requires the use decision support systems capable of simulating agricultural water demand with the latest available data. Unfortunately, managers from local and regional agencies often use different datasets of variable quality, which complicates coordinated action. In previous work we have demonstrated novel methodologies to use satellite-based observational technologies, in conjunction with hydro-economic models and state of the art data assimilation methods, to enable robust regional assessment and prediction of drought impacts on agricultural production, water resources, and land allocation. These methods create an opportunity for new, cost-effective analysis tools to support policy and decision-making over large spatial extents. The methods can be driven with information from existing satellite-derived operational products, such as the Satellite Irrigation Management Support system (SIMS) operational over California, the Cropland Data Layer (CDL), and using a modified light-use efficiency algorithm to retrieve crop yield from the synergistic use of MODIS and Landsat imagery. Here we present an integration of this modeling framework in a client-server architecture based on the Hydra platform. Assimilation and processing of resource intensive remote sensing data, as well as hydrologic and other ancillary information occur on the server side. This information is processed and summarized as attributes in water demand nodes that are part of a vector description of the water distribution network. With this architecture, our decision support system becomes a light weight `app` that connects to the server to retrieve the latest information regarding water demands, land use, yields and hydrologic information required to run different management scenarios. Furthermore, this architecture ensures all agencies and teams involved in water management use the same, up-to-date information in their simulations.

Regional risk assessment approaches to land planning for industrial polluted areas in China: the Hulunbeier region case study.

PubMed

Li, Daiqing; Zhang, Chen; Pizzol, Lisa; Critto, Andrea; Zhang, Haibo; Lv, Shihai; Marcomini, Antonio

2014-04-01

The rapid industrial development and urbanization processes that occurred in China over the past 30years has increased dramatically the consumption of natural resources and raw materials, thus exacerbating the human pressure on environmental ecosystems. In result, large scale environmental pollution of soil, natural waters and urban air were recorded. The development of effective industrial planning to support regional sustainable economy development has become an issue of serious concern for local authorities which need to select safe sites for new industrial settlements (i.e. industrial plants) according to assessment approaches considering cumulative impacts, synergistic pollution effects and risks of accidental releases. In order to support decision makers in the development of efficient and effective regional land-use plans encompassing the identification of suitable areas for new industrial settlements and areas in need of intervention measures, this study provides a spatial regional risk assessment methodology which integrates relative risk assessment (RRA) and socio-economic assessment (SEA) and makes use of spatial analysis (GIS) methodologies and multicriteria decision analysis (MCDA) techniques. The proposed methodology was applied to the Chinese region of Hulunbeier which is located in eastern Inner Mongolia Autonomous Region, adjacent to the Republic of Mongolia. The application results demonstrated the effectiveness of the proposed methodology in the identification of the most hazardous and risky industrial settlements, the most vulnerable regional receptors and the regional districts which resulted to be the most relevant for intervention measures since they are characterized by high regional risk and excellent socio-economic development conditions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Strategy generalization across orientation tasks: testing a computational cognitive model.

PubMed

Gunzelmann, Glenn

2008-07-08

Humans use their spatial information processing abilities flexibly to facilitate problem solving and decision making in a variety of tasks. This article explores the question of whether a general strategy can be adapted for performing two different spatial orientation tasks by testing the predictions of a computational cognitive model. Human performance was measured on an orientation task requiring participants to identify the location of a target either on a map (find-on-map) or within an egocentric view of a space (find-in-scene). A general strategy instantiated in a computational cognitive model of the find-on-map task, based on the results from Gunzelmann and Anderson (2006), was adapted to perform both tasks and used to generate performance predictions for a new study. The qualitative fit of the model to the human data supports the view that participants were able to tailor a general strategy to the requirements of particular spatial tasks. The quantitative differences between the predictions of the model and the performance of human participants in the new experiment expose individual differences in sample populations. The model provides a means of accounting for those differences and a framework for understanding how human spatial abilities are applied to naturalistic spatial tasks that involve reasoning with maps. 2008 Cognitive Science Society, Inc.

Spatial effects on hybrid electric vehicle adoption

DOE PAGES

Liu, Xiaoli; Roberts, Matthew C.; Sioshansi, Ramteen

2017-03-08

This paper examines spatial effects on hybrid-electric vehicle (HEV) adoption. This is in contrast to most existing analyses, which concentrate on analyzing socioeconomic factors and demographics. This paper uses a general spatial model to estimate the strength of ‘neighbor effects’ on HEV adoption—namely that each consumer’s HEV-adoption decision can be influenced by the HEV-adoption decisions of geographic neighbors. We use detailed census tract-level demographic data from the 2010 United States Census and the 2012 American Community Survey and vehicle registration data collected by the Ohio Bureau of Motor Vehicles. We find that HEV adoption exhibits significant spatial effects. We furthermore » conduct a time-series analysis and show that historical HEV adoption has a spatial effect on future adoption. Lastly, these results suggest that HEVs may appear in more dense clusters than models that do not consider spatial effects predict.« less

Large scale Wyoming transportation data: a resource planning tool

USGS Publications Warehouse

O'Donnell, Michael S.; Fancher, Tammy S.; Freeman, Aaron T.; Ziegler, Abra E.; Bowen, Zachary H.; Aldridge, Cameron L.

2014-01-01

The U.S. Geological Survey Fort Collins Science Center created statewide roads data for the Bureau of Land Management Wyoming State Office using 2009 aerial photography from the National Agriculture Imagery Program. The updated roads data resolves known concerns of omission, commission, and inconsistent representation of map scale, attribution, and ground reference dates which were present in the original source data. To ensure a systematic and repeatable approach of capturing roads on the landscape using on-screen digitizing from true color National Agriculture Imagery Program imagery, we developed a photogrammetry key and quality assurance/quality control protocols. Therefore, the updated statewide roads data will support the Bureau of Land Management’s resource management requirements with a standardized map product representing 2009 ground conditions. The updated Geographic Information System roads data set product, represented at 1:4,000 and +/- 10 meters spatial accuracy, contains 425,275 kilometers within eight attribute classes. The quality control of these products indicated a 97.7 percent accuracy of aspatial information and 98.0 percent accuracy of spatial locations. Approximately 48 percent of the updated roads data was corrected for spatial errors of greater than 1 meter relative to the pre-existing road data. Twenty-six percent of the updated roads involved correcting spatial errors of greater than 5 meters and 17 percent of the updated roads involved correcting spatial errors of greater than 9 meters. The Bureau of Land Management, other land managers, and researchers can use these new statewide roads data set products to support important studies and management decisions regarding land use changes, transportation and planning needs, transportation safety, wildlife applications, and other studies.

Web-based GIS for spatial pattern detection: application to malaria incidence in Vietnam.

PubMed

Bui, Thanh Quang; Pham, Hai Minh

2016-01-01

There is a great concern on how to build up an interoperable health information system of public health and health information technology within the development of public information and health surveillance programme. Technically, some major issues remain regarding to health data visualization, spatial processing of health data, health information dissemination, data sharing and the access of local communities to health information. In combination with GIS, we propose a technical framework for web-based health data visualization and spatial analysis. Data was collected from open map-servers and geocoded by open data kit package and data geocoding tools. The Web-based system is designed based on Open-source frameworks and libraries. The system provides Web-based analyst tool for pattern detection through three spatial tests: Nearest neighbour, K function, and Spatial Autocorrelation. The result is a web-based GIS, through which end users can detect disease patterns via selecting area, spatial test parameters and contribute to managers and decision makers. The end users can be health practitioners, educators, local communities, health sector authorities and decision makers. This web-based system allows for the improvement of health related services to public sector users as well as citizens in a secure manner. The combination of spatial statistics and web-based GIS can be a solution that helps empower health practitioners in direct and specific intersectional actions, thus provide for better analysis, control and decision-making.

Electronic decision support for diagnostic imaging in a primary care setting

PubMed Central

Reed, Martin H

2011-01-01

Methods Clinical guideline adherence for diagnostic imaging (DI) and acceptance of electronic decision support in a rural community family practice clinic was assessed over 36 weeks. Physicians wrote 904 DI orders, 58% of which were addressed by the Canadian Association of Radiologists guidelines. Results Of those orders with guidelines, 76% were ordered correctly; 24% were inappropriate or unnecessary resulting in a prompt from clinical decision support. Physicians followed suggestions from decision support to improve their DI order on 25% of the initially inappropriate orders. The use of decision support was not mandatory, and there were significant variations in use rate. Initially, 40% reported decision support disruptive in their work flow, which dropped to 16% as physicians gained experience with the software. Conclusions Physicians supported the concept of clinical decision support but were reluctant to change clinical habits to incorporate decision support into routine work flow. PMID:21486884

Prefrontal spatial working memory network predicts animal's decision making in a free choice saccade task

PubMed Central

Mochizuki, Kei

2015-01-01

While neurons in the lateral prefrontal cortex (PFC) encode spatial information during the performance of working memory tasks, they are also known to participate in subjective behavior such as spatial attention and action selection. In the present study, we analyzed the activity of primate PFC neurons during the performance of a free choice memory-guided saccade task in which the monkeys needed to choose a saccade direction by themselves. In trials when the receptive field location was subsequently chosen by the animal, PFC neurons with spatially selective visual response started to show greater activation before cue onset. This result suggests that the fluctuation of firing before cue presentation prematurely biased the representation of a certain spatial location and eventually encouraged the subsequent choice of that location. In addition, modulation of the activity by the animal's choice was observed only in neurons with high sustainability of activation and was also dependent on the spatial configuration of the visual cues. These findings were consistent with known characteristics of PFC neurons in information maintenance in spatial working memory function. These results suggest that precue fluctuation of spatial representation was shared and enhanced through the working memory network in the PFC and could finally influence the animal's free choice of saccade direction. The present study revealed that the PFC plays an important role in decision making in a free choice condition and that the dynamics of decision making are constrained by the network architecture embedded in this cortical area. PMID:26490287

Bridging the Gap Between Surveyors and the Geo-Spatial Society

NASA Astrophysics Data System (ADS)

Müller, H.

2016-06-01

For many years FIG, the International Association of Surveyors, has been trying to bridge the gap between surveyors and the geospatial society as a whole, with the geospatial industries in particular. Traditionally the surveying profession contributed to the good of society by creating and maintaining highly precise and accurate geospatial data bases, based on an in-depth knowledge of spatial reference frameworks. Furthermore in many countries surveyors may be entitled to make decisions about land divisions and boundaries. By managing information spatially surveyors today develop into the role of geo-data managers, the longer the more. Job assignments in this context include data entry management, data and process quality management, design of formal and informal systems, information management, consultancy, land management, all that in close cooperation with many different stakeholders. Future tasks will include the integration of geospatial information into e-government and e-commerce systems. The list of professional tasks underpins the capabilities of surveyors to contribute to a high quality geospatial data and information management. In that way modern surveyors support the needs of a geo-spatial society. The paper discusses several approaches to define the role of the surveyor within the modern geospatial society.

Supporting end of life decision making: Case studies of relational closeness in supported decision making for people with severe or profound intellectual disability.

PubMed

Watson, Joanne; Wilson, Erin; Hagiliassis, Nick

2017-11-01

The United Nations Convention on the Rights of Persons with Disabilities (UNCRPD) promotes the use of supported decision making in lieu of substitute decision making. To date, there has been a lack of focus on supported decision making for people with severe or profound intellectual disability, including for end of life decisions. Five people with severe or profound intellectual disability's experiences of supported decision making were examined. This article is particularly focused on one participant's experiences at the end of his life. All five case studies identified that supporters were most effective in providing decision-making support for participants when they were relationally close to the person and had knowledge of the person's life story, particularly in relation to events that demonstrated preference. Findings from this study provide new understandings of supported decision making for people with severe or profound intellectual disability and have particular relevance for supporting decision making at the end of life. © 2017 John Wiley & Sons Ltd.

Internally generated hippocampal sequences as a vantage point to probe future-oriented cognition.

PubMed

Pezzulo, Giovanni; Kemere, Caleb; van der Meer, Matthijs A A

2017-05-01

Information processing in the rodent hippocampus is fundamentally shaped by internally generated sequences (IGSs), expressed during two different network states: theta sequences, which repeat and reset at the ∼8 Hz theta rhythm associated with active behavior, and punctate sharp wave-ripple (SWR) sequences associated with wakeful rest or slow-wave sleep. A potpourri of diverse functional roles has been proposed for these IGSs, resulting in a fragmented conceptual landscape. Here, we advance a unitary view of IGSs, proposing that they reflect an inferential process that samples a policy from the animal's generative model, supported by hippocampus-specific priors. The same inference affords different cognitive functions when the animal is in distinct dynamical modes, associated with specific functional networks. Theta sequences arise when inference is coupled to the animal's action-perception cycle, supporting online spatial decisions, predictive processing, and episode encoding. SWR sequences arise when the animal is decoupled from the action-perception cycle and may support offline cognitive processing, such as memory consolidation, the prospective simulation of spatial trajectories, and imagination. We discuss the empirical bases of this proposal in relation to rodent studies and highlight how the proposed computational principles can shed light on the mechanisms of future-oriented cognition in humans. © 2017 New York Academy of Sciences.

The Michelin red guide of the brain: role of dopamine in goal-oriented navigation.

PubMed

Retailleau, Aude; Boraud, Thomas

2014-01-01

Spatial learning has been recognized over the years to be under the control of the hippocampus and related temporal lobe structures. Hippocampal damage often causes severe impairments in the ability to learn and remember a location in space defined by distal visual cues. Such cognitive disabilities are found in Parkinsonian patients. We recently investigated the role of dopamine in navigation in the 6-Hydroxy-dopamine (6-OHDA) rat, a model of Parkinson's disease (PD) commonly used to investigate the pathophysiology of dopamine depletion (Retailleau et al., 2013). We demonstrated that dopamine (DA) is essential to spatial learning as its depletion results in spatial impairments. Our results showed that the behavioral effect of DA depletion is correlated with modification of the neural encoding of spatial features and decision making processes in hippocampus. However, the origin of these alterations in the neural processing of the spatial information needs to be clarified. It could result from a local effect: dopamine depletion disturbs directly the processing of relevant spatial information at hippocampal level. Alternatively, it could result from a more distributed network effect: dopamine depletion elsewhere in the brain (entorhinal cortex, striatum, etc.) modifies the way hippocampus processes spatial information. Recent experimental evidence in rodents, demonstrated indeed, that other brain areas are involved in the acquisition of spatial information. Amongst these, the cortex-basal ganglia (BG) loop is known to be involved in reinforcement learning and has been identified as an important contributor to spatial learning. In particular, it has been shown that altered activity of the BG striatal complex can impair the ability to perform spatial learning tasks. The present review provides a glimpse of the findings obtained over the past decade that support a dialog between these two structures during spatial learning under DA control.

Towards a geophysical decision-support system for monitoring and managing unstable slopes

NASA Astrophysics Data System (ADS)

Chambers, J. E.; Meldrum, P.; Wilkinson, P. B.; Uhlemann, S.; Swift, R. T.; Inauen, C.; Gunn, D.; Kuras, O.; Whiteley, J.; Kendall, J. M.

2017-12-01

Conventional approaches for condition monitoring, such as walk over surveys, remote sensing or intrusive sampling, are often inadequate for predicting instabilities in natural and engineered slopes. Surface observations cannot detect the subsurface precursors to failure events; instead they can only identify failure once it has begun. On the other hand, intrusive investigations using boreholes only sample a very small volume of ground and hence small scale deterioration process in heterogeneous ground conditions can easily be missed. It is increasingly being recognised that geophysical techniques can complement conventional approaches by providing spatial subsurface information. Here we describe the development and testing of a new geophysical slope monitoring system. It is built around low-cost electrical resistivity tomography instrumentation, combined with integrated geotechnical logging capability, and coupled with data telemetry. An automated data processing and analysis workflow is being developed to streamline information delivery. The development of this approach has provided the basis of a decision-support tool for monitoring and managing unstable slopes. The hardware component of the system has been operational at a number of field sites associated with a range of natural and engineered slopes for up to two years. We report on the monitoring results from these sites, discuss the practicalities of installing and maintaining long-term geophysical monitoring infrastructure, and consider the requirements of a fully automated data processing and analysis workflow. We propose that the result of this development work is a practical decision-support tool that can provide near-real-time information relating to the internal condition of problematic slopes.

Evaluation of Rgb-Based Vegetation Indices from Uav Imagery to Estimate Forage Yield in Grassland

NASA Astrophysics Data System (ADS)

Lussem, U.; Bolten, A.; Gnyp, M. L.; Jasper, J.; Bareth, G.

2018-04-01

Monitoring forage yield throughout the growing season is of key importance to support management decisions on grasslands/pastures. Especially on intensely managed grasslands, where nitrogen fertilizer and/or manure are applied regularly, precision agriculture applications are beneficial to support sustainable, site-specific management decisions on fertilizer treatment, grazing management and yield forecasting to mitigate potential negative impacts. To support these management decisions, timely and accurate information is needed on plant parameters (e.g. forage yield) with a high spatial and temporal resolution. However, in highly heterogeneous plant communities such as grasslands, assessing their in-field variability non-destructively to determine e.g. adequate fertilizer application still remains challenging. Especially biomass/yield estimation, as an important parameter in assessing grassland quality and quantity, is rather laborious. Forage yield (dry or fresh matter) is mostly measured manually with rising plate meters (RPM) or ultrasonic sensors (handheld or mounted on vehicles). Thus the in-field variability cannot be assessed for the entire field or only with potential disturbances. Using unmanned aerial vehicles (UAV) equipped with consumer grade RGB cameras in-field variability can be assessed by computing RGB-based vegetation indices. In this contribution we want to test and evaluate the robustness of RGB-based vegetation indices to estimate dry matter forage yield on a recently established experimental grassland site in Germany. Furthermore, the RGB-based VIs are compared to indices computed from the Yara N-Sensor. The results show a good correlation of forage yield with RGB-based VIs such as the NGRDI with R2 values of 0.62.

Developing an Analytical Framework: Incorporating Ecosystem Services into Decision Making - Proceedings of a Workshop

USGS Publications Warehouse

Hogan, Dianna; Arthaud, Greg; Pattison, Malka; Sayre, Roger G.; Shapiro, Carl

2010-01-01

The analytical framework for understanding ecosystem services in conservation, resource management, and development decisions is multidisciplinary, encompassing a combination of the natural and social sciences. This report summarizes a workshop on 'Developing an Analytical Framework: Incorporating Ecosystem Services into Decision Making,' which focused on the analytical process and on identifying research priorities for assessing ecosystem services, their production and use, their spatial and temporal characteristics, their relationship with natural systems, and their interdependencies. Attendees discussed research directions and solutions to key challenges in developing the analytical framework. The discussion was divided into two sessions: (1) the measurement framework: quantities and values, and (2) the spatial framework: mapping and spatial relationships. This workshop was the second of three preconference workshops associated with ACES 2008 (A Conference on Ecosystem Services): Using Science for Decision Making in Dynamic Systems. These three workshops were designed to explore the ACES 2008 theme on decision making and how the concept of ecosystem services can be more effectively incorporated into conservation, restoration, resource management, and development decisions. Preconference workshop 1, 'Developing a Vision: Incorporating Ecosystem Services into Decision Making,' was held on April 15, 2008, in Cambridge, MA. In preconference workshop 1, participants addressed what would have to happen to make ecosystem services be used more routinely and effectively in conservation, restoration, resource management, and development decisions, and they identified some key challenges in developing the analytical framework. Preconference workshop 3, 'Developing an Institutional Framework: Incorporating Ecosystem Services into Decision Making,' was held on October 30, 2008, in Albuquerque, NM; participants examined the relationship between the institutional framework and the use of ecosystem services in decision making.

Monitoring Drought Conditions in the Navajo Nation Using NASA Earth Observations

NASA Technical Reports Server (NTRS)

Ly, Vickie; Gao, Michael; Cary, Cheryl; Turnbull-Appell, Sophie; Surunis, Anton

2016-01-01

The Navajo Nation, a 65,700 sq km Native American territory located in the southwestern United States, has been increasingly impacted by severe drought events and changes in climate. These events are coupled with a lack of domestic water infrastructure and economic resources, leaving approximately one-third of the population without access to potable water in their homes. Current methods of monitoring drought are dependent on state-based monthly Standardized Precipitation Index value maps calculated by the Western Regional Climate Center. However, these maps do not provide the spatial resolution needed to illustrate differences in drought severity across the vast Nation. To better understand and monitor drought events and drought regime changes in the Navajo Nation, this project created a geodatabase of historical climate information specific to the area, and a decision support tool to calculate average Standardized Precipitation Index values for user-specified areas. The tool and geodatabase use Tropical Rainfall Monitoring Mission (TRMM) and Global Precipitation Monitor (GPM) observed precipitation data and Parameter-elevation Relationships on Independent Slopes Model modeled historical precipitation data, as well as NASA's modeled Land Data Assimilation Systems deep soil moisture, evaporation, and transpiration data products. The geodatabase and decision support tool will allow resource managers in the Navajo Nation to utilize current and future NASA Earth observation data for increased decision-making capacity regarding future climate change impact on water resources.

TEMPO Early Adopters in Air-Quality Forecasting, Planning and Assessment, Pollution Emissions, Health, Agriculture, and Environmental Impacts: Applications and Decision Support

NASA Astrophysics Data System (ADS)

Newchurch, M.; Zavodsky, B.; Chance, K.; Haynes, J.; Lefer, B. L.; Naeger, A.

2016-12-01

The AQ research community has a long legacy of using space-based observations (e.g., Solar Backscatter Ultraviolet Instrument [SBUV], Global Ozone Monitoring Experiment [GOME], Ozone Monitoring Instrument [OMI], and the Ozone Mapping & Profiler Suite [OMPS]) to study atmospheric chemistry. These measurements have been used to observe day-to-day and year-to-year changes in atmospheric constituents. However, they have not been able to capture the diurnal variability of pollution with enough temporal or spatial fidelity and a low enough latency for regular use by operational decision makers. As a result, the operational AQ community has traditionally relied on ground-based (e.g., collection stations, LIDAR) and airborne observing systems to study tropospheric chemistry. In order to maximize its utility for applications and decision support, there is a need to educate the community about the game-changing potential for the geostationary TEMPO mission well ahead of its expected launch date early in the third decade of this millinium. This NASA mission will engage user communities and enable science across the NASA Applied Science Focus Areas of Health and Air Quality, Disasters, Water Resources, and Ecological Forecasting, In addition, topics discussed will provide opportunities for collaborations extending TEMPO applications to future program areas in Agriculture, Weather and Climate (including Numerical Weather Prediction), Energy, and Oceans.

Contribution of Geographic Information Systems and location models to planning of wastewater systems.

PubMed

Leitão, J P; Matos, J S; Gonçalves, A B; Matos, J L

2005-01-01

This paper presents the contributions of Geographic Information Systems (GIS) and location models towards planning regional wastewater systems (sewers and wastewater treatment plants) serving small agglomerations, i.e. agglomerations with less than 2,000 inhabitants. The main goal was to develop a decision support tool for tracing and locating regional wastewater systems. The main results of the model are expressed in terms of number, capacity and location of Wastewater Treatment Plants (WWTP) and the length of main sewers. The decision process concerning the location and capacity of wastewater systems has a number of parameters that can be optimized. These parameters include the total sewer length and number, capacity and location of WWTP. The optimization of parameters should lead to the minimization of construction and operation costs of the integrated system. Location models have been considered as tools for decision support, mainly when a geo-referenced database can be used. In these cases, the GIS may represent an important role for the analysis of data and results especially in the preliminary stage of planning and design. After selecting the spatial location model and the heuristics, two greedy algorithms were implemented in Visual Basic for Applications on the ArcGIS software environment. To illustrate the application of these algorithms a case study was developed, in a rural area located in the central part of Portugal.

Navigating Monogamy: Nonapeptide Sensitivity in a Memory Neural Circuit May Shape Social Behavior and Mating Decisions

PubMed Central

Ophir, Alexander G.

2017-01-01

The role of memory in mating systems is often neglected despite the fact that most mating systems are defined in part by how animals use space. Monogamy, for example, is usually characterized by affiliative (e.g., pairbonding) and defensive (e.g., mate guarding) behaviors, but a high degree of spatial overlap in home range use is the easiest defining feature of monogamous animals in the wild. The nonapeptides vasopressin and oxytocin have been the focus of much attention for their importance in modulating social behavior, however this work has largely overshadowed their roles in learning and memory. To date, the understanding of memory systems and mechanisms governing social behavior have progressed relatively independently. Bridging these two areas will provide a deeper appreciation for understanding behavior, and in particular the mechanisms that mediate reproductive decision-making. Here, I argue that the ability to mate effectively as monogamous individuals is linked to the ability to track conspecifics in space. I discuss the connectivity across some well-known social and spatial memory nuclei, and propose that the nonapeptide receptors within these structures form a putative “socio-spatial memory neural circuit.” This purported circuit may function to integrate social and spatial information to shape mating decisions in a context-dependent fashion. The lateral septum and/or the nucleus accumbens, and neuromodulation therein, may act as an intermediary to relate socio-spatial information with social behavior. Identifying mechanisms responsible for relating information about the social world with mechanisms mediating mating tactics is crucial to fully appreciate the suite of factors driving reproductive decisions and social decision-making. PMID:28744194

An information theory analysis of spatial decisions in cognitive development

PubMed Central

Scott, Nicole M.; Sera, Maria D.; Georgopoulos, Apostolos P.

2015-01-01

Performance in a cognitive task can be considered as the outcome of a decision-making process operating across various knowledge domains or aspects of a single domain. Therefore, an analysis of these decisions in various tasks can shed light on the interplay and integration of these domains (or elements within a single domain) as they are associated with specific task characteristics. In this study, we applied an information theoretic approach to assess quantitatively the gain of knowledge across various elements of the cognitive domain of spatial, relational knowledge, as a function of development. Specifically, we examined changing spatial relational knowledge from ages 5 to 10 years. Our analyses consisted of a two-step process. First, we performed a hierarchical clustering analysis on the decisions made in 16 different tasks of spatial relational knowledge to determine which tasks were performed similarly at each age group as well as to discover how the tasks clustered together. We next used two measures of entropy to capture the gradual emergence of order in the development of relational knowledge. These measures of “cognitive entropy” were defined based on two independent aspects of chunking, namely (1) the number of clusters formed at each age group, and (2) the distribution of tasks across the clusters. We found that both measures of entropy decreased with age in a quadratic fashion and were positively and linearly correlated. The decrease in entropy and, therefore, gain of information during development was accompanied by improved performance. These results document, for the first time, the orderly and progressively structured “chunking” of decisions across the development of spatial relational reasoning and quantify this gain within a formal information-theoretic framework. PMID:25698915

MonitoringResources.org—Supporting coordinated and cost-effective natural resource monitoring across organizations

USGS Publications Warehouse

Bayer, Jennifer M.; Scully, Rebecca A.; Weltzin, Jake F.

2018-05-21

Natural resource managers who oversee the Nation’s resources require data to support informed decision-making at a variety of spatial and temporal scales that often cross typical jurisdictional boundaries such as states, agency regions, and watersheds. These data come from multiple agencies, programs, and sources, often with their own methods and standards for data collection and organization. Coordinating standards and methods is often prohibitively time-intensive and expensive. MonitoringResources.org offers a suite of tools and resources that support coordination of monitoring efforts, cost-effective planning, and sharing of knowledge among organizations. The website was developed by the Pacific Northwest Aquatic Monitoring Partnership—a collaboration of Federal, state, tribal, local, and private monitoring programs—and the U.S. Geological Survey (USGS), with funding from the Bonneville Power Administration and USGS. It is a key component of a coordinated monitoring and information network.

A multiple-point spatially weighted k-NN method for object-based classification

NASA Astrophysics Data System (ADS)

Tang, Yunwei; Jing, Linhai; Li, Hui; Atkinson, Peter M.

2016-10-01

Object-based classification, commonly referred to as object-based image analysis (OBIA), is now commonly regarded as able to produce more appealing classification maps, often of greater accuracy, than pixel-based classification and its application is now widespread. Therefore, improvement of OBIA using spatial techniques is of great interest. In this paper, multiple-point statistics (MPS) is proposed for object-based classification enhancement in the form of a new multiple-point k-nearest neighbour (k-NN) classification method (MPk-NN). The proposed method first utilises a training image derived from a pre-classified map to characterise the spatial correlation between multiple points of land cover classes. The MPS borrows spatial structures from other parts of the training image, and then incorporates this spatial information, in the form of multiple-point probabilities, into the k-NN classifier. Two satellite sensor images with a fine spatial resolution were selected to evaluate the new method. One is an IKONOS image of the Beijing urban area and the other is a WorldView-2 image of the Wolong mountainous area, in China. The images were object-based classified using the MPk-NN method and several alternatives, including the k-NN, the geostatistically weighted k-NN, the Bayesian method, the decision tree classifier (DTC), and the support vector machine classifier (SVM). It was demonstrated that the new spatial weighting based on MPS can achieve greater classification accuracy relative to the alternatives and it is, thus, recommended as appropriate for object-based classification.

Cognitive and behavioural dispositions in offspring at high risk for alcoholism.

PubMed

Kumar, Rajesh; Kumar, Keshav Janakiprasad; Benegal, Vivek

2018-06-01

Offspring with family history of alcoholism are considered to be at high risk for alcoholism. The present study sought to expand our understanding of cognitive and behavioural dispositions associated with executive control and self-regulation in alcohol naïve offspring with and without family history of alcoholism. Sample comprised of alcohol naive offspring in two groups: (i) at high risk (n = 34) and (ii) at low risk for alcoholism (n = 34). Both groups were matched on age (+/-1 year), education (+/-1 year) and gender. Measures used were: Mini-International Neuropsychiatric Interview, Family Interview for Genetic Studies, Socio-demographic Data Sheet, Annett's Handedness Questionnaire, Barratt's Impulsiveness Scale-version 11, Digit Span Test, Spatial Span Test, Tower of London, Wisconsin Card Sorting Test, Iowa Gambling Task (IGT) and Game of Dice Task (GDT). Results showed that alcohol naive offspring at high risk for alcoholism reported significantly high impulsivity and demonstrated significant differences on executive functions and decision making tasks. Correlation analysis revealed that high impulsivity was significantly associated with poor performance on explicit decision making task (GDT) and executive function task (WCST). There was no significant correlation between two decision making tasks (IGT and GDT) in both groups and performance on IGT was not significantly associated with impulsivity and executive functions. The present study indicates cognitive and behavioural dispositions in alcohol naive offspring at high risk for alcoholism and support the sub-optimal balance between reflective and impulsive system responsible for addiction. Furthermore, present study supports separability between two different types of decision making tasks. Copyright © 2018 Elsevier B.V. All rights reserved.

Assessing the vulnerability of human and biological communities to changing ecosystem services using a GIS-based multi-criteria decision support tool

USGS Publications Warehouse

Villarreal, Miguel; Norman, Laura M.; Labiosa, William B.

2012-01-01

In this paper we describe an application of a GIS-based multi-criteria decision support web tool that models and evaluates relative changes in ecosystem services to policy and land management decisions. The Santa Cruz Watershed Ecosystem Portfolio (SCWEPM) was designed to provide credible forecasts of responses to ecosystem drivers and stressors and to illustrate the role of land use decisions on spatial and temporal distributions of ecosystem services within a binational (U.S. and Mexico) watershed. We present two SCWEPM sub-models that when analyzed together address bidirectional relationships between social and ecological vulnerability and ecosystem services. The first model employs the Modified Socio-Environmental Vulnerability Index (M-SEVI), which assesses community vulnerability using information from U.S. and Mexico censuses on education, access to resources, migratory status, housing situation, and number of dependents. The second, relating land cover change to biodiversity (provisioning services), models changes in the distribution of terrestrial vertebrate habitat based on multitemporal vegetation and land cover maps, wildlife habitat relationships, and changes in land use/land cover patterns. When assessed concurrently, the models exposed some unexpected relationships between vulnerable communities and ecosystem services provisioning. For instance, the most species-rich habitat type in the watershed, Desert Riparian Forest, increased over time in areas occupied by the most vulnerable populations and declined in areas with less vulnerable populations. This type of information can be used to identify ecological conservation and restoration targets that enhance the livelihoods of people in vulnerable communities and promote biodiversity and ecosystem health.

Development of the Supported Decision Making Inventory System.

PubMed

Shogren, Karrie A; Wehmeyer, Michael L; Uyanik, Hatice; Heidrich, Megan

2017-12-01

Supported decision making has received increased attention as an alternative to guardianship and a means to enable people with intellectual and developmental disabilities to exercise their right to legal capacity. Assessments are needed that can used by people with disabilities and their systems of supports to identify and plan for needed supports to enable decision making. This article describes the steps taken to develop such an assessment tool, the Supported Decision Making Inventory System (SDMIS), and initial feedback received from self-advocates with intellectual disability. The three sections of the SDMIS (Supported Decision Making Personal Factors Inventory, Supported Decision Making Environmental Demands Inventory, and Decision Making Autonomy Inventory) are described and implications for future research, policy, and practice are discussed.

Science informed water resources decision-making: Examples using remote sensing observations in East Africa, the Lower Mekong Basin and the western United States

NASA Astrophysics Data System (ADS)

Granger, S. L.; Andreadis, K.; Das, N.; Farr, T. G.; Ines, A. V. M.; Jayasinghe, S.; Jones, C. E.; Melton, F. S.; Ndungu, L. W.; Lai-Norling, J.; Painter, T. H.

2017-12-01

Across the globe, planners and decision makers are often hampered by organizational and data silos and/or a lack of historic data or scant in situ observations on which to base policy and action plans. The end result is a complex interaction of responsibilities, legal frameworks, and stakeholder needs guided by uncertain information that is essentially bounded by how climate extremes are defined and characterized. Because of the importance of water, considerable resources in the developing and developed world are invested in data and tools for managing water. However, the existing paradigm of water management around the world faces significant challenges including inadequate funding to install, maintain or upgrade monitoring networks, lack of resources to integrate new science and data sources into existing tools, and demands for improved spatial coverage of observations. Add to this, a changing hydrology that is so complex it requires measurements and analyses that have never been done before. Interest in applying remote sensing science and observations into the decision making process is growing the world over, but in order to succeed, it is essential to form partnerships with stakeholder organizations and decision makers at the outset. In this talk, we describe examples of succesful decision-maker and science partnering based on projects that apply remote sensing science and observations in East Africa and the Lower Mekong Basin supported by the SERVIR Initiative, a joint United States Agency for International Development (USAID) and National Aeronautics and Space Administration (NASA) program, and projects in the western United States supported by NASA's Jet Propulsion Laboratory and the Western Water Applications Office (WWAO). All of these examples have benefitted from strong, committed partnerships with end user agencies. Best practices and lessons learned in connecting science to decision making amongst these examples are explored.

Cognitive issues in autonomous spacecraft-control operations: An investigation of software-mediated decision making in a scaled environment

NASA Astrophysics Data System (ADS)

Murphy, Elizabeth Drummond

As advances in technology are applied in complex, semi-automated domains, human controllers are distanced from the controlled process. This physical and psychological distance may both facilitate and degrade human performance. To investigate cognitive issues in spacecraft ground-control operations, the present experimental research was undertaken. The primary issue concerned the ability of operations analysts who do not monitor operations to make timely, accurate decisions when autonomous software calls for human help. Another key issue involved the potential effects of spatial-visualization ability (SVA) in environments that present data in graphical formats. Hypotheses were derived largely from previous findings and predictions in the literature. Undergraduate psychology students were assigned at random to a monitoring condition or an on-call condition in a scaled environment. The experimental task required subjects to decide on the veracity of a problem diagnosis delivered by a software process on-board a simulated spacecraft. To support decision-making, tabular and graphical data displays presented information on system status. A level of software confidence in the problem diagnosis was displayed, and subjects reported their own level of confidence in their decisions. Contrary to expectations, the performance of on-call subjects did not differ significantly from that of continuous monitors. Analysis yielded a significant interaction of sex and condition: Females in the on-call condition had the lowest mean accuracy. Results included a preference for bar charts over line graphs and faster performance with tables than with line graphs. A significant correlation was found between subjective confidence and decision accuracy. SVA was found to be predictive of accuracy but not speed; and SVA was found to be a stronger predictor of performance for males than for females. Low-SVA subjects reported that they relied more on software confidence than did medium- or high-SVA subjects. These and other findings have implications for the design of user interfaces to support human decision-making in on-call situations and to accommodate low-SVA users.

Rapid Benefit Indicators (RBI) Spatial Analysis Tools

EPA Science Inventory

The Rapid Benefit Indicators (RBI) approach consists of five steps and is outlined in Assessing the Benefits of Wetland Restoration - A Rapid Benefits Indicators Approach for Decision Makers. This spatial analysis tool is intended to be used to analyze existing spatial informatio...

The influence of hazard models on GIS-based regional risk assessments and mitigation policies

USGS Publications Warehouse

Bernknopf, R.L.; Rabinovici, S.J.M.; Wood, N.J.; Dinitz, L.B.

2006-01-01

Geographic information systems (GIS) are important tools for understanding and communicating the spatial distribution of risks associated with natural hazards in regional economies. We present a GIS-based decision support system (DSS) for assessing community vulnerability to natural hazards and evaluating potential mitigation policy outcomes. The Land Use Portfolio Modeler (LUPM) integrates earth science and socioeconomic information to predict the economic impacts of loss-reduction strategies. However, the potential use of such systems in decision making may be limited when multiple but conflicting interpretations of the hazard are available. To explore this problem, we conduct a policy comparison using the LUPM to test the sensitivity of three available assessments of earthquake-induced lateral-spread ground failure susceptibility in a coastal California community. We find that the uncertainty regarding the interpretation of the science inputs can influence the development and implementation of natural hazard management policies. Copyright ?? 2006 Inderscience Enterprises Ltd.

Rapid Prototyping of Hyperspectral Image Analysis Algorithms for Improved Invasive Species Decision Support Tools

NASA Astrophysics Data System (ADS)

Bruce, L. M.; Ball, J. E.; Evangilista, P.; Stohlgren, T. J.

2006-12-01

Nonnative invasive species adversely impact ecosystems, causing loss of native plant diversity, species extinction, and impairment of wildlife habitats. As a result, over the past decade federal and state agencies and nongovernmental organizations have begun to work more closely together to address the management of invasive species. In 2005, approximately 500M dollars was budgeted by U.S. Federal Agencies for the management of invasive species. Despite extensive expenditures, most of the methods used to detect and quantify the distribution of these invaders are ad hoc, at best. Likewise, decisions on the type of management techniques to be used or evaluation of the success of these methods are typically non-systematic. More efficient methods to detect or predict the occurrence of these species, as well as the incorporation of this knowledge into decision support systems, are greatly needed. In this project, rapid prototyping capabilities (RPC) are utilized for an invasive species application. More precisely, our recently developed analysis techniques for hyperspectral imagery are being prototyped for inclusion in the national Invasive Species Forecasting System (ISFS). The current ecological forecasting tools in ISFS will be compared to our hyperspectral-based invasives prediction algorithms to determine if/how the newer algorithms enhance the performance of ISFS. The PIs have researched the use of remotely sensed multispectral and hyperspectral reflectance data for the detection of invasive vegetative species. As a result, the PI has designed, implemented, and benchmarked various target detection systems that utilize remotely sensed data. These systems have been designed to make decisions based on a variety of remotely sensed data, including high spectral/spatial resolution hyperspectral signatures (1000's of spectral bands, such as those measured using ASD handheld devices), moderate spectral/spatial resolution hyperspectral images (100's of spectral bands, such as Hyperion imagery), and low spectral/spatial resolution images (such as MODIS imagery). These algorithms include hyperspectral exploitation methods such as stepwise-LDA band selection, optimized spectral band grouping, and stepwise PCA component selection. The PIs have extensive experience with combining these recently- developed methods with conventional classifiers to form an end-to-end automated target recognition (ATR) system for detecting invasive species. The outputs of these systems can be invasive prediction maps, as well as quantitative accuracy assessments like confusion matrices, user accuracies, and producer accuracies. For all of these research endeavors, the PIs have developed numerous advanced signal and image processing methodologies, as well a suite of associated software modules. However, the use of the prototype software modules has been primarily contained to Mississippi State University. The project described in this presentation and paper will enable future systematic inclusion of these software modules into a DSS with national scope.

Adaptive Comanagement of a Marine Protected Area Network in Fiji

PubMed Central

WEEKS, REBECCA; JUPITER, STACY D

2014-01-01

Adaptive management of natural resources is an iterative process of decision making whereby management strategies are progressively changed or adjusted in response to new information. Despite an increasing focus on the need for adaptive conservation strategies, there remain few applied examples. We describe the 9-year process of adaptive comanagement of a marine protected area network in Kubulau District, Fiji. In 2011, a review of protected area boundaries and management rules was motivated by the need to enhance management effectiveness and the desire to improve resilience to climate change. Through a series of consultations, with the Wildlife Conservation Society providing scientific input to community decision making, the network of marine protected areas was reconfigured so as to maximize resilience and compliance. Factors identified as contributing to this outcome include well-defined resource-access rights; community respect for a flexible system of customary governance; long-term commitment and presence of comanagement partners; supportive policy environment for comanagement; synthesis of traditional management approaches with systematic monitoring; and district-wide coordination, which provided a broader spatial context for adaptive-management decision making. PMID:24112643

Wild Fire Risk Map in the Eastern Steppe of Mongolia Using Spatial Multi-Criteria Analysis

NASA Astrophysics Data System (ADS)

Nasanbat, Elbegjargal; Lkhamjav, Ochirkhuyag

2016-06-01

Grassland fire is a cause of major disturbance to ecosystems and economies throughout the world. This paper investigated to identify risk zone of wildfire distributions on the Eastern Steppe of Mongolia. The study selected variables for wildfire risk assessment using a combination of data collection, including Social Economic, Climate, Geographic Information Systems, Remotely sensed imagery, and statistical yearbook information. Moreover, an evaluation of the result is used field validation data and assessment. The data evaluation resulted divided by main three group factors Environmental, Social Economic factor, Climate factor and Fire information factor into eleven input variables, which were classified into five categories by risk levels important criteria and ranks. All of the explanatory variables were integrated into spatial a model and used to estimate the wildfire risk index. Within the index, five categories were created, based on spatial statistics, to adequately assess respective fire risk: very high risk, high risk, moderate risk, low and very low. Approximately more than half, 68 percent of the study area was predicted accuracy to good within the very high, high risk and moderate risk zones. The percentages of actual fires in each fire risk zone were as follows: very high risk, 42 percent; high risk, 26 percent; moderate risk, 13 percent; low risk, 8 percent; and very low risk, 11 percent. The main overall accuracy to correct prediction from the model was 62 percent. The model and results could be support in spatial decision making support system processes and in preventative wildfire management strategies. Also it could be help to improve ecological and biodiversity conservation management.

Supporting End of Life Decision Making: Case Studies of Relational Closeness in Supported Decision Making for People with Severe or Profound Intellectual Disability

ERIC Educational Resources Information Center

Watson, Joanne; Wilson, Erin; Hagiliassis, Nick

2017-01-01

Background: The United Nations Convention on the Rights of Persons with Disabilities (UNCRPD) promotes the use of supported decision making in lieu of substitute decision making. To date, there has been a lack of focus on supported decision making for people with severe or profound intellectual disability, including for end of life decisions.…

Applying the Wildland Fire Decision Support System (WFDSS) to support risk-informed decision making: The Gold Pan Fire, Bitterroot National Forest, Montana, USA

Treesearch

Erin K. Noonan-Wright; Tonja S. Opperman

2015-01-01

In response to federal wildfire policy changes, risk-informed decision-making by way of improved decision support, is increasingly becoming a component of managing wildfires. As fire incidents escalate in size and complexity, the Wildland Fire Decision Support System (WFDSS) provides support with different analytical tools as fire conditions change. We demonstrate the...

Decision support for clinical laboratory capacity planning.

PubMed

van Merode, G G; Hasman, A; Derks, J; Goldschmidt, H M; Schoenmaker, B; Oosten, M

1995-01-01

The design of a decision support system for capacity planning in clinical laboratories is discussed. The DSS supports decisions concerning the following questions: how should the laboratory be divided into job shops (departments/sections), how should staff be assigned to workstations and how should samples be assigned to workstations for testing. The decision support system contains modules for supporting decisions at the overall laboratory level (concerning the division of the laboratory into job shops) and for supporting decisions at the job shop level (assignment of staff to workstations and sample scheduling). Experiments with these modules are described showing both the functionality and the validity.

Features of computerized clinical decision support systems supportive of nursing practice: a literature review.

PubMed

Lee, Seonah

2013-10-01

This study aimed to organize the system features of decision support technologies targeted at nursing practice into assessment, problem identification, care plans, implementation, and outcome evaluation. It also aimed to identify the range of the five stage-related sequential decision supports that computerized clinical decision support systems provided. MEDLINE, CINAHL, and EMBASE were searched. A total of 27 studies were reviewed. The system features collected represented the characteristics of each category from patient assessment to outcome evaluation. Several features were common across the reviewed systems. For the sequential decision support, all of the reviewed systems provided decision support in sequence for patient assessment and care plans. Fewer than half of the systems included problem identification. There were only three systems operating in an implementation stage and four systems in outcome evaluation. Consequently, the key steps for sequential decision support functions were initial patient assessment, problem identification, care plan, and outcome evaluation. Providing decision support in such a full scope will effectively help nurses' clinical decision making. By organizing the system features, a comprehensive picture of nursing practice-oriented computerized decision support systems was obtained; however, the development of a guideline for better systems should go beyond the scope of a literature review.

Methods to achieve accurate projection of regional and global raster databases

USGS Publications Warehouse

Usery, E.L.; Seong, J.C.; Steinwand, D.R.; Finn, M.P.

2002-01-01

This research aims at building a decision support system (DSS) for selecting an optimum projection considering various factors, such as pixel size, areal extent, number of categories, spatial pattern of categories, resampling methods, and error correction methods. Specifically, this research will investigate three goals theoretically and empirically and, using the already developed empirical base of knowledge with these results, develop an expert system for map projection of raster data for regional and global database modeling. The three theoretical goals are as follows: (1) The development of a dynamic projection that adjusts projection formulas for latitude on the basis of raster cell size to maintain equal-sized cells. (2) The investigation of the relationships between the raster representation and the distortion of features, number of categories, and spatial pattern. (3) The development of an error correction and resampling procedure that is based on error analysis of raster projection.

CELL5M: A geospatial database of agricultural indicators for Africa South of the Sahara.

PubMed

Koo, Jawoo; Cox, Cindy M; Bacou, Melanie; Azzarri, Carlo; Guo, Zhe; Wood-Sichra, Ulrike; Gong, Queenie; You, Liangzhi

2016-01-01

Recent progress in large-scale georeferenced data collection is widening opportunities for combining multi-disciplinary datasets from biophysical to socioeconomic domains, advancing our analytical and modeling capacity. Granular spatial datasets provide critical information necessary for decision makers to identify target areas, assess baseline conditions, prioritize investment options, set goals and targets and monitor impacts. However, key challenges in reconciling data across themes, scales and borders restrict our capacity to produce global and regional maps and time series. This paper provides overview, structure and coverage of CELL5M-an open-access database of geospatial indicators at 5 arc-minute grid resolution-and introduces a range of analytical applications and case-uses. CELL5M covers a wide set of agriculture-relevant domains for all countries in Africa South of the Sahara and supports our understanding of multi-dimensional spatial variability inherent in farming landscapes throughout the region.

Spatial modelling of arsenic distribution and human health effects in Lake Victoria basin, Tanzania

NASA Astrophysics Data System (ADS)

Ijumulana, Julian; Mtalo, Felix; Bhattacharya, Prosun

2016-04-01

Increasing incidences of naturally occurring geogenic pollutants in drinking water sources and associated human health risks are the two major challenges requiring detailed knowledge to support decision making process at various levels. The presence, location and extent of environmental contamination is needed towards developing mitigation measures to achieve required standards. In this study we are developing a GIS-based model to detect and predict drinking water pollutants at the identified hotspots and monitor its variation in space. In addition, the mobility of pollutants within the affected region needs to be evaluated using topographic and hydrogeological data. Based on these geospatial data on contaminant distribution, spatial relationship of As and F contamination and reported human health effects such as dental caries, dental fluorosis, skeletal fluorosis and bone crippling, skin and other cancers etc. can be modeled for potential interventions for safe drinking water supplies.

[Environmental impact assessment based on planning support system].

PubMed

Chen, Wen-Bo; Carsjens, Gerrit-Jan

2011-02-01

How to assess environmental impact is one of the keys in land use planning. This article described in detail the concepts of activities, impact zones, functions, and sensitivities, as well as the development of STEPP (strategic tool for integrating environmental aspects in planning procedures) based on Avenue, the secondary developing language of ArcView GIS. The system makes it convenient for planning practitioners exchanging information, and can spatially, visually and quantitatively describe environmental impact and its change. In this study, the urban-rural combination area located between EDE and Veenendaal of The Netherlands was taken as case, and the results indicated that the environment was incorporated well in the planning procedure based on the concepts, and could also demonstrate the effects of planning measures on environment spatially, explicitly, and in real-time, facilitating the participation of planning practitioners and decision-making. Some proposals of how to promote STEEP application in China were suggested.

Trading Speed and Accuracy by Coding Time: A Coupled-circuit Cortical Model

PubMed Central

Standage, Dominic; You, Hongzhi; Wang, Da-Hui; Dorris, Michael C.

2013-01-01

Our actions take place in space and time, but despite the role of time in decision theory and the growing acknowledgement that the encoding of time is crucial to behaviour, few studies have considered the interactions between neural codes for objects in space and for elapsed time during perceptual decisions. The speed-accuracy trade-off (SAT) provides a window into spatiotemporal interactions. Our hypothesis is that temporal coding determines the rate at which spatial evidence is integrated, controlling the SAT by gain modulation. Here, we propose that local cortical circuits are inherently suited to the relevant spatial and temporal coding. In simulations of an interval estimation task, we use a generic local-circuit model to encode time by ‘climbing’ activity, seen in cortex during tasks with a timing requirement. The model is a network of simulated pyramidal cells and inhibitory interneurons, connected by conductance synapses. A simple learning rule enables the network to quickly produce new interval estimates, which show signature characteristics of estimates by experimental subjects. Analysis of network dynamics formally characterizes this generic, local-circuit timing mechanism. In simulations of a perceptual decision task, we couple two such networks. Network function is determined only by spatial selectivity and NMDA receptor conductance strength; all other parameters are identical. To trade speed and accuracy, the timing network simply learns longer or shorter intervals, driving the rate of downstream decision processing by spatially non-selective input, an established form of gain modulation. Like the timing network's interval estimates, decision times show signature characteristics of those by experimental subjects. Overall, we propose, demonstrate and analyse a generic mechanism for timing, a generic mechanism for modulation of decision processing by temporal codes, and we make predictions for experimental verification. PMID:23592967

High-Resolution Climate Data Visualization through GIS- and Web-based Data Portals

NASA Astrophysics Data System (ADS)

WANG, X.; Huang, G.

2017-12-01

Sound decisions on climate change adaptation rely on an in-depth assessment of potential climate change impacts at regional and local scales, which usually requires finer resolution climate projections at both spatial and temporal scales. However, effective downscaling of global climate projections is practically difficult due to the lack of computational resources and/or long-term reference data. Although a large volume of downscaled climate data has been make available to the public, how to understand and interpret the large-volume climate data and how to make use of the data to drive impact assessment and adaptation studies are still challenging for both impact researchers and decision makers. Such difficulties have become major barriers preventing informed climate change adaptation planning at regional scales. Therefore, this research will explore new GIS- and web-based technologies to help visualize the large-volume regional climate data with high spatiotemporal resolutions. A user-friendly public data portal, named Climate Change Data Portal (CCDP, http://ccdp.network), will be established to allow intuitive and open access to high-resolution regional climate projections at local scales. The CCDP offers functions of visual representation through geospatial maps and data downloading for a variety of climate variables (e.g., temperature, precipitation, relative humidity, solar radiation, and wind) at multiple spatial resolutions (i.e., 25 - 50 km) and temporal resolutions (i.e., annual, seasonal, monthly, daily, and hourly). The vast amount of information the CCDP encompasses can provide a crucial basis for assessing impacts of climate change on local communities and ecosystems and for supporting better decision making under a changing climate.

Linked Micromaps: Statistical Summaries in a Spatial Context

EPA Science Inventory

Communicating summaries of spatial data to decision makers and the public is challenging. We present a graphical method that provides both a geographic context and a statistical summary for such spatial data. Monitoring programs have a need for such geographical summaries. For ...

A new spatial multiple discrete-continuous modeling approach to land use change analysis.

DOT National Transportation Integrated Search

2013-09-01

This report formulates a multiple discrete-continuous probit (MDCP) land-use model within a : spatially explicit economic structural framework for land-use change decisions. The spatial : MDCP model is capable of predicting both the type and intensit...

Rapid Benefit Indicators (RBI) Spatial Analysis Toolset - Manual

EPA Science Inventory

The Rapid Benefit Indicators (RBI) approach consists of five steps and is outlined in Assessing the Benefits of Wetland Restoration - A Rapid Benefits Indicators Approach for Decision Makers. This spatial analysis tool is intended to be used to analyze existing spatial informatio...

HUMAN HEALTH METRICS FOR ENVIRONMENTAL DECISION SUPPORT TOOLS: LESSONS FROM HEALTH ECONOMICS AND DECISION ANALYSIS: PUBLISHED REPORT

EPA Science Inventory

NRMRL-CIN-1351A Hofstetter**, P., and Hammitt, J. K. Human Health Metrics for Environmental Decision Support Tools: Lessons from Health Economics and Decision Analysis. EPA/600/R-01/104 (NTIS PB2002-102119). Decision makers using environmental decision support tools are often ...

Prefrontal spatial working memory network predicts animal's decision making in a free choice saccade task.

PubMed

Mochizuki, Kei; Funahashi, Shintaro

2016-01-01

While neurons in the lateral prefrontal cortex (PFC) encode spatial information during the performance of working memory tasks, they are also known to participate in subjective behavior such as spatial attention and action selection. In the present study, we analyzed the activity of primate PFC neurons during the performance of a free choice memory-guided saccade task in which the monkeys needed to choose a saccade direction by themselves. In trials when the receptive field location was subsequently chosen by the animal, PFC neurons with spatially selective visual response started to show greater activation before cue onset. This result suggests that the fluctuation of firing before cue presentation prematurely biased the representation of a certain spatial location and eventually encouraged the subsequent choice of that location. In addition, modulation of the activity by the animal's choice was observed only in neurons with high sustainability of activation and was also dependent on the spatial configuration of the visual cues. These findings were consistent with known characteristics of PFC neurons in information maintenance in spatial working memory function. These results suggest that precue fluctuation of spatial representation was shared and enhanced through the working memory network in the PFC and could finally influence the animal's free choice of saccade direction. The present study revealed that the PFC plays an important role in decision making in a free choice condition and that the dynamics of decision making are constrained by the network architecture embedded in this cortical area. Copyright © 2016 the American Physiological Society.

Building capacity for in-situ phenological observation data to support integrated biodiversity information at local to national scales

NASA Astrophysics Data System (ADS)

Weltzin, J. F.

2016-12-01

Earth observations from a variety of platforms and across a range of scales are required to support research, natural resource management, and policy- and decision-making in a changing world. Integrated earth observation data provides multi-faceted information critical to decision support, vulnerability and change detection, risk assessments, early warning and modeling, simulation and forecasting in the natural resource societal benefit area. The USA National Phenology Network (USA-NPN; www.usanpn.org) is a national-scale science and monitoring initiative focused on phenology - the study of seasonal life-cycle events such as leafing, flowering, reproduction, and migration - as a tool to understand the response of biodiversity to environmental variation and change. USA-NPN provides a hierarchical, national monitoring framework that enables other organizations to leverage the capacity of the Network for their own applications - minimizing investment and duplication of effort - while promoting interoperability and sustainability. Over the last decade, the network has focused on the development of a centralized database for in-situ (ground based) observations of plants and animals, now with 8 M records for the period 1954-present. More recently, we have developed a workflow for the production and validation of spatially gridded phenology products based on models that couple the organismal data with climatological and meteorological data at daily time-steps and relatively fine spatial resolutions ( 2.5 km to 4 km). These gridded data are now ripe for integration with other modeled or earth observation gridded data, e.g., indices of drought impact or land surface reflectance. This greatly broadens capacity to scale organismal observational data to landscapes and regions, and enables novel investigations of biophysical interactions at unprecedented scales, e.g., continental-scale migrations. Sustainability emerges from identification of stakeholder needs, segmentation of target audiences (e.g., data contributors, data consumers), documentation of all aspects of the data production and delivery process, development of collaborative partnerships, enterprise approaches to information management, and excellent customer service.

Operational data products to support phenological research and applications at local to continental scales

NASA Astrophysics Data System (ADS)

Weltzin, J. F.

2017-12-01

Phenological data from a variety of platforms - across a range of spatial and temporal scales - are required to support research, natural resource management, and policy- and decision-making in a changing world. Observational and modeled phenological data, especially when integrated with associated biophysical data (e.g., climate, land-use/land-cover, hydrology) has great potential to provide multi-faceted information critical to decision support systems, vulnerability and risk assessments, change detection applications, and early-warning and forecasting systems for natural and modified ecosystems. The USA National Phenology Network (USA-NPN; www.usanpn.org) is a national-scale science and monitoring initiative focused on understanding the drivers and feedback effects of phenological variation in changing environments. The Network maintains a centralized database of over 10M ground-based observations of plants and animals for 1954-present, and leverages these data to produce operational data products for use by a variety of audiences, including researchers and resource managers. This presentation highlights our operational data products, including the tools, maps, and services that facilitate discovery, accessibility and usability of integrated phenological information. We describe (1) the data download tool, a customizable GUI that provides geospatially referenced raw, bounded or summarized organismal and climatological data and associated metadata (including calendars, time-series curves, and XY graphs), (2) the visualization tool, which provides opportunities to explore, visualize and export or download both organismal and modeled (gridded) products at daily time-steps and relatively fine spatial resolutions ( 2.5 km to 4 km) for the period 1980 to 6 days into the future, and (3) web services that enable custom query and download of map, feature and cover services in a variety of standard formats. These operational products facilitate scaling of integrated phenological and associated data to landscapes and regions, and enable novel investigations of biophysical interactions at unprecedented scales, e.g., continental-scale migrations.

Predicting long-range transport: a systematic evaluation of two multimedia transport models.

PubMed

Bennett, D H; Scheringer, M; McKone, T E; Hungerbühler, K

2001-03-15

The United Nations Environment Program has recently developed criteria to identify and restrict chemicals with a potential for persistence and long-range transport (persistent organic pollutants or POPs). There are many stakeholders involved, and the issues are not only scientific but also include social, economic, and political factors. This work focuses on one aspect of the POPs debate, the criteria for determining the potential for long-range transport (LRT). Our goal is to determine if current models are reliable enough to support decisions that classify a chemical based on the LRT potential. We examine the robustness of two multimedia fate models for determining the relative ranking and absolute spatial range of various chemicals in the environment. We also consider the effect of parameter uncertainties and the model uncertainty associated with the selection of an algorithm for gas-particle partitioning on the model results. Given the same chemical properties, both models give virtually the same ranking. However, when chemical parameter uncertainties and model uncertainties such as particle partitioning are considered, the spatial range distributions obtained for the individual chemicals overlap, preventing a distinct rank order. The absolute values obtained for the predicted spatial range or travel distance differ significantly between the two models for the uncertainties evaluated. We find that to evaluate a chemical when large and unresolved uncertainties exist, it is more informative to use two or more models and include multiple types of uncertainty. Model differences and uncertainties must be explicitly confronted to determine how the limitations of scientific knowledge impact predictions in the decision-making process.

Simulating Spatial Growth Patterns in Developing Countries: A Case of Shama in the Western Region of Ghana.

NASA Astrophysics Data System (ADS)

Inkoom, J. N.; Nyarko, B. K.

2014-12-01

The integration of geographic information systems (GIS) and agent-based modelling (ABM) can be an efficient tool to improve spatial planning practices. This paper utilizes GIS and ABM approaches to simulate spatial growth patterns of settlement structures in Shama. A preliminary household survey on residential location decision-making choice served as the behavioural rule for household agents in the model. Physical environment properties of the model were extracted from a 2005 image implemented in NetLogo. The resulting growth pattern model was compared with empirical growth patterns to ascertain the model's accuracy. The paper establishes that the development of unplanned structures and its evolving structural pattern are a function of land price, proximity to economic centres, household economic status and location decision-making patterns. The application of the proposed model underlines its potential for integration into urban planning policies and practices, and for understanding residential decision-making processes in emerging cities in developing countries. Key Words: GIS; Agent-based modelling; Growth patterns; NetLogo; Location decision making; Computational Intelligence.

An integrated theory of attention and decision making in visual signal detection.

PubMed

Smith, Philip L; Ratcliff, Roger

2009-04-01

The simplest attentional task, detecting a cued stimulus in an otherwise empty visual field, produces complex patterns of performance. Attentional cues interact with backward masks and with spatial uncertainty, and there is a dissociation in the effects of these variables on accuracy and on response time. A computational theory of performance in this task is described. The theory links visual encoding, masking, spatial attention, visual short-term memory (VSTM), and perceptual decision making in an integrated dynamic framework. The theory assumes that decisions are made by a diffusion process driven by a neurally plausible, shunting VSTM. The VSTM trace encodes the transient outputs of early visual filters in a durable form that is preserved for the time needed to make a decision. Attention increases the efficiency of VSTM encoding, either by increasing the rate of trace formation or by reducing the delay before trace formation begins. The theory provides a detailed, quantitative account of attentional effects in spatial cuing tasks at the level of response accuracy and the response time distributions. (c) 2009 APA, all rights reserved

Negotiation and Decision Making with Collaborative Software: How MarineMap 'Changed the Game' in California's Marine Life Protected Act Initiative.

PubMed

Cravens, Amanda E

2016-02-01

Environmental managers and planners have become increasingly enthusiastic about the potential of decision support tools (DSTs) to improve environmental decision-making processes as information technology transforms many aspects of daily life. Discussions about DSTs, however, rarely recognize the range of ways software can influence users' negotiation, problem-solving, or decision-making strategies and incentives, in part because there are few empirical studies of completed processes that used technology. This mixed-methods study-which draws on data from approximately 60 semi-structured interviews and an online survey--examines how one geospatial DST influenced participants' experiences during a multi-year marine planning process in California. Results suggest that DSTs can facilitate communication by creating a common language, help users understand the geography and scientific criteria in play during the process, aid stakeholders in identifying shared or diverging interests, and facilitate joint problem solving. The same design features that enabled the tool to aid in decision making, however, also presented surprising challenges in certain circumstances by, for example, making it difficult for participants to discuss information that was not spatially represented on the map-based interface. The study also highlights the importance of the social context in which software is developed and implemented, suggesting that the relationship between the software development team and other participants may be as important as technical software design in shaping how DSTs add value. The paper concludes with considerations to inform the future use of DSTs in environmental decision-making processes.

From products to processes: Academic events to foster interdisciplinary and iterative dialogue in a changing climate

NASA Astrophysics Data System (ADS)

Addor, Nans; Ewen, Tracy; Johnson, Leigh; Ćöltekin, Arzu; Derungs, Curdin; Muccione, Veruska

2015-08-01

In the context of climate change, both climate researchers and decision makers deal with uncertainties, but these uncertainties differ in fundamental ways. They stem from different sources, cover different temporal and spatial scales, might or might not be reducible or quantifiable, and are generally difficult to characterize and communicate. Hence, a mutual understanding between current and future climate researchers and decision makers must evolve for adaptation strategies and planning to progress. Iterative two-way dialogue can help to improve the decision making process by bridging current top-down and bottom-up approaches. One way to cultivate such interactions is by providing venues for these actors to interact and exchange on the uncertainties they face. We use a workshop-seminar series involving academic researchers, students, and decision makers as an opportunity to put this idea into practice and evaluate it. Seminars, case studies, and a round table allowed participants to reflect upon and experiment with uncertainties. An opinion survey conducted before and after the workshop-seminar series allowed us to qualitatively evaluate its influence on the participants. We find that the event stimulated new perspectives on research products and communication processes, and we suggest that similar events may ultimately contribute to the midterm goal of improving support for decision making in a changing climate. Therefore, we recommend integrating bridging events into university curriculum to foster interdisciplinary and iterative dialogue among researchers, decision makers, and students.

Negotiation and Decision Making with Collaborative Software: How MarineMap `Changed the Game' in California's Marine Life Protected Act Initiative

NASA Astrophysics Data System (ADS)

Cravens, Amanda E.

2016-02-01

Environmental managers and planners have become increasingly enthusiastic about the potential of decision support tools (DSTs) to improve environmental decision-making processes as information technology transforms many aspects of daily life. Discussions about DSTs, however, rarely recognize the range of ways software can influence users' negotiation, problem-solving, or decision-making strategies and incentives, in part because there are few empirical studies of completed processes that used technology. This mixed-methods study—which draws on data from approximately 60 semi-structured interviews and an online survey—examines how one geospatial DST influenced participants' experiences during a multi-year marine planning process in California. Results suggest that DSTs can facilitate communication by creating a common language, help users understand the geography and scientific criteria in play during the process, aid stakeholders in identifying shared or diverging interests, and facilitate joint problem solving. The same design features that enabled the tool to aid in decision making, however, also presented surprising challenges in certain circumstances by, for example, making it difficult for participants to discuss information that was not spatially represented on the map-based interface. The study also highlights the importance of the social context in which software is developed and implemented, suggesting that the relationship between the software development team and other participants may be as important as technical software design in shaping how DSTs add value. The paper concludes with considerations to inform the future use of DSTs in environmental decision-making processes.

SANDS: an architecture for clinical decision support in a National Health Information Network.

PubMed

Wright, Adam; Sittig, Dean F

2007-10-11

A new architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support) is introduced and its performance evaluated. The architecture provides a method for performing clinical decision support across a network, as in a health information exchange. Using the prototype we demonstrated that, first, a number of useful types of decision support can be carried out using our architecture; and, second, that the architecture exhibits desirable reliability and performance characteristics.

Effects of in-vehicle warning information displays with or without spatial compatibility on driving behaviors and response performance.

PubMed

Liu, Yung-Ching; Jhuang, Jing-Wun

2012-07-01

A driving simulator study was conducted to evaluate the effects of five in-vehicle warning information displays upon drivers' emergent response and decision performance. These displays include visual display, auditory displays with and without spatial compatibility, hybrid displays in both visual and auditory format with and without spatial compatibility. Thirty volunteer drivers were recruited to perform various tasks that involved driving, stimulus-response, divided attention and stress rating. Results show that for displays of single-modality, drivers benefited more when coping with visual display of warning information than auditory display with or without spatial compatibility. However, auditory display with spatial compatibility significantly improved drivers' performance in reacting to the divided attention task and making accurate S-R task decision. Drivers' best performance results were obtained for hybrid display with spatial compatibility. Hybrid displays enabled drivers to respond the fastest and achieve the best accuracy in both S-R and divided attention tasks. Copyright © 2011 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Combating Flood Crisis with Geographic Information System (GIS): An Example From Akure, Southwest Nigeria

NASA Astrophysics Data System (ADS)

Eludoyin, A. O.; Akinbode, O. M.; Archibong, Ediang Okuku

2007-07-01

Flood is a natural environmental disaster which could be aggravated by man's unguided development. It may subsequently cause destruction of properties and loss of life. Therefore it needs to be controlled and human influences controlled. This study attempts to describe an application of GIS as decision support to flooding problems in an urban area in Nigeria. The objective of the study is to describe the efficacy of GIS in monitoring of development on floodplains in an urban area in Nigeria. Topographic features were digitised from an existing 1:5,000 topographic map of Akure, with some position data collected and map updated using a handheld GPS. A database was created using both cartographic and attributes data collected from these and other sources. Spatial analyses were carried out using a PC based Integrated Land and Water Information System (ILWIS), version 3.2. The results obtained implicated dumpsites within the river channel as well as structural development within the River Ala floodplain as the major causes of inundation in this section of the city, especially, in the wet season. The study concluded that GIS could provide adequate decision support information to policy makers.

Multi-criteria Decision Support System (DSS) for optimal locations of Soil Aquifer Treatment (SAT) facilities.

PubMed

Tsangaratos, P; Kallioras, A; Pizpikis, Th; Vasileiou, E; Ilia, I; Pliakas, F

2017-12-15

Managed Aquifer Recharge is a wide-spread well-established groundwater engineering method which is largely seen as sound and sustainable solution to water scarcity hydrologically sensitive areas, such as the Circum Mediterranean. The process of site selection for the installation of a MAR facility is of paramount importance for the feasibility and effectiveness of the project itself, especially when the facility will include the use of waters of impaired quality as a recharge source, as in the case of Soil-Aquifer-Treatment systems. The main objective of this study is to present the developed framework of a multi-criteria Decision Support System (DSS) that integrates within a dynamic platform the main groundwater engineering parameters associated with MAR applications together with the general geographical features which determine the effectiveness of such a project. The proposed system will provide an advanced coupled DSS-GIS tool capable of handling local MAR-related issues -such as hydrogeology, topography, soil, climate etc., and spatially distributed variables -such as societal, economic, administrative, legislative etc., with special reference to Soil-Aquifer-Treatment technologies. Copyright © 2017 Elsevier B.V. All rights reserved.

Reconciling Scale Mismatch in Water Governance, Hydro-climatic Processes and Infrastructure Systems of Water Supply in Las Vegas

NASA Astrophysics Data System (ADS)

Garcia, M. E.; Alarcon, T.; Portney, K.; Islam, S.

2013-12-01

Water resource systems are a classic example of a common pool resource due to the high cost of exclusion and the subtractability of the resource; for common pool resources, the performance of governance systems primarily depends on how well matched the institutional arrangements and rules are to the biophysical conditions and social norms. Changes in water governance, hydro-climatic processes and infrastructure systems occur on disparate temporal and spatial scales. A key challenge is the gap between current climate change model resolution, and the spatial and temporal scale of urban water supply decisions. This gap will lead to inappropriate management policies if not mediated through a carefully crafted decision making process. Traditional decision support and planning methods (DSPM) such as classical decision analysis are not equipped to deal with a non-static climate. While emerging methods such as decision scaling, robust decision making and real options are designed to deal with a changing climate, governance systems have evolved under the assumption of a static climate and it is not clear if these methods are well suited to the existing governance regime. In our study, these questions are contextualized by examining an urban water utility that has made significant changes in policy to adapt to changing conditions: the Southern Nevada Water Authority (SNWA) which serves metropolitan Las Vegas. Like most desert cities, Las Vegas exists because of water; the artesian springs of the Las Vegas Valley once provided an ample water supply for Native Americans, ranchers and later a small railroad city. However, population growth has increased demands far beyond local supplies. The area now depends on the Colorado River for the majority of its water supply. Natural climate variability with periodic droughts has further challenged water providers; projected climate changes and further population growth will exacerbate these challenges. Las Vegas is selected as a case study due to the combined challenges of population growth and climate change, common in the arid west, and due its cooperative institutional response to these challenges, unprecedented in the arid west. To begin to disentangle this question we have analyzed the institutional arrangements and rules which govern water decision making in the Las Vegas Valley and evaluated the existing DSPM used by the SNWA and partner utilities. Presented here are the preliminary results from an ongoing project.

Future of electronic health records: implications for decision support.

PubMed

Rothman, Brian; Leonard, Joan C; Vigoda, Michael M

2012-01-01

The potential benefits of the electronic health record over traditional paper are many, including cost containment, reductions in errors, and improved compliance by utilizing real-time data. The highest functional level of the electronic health record (EHR) is clinical decision support (CDS) and process automation, which are expected to enhance patient health and healthcare. The authors provide an overview of the progress in using patient data more efficiently and effectively through clinical decision support to improve health care delivery, how decision support impacts anesthesia practice, and how some are leading the way using these systems to solve need-specific issues. Clinical decision support uses passive or active decision support to modify clinician behavior through recommendations of specific actions. Recommendations may reduce medication errors, which would result in considerable savings by avoiding adverse drug events. In selected studies, clinical decision support has been shown to decrease the time to follow-up actions, and prediction has proved useful in forecasting patient outcomes, avoiding costs, and correctly prompting treatment plan modifications by clinicians before engaging in decision-making. Clinical documentation accuracy and completeness is improved by an electronic health record and greater relevance of care data is delivered. Clinical decision support may increase clinician adherence to clinical guidelines, but educational workshops may be equally effective. Unintentional consequences of clinical decision support, such as alert desensitization, can decrease the effectiveness of a system. Current anesthesia clinical decision support use includes antibiotic administration timing, improved documentation, more timely billing, and postoperative nausea and vomiting prophylaxis. Electronic health record implementation offers data-mining opportunities to improve operational, financial, and clinical processes. Using electronic health record data in real-time for decision support and process automation has the potential to both reduce costs and improve the quality of patient care. © 2012 Mount Sinai School of Medicine.

Salience from the decision perspective: You know where it is before you know it is there.

PubMed

Zehetleitner, Michael; Müller, Hermann J

2010-12-31

In visual search for feature contrast ("odd-one-out") singletons, identical manipulations of salience, whether by varying target-distractor similarity or dimensional redundancy of target definition, had smaller effects on reaction times (RTs) for binary localization decisions than for yes/no detection decisions. According to formal models of binary decisions, identical differences in drift rates would yield larger RT differences for slow than for fast decisions. From this principle and the present findings, it follows that decisions on the presence of feature contrast singletons are slower than decisions on their location. This is at variance with two classes of standard models of visual search and object recognition that assume a serial cascade of first detection, then localization and identification of a target object, but also inconsistent with models assuming that as soon as a target is detected all its properties, spatial as well as non-spatial (e.g., its category), are available immediately. As an alternative, we propose a model of detection and localization tasks based on random walk processes, which can account for the present findings.

Virtual strain gage size study

DOE PAGES

Reu, Phillip L.

2015-09-22

DIC is a non-linear low-pass spatial filtering operation; whether we consider the effect of the subset and shape function, the strain window used in the strain calculation, of other post-processing of the results, each decision will impact the spatial resolution, of the measurement. More fundamentally, the speckle size limits, the spatial resolution by dictating the smallest possible subset. After this decision the processing settings are controlled by the allowable noise level balanced by possible bias errors created by the data filtering. This article describes a process to determine optimum DIC software settings to determine if the peak displacements or strainsmore » are being found.« less

Linking Science and Management in an Interactive Geospatial, Mutli-Criterion, Structured Decision Support Framework: Use Case Studies of the "Future Forests Geo-visualization and Decision Support Tool

NASA Astrophysics Data System (ADS)

Pontius, J.; Duncan, J.

2017-12-01

Land managers are often faced with balancing management activities to accomplish a diversity of management objectives, in systems faced with many stress agents. Advances in ecosystem modeling provide a rich source of information to inform management. Coupled with advances in decision support techniques and computing capabilities, interactive tools are now accessible for a broad audience of stakeholders. Here we present one such tool designed to capture information on how climate change may impact forested ecosystems, and how that impact varies spatially across the landscape. This tool integrates empirical models of current and future forest structure and function in a structured decision framework that allows users to customize weights for multiple management objectives and visualize suitability outcomes across the landscape. Combined with climate projections, the resulting products allow stakeholders to compare the relative success of various management objectives on a pixel by pixel basis and identify locations where management outcomes are most likely to be met. Here we demonstrate this approach with the integration of several of the preliminary models developed to map species distributions, sugar maple health, forest fragmentation risk and hemlock vulnerability to hemlock woolly adelgid under current and future climate scenarios. We compare three use case studies with objective weightings designed to: 1) Identify key parcels for sugarbush conservation and management, 2) Target state lands that may serve as hemlock refugia from hemlock woolly adelgid induced mortality, and 3) Examine how climate change may alter the success of managing for both sugarbush and hemlock across privately owned lands. This tool highlights the value of flexible models that can be easily run with customized weightings in a dynamic, integrated assessment that allows users to hone in on their potentially complex management objectives, and to visualize and prioritize locations across the landscape. It also demonstrates the importance of including climate considerations for long-term management. This merging of scientific knowledge with the diversity of stakeholder needs is an important step towards using science to inform management and policy decisions.

Toward a Multilingual, Experiential Environment for Learning Decision Technology.

ERIC Educational Resources Information Center

Yeo, Gee Kin; Tan, Seng Teen

1999-01-01

Describes work at the National University of Singapore on the Internet in expanding a simulation game used in supporting a course in decision technology. Topics include decision support systems, multilingual support for cross-cultural decision studies, process support in a World Wide Web-enhanced multiuser domain (MUD) learning environment, and…

Maintenance and operations decision support tool : Clarus regional demonstrations.

DOT National Transportation Integrated Search

2011-01-01

Weather affects almost all maintenance activity decisions. The Federal Highway Administration (FHWA) tested a new decision support system for maintenance in Iowa, Indiana, and Illinois called the Maintenance and Operations Decision Support System (MO...

DECISION-MAKING SPARK CHAMBERS,

DTIC Science & Technology

of scattering of a particle and coplanarity of two particles. Decision - making spark chambers are used to trigger an optical spark chamber of two...the position of a spark and the separation of two sparks. Many other kinds of spatial decisions can be made with these devices such as the recognition

Agricultural Decision Support Through Robust Assimilation of Satellite Derived Soil Moisture Estimates

NASA Astrophysics Data System (ADS)

Mishra, V.; Cruise, J.; Mecikalski, J. R.

2012-12-01

Soil Moisture is a key component in the hydrological process, affects surface and boundary layer energy fluxes and is the driving factor in agricultural production. Multiple in situ soil moisture measuring instruments such as Time-domain Reflectrometry (TDR), Nuclear Probes etc. are in use along with remote sensing methods like Active and Passive Microwave (PM) sensors. In situ measurements, despite being more accurate, can only be obtained at discrete points over small spatial scales. Remote sensing estimates, on the other hand, can be obtained over larger spatial domains with varying spatial and temporal resolutions. Soil moisture profiles derived from satellite based thermal infrared (TIR) imagery can overcome many of the problems associated with laborious in-situ observations over large spatial domains. An area where soil moisture observation and assimilation is receiving increasing attention is agricultural crop modeling. This study revolves around the use of the Decision Support System for Agrotechnology Transfer (DSSAT) crop model to simulate corn yields under various forcing scenarios. First, the model was run and calibrated using observed precipitation and model generated soil moisture dynamics. Next, the modeled soil moisture was updated using estimates derived from satellite based TIR imagery and the Atmospheric Land Exchange Inverse (ALEXI) model. We selected three climatically different locations to test the concept. Test Locations were selected to represent varied climatology. Bell Mina, Alabama - South Eastern United States, representing humid subtropical climate. Nabb, Indiana - Mid Western United States, representing humid continental climate. Lubbok, Texas - Southern United States, representing semiarid steppe climate. A temporal (2000-2009) correlation analysis of the soil moisture values from both DSSAT and ALEXI were performed and validated against the Land Information System (LIS) soil moisture dataset. The results clearly show strong correlation (R = 73%) between ALEXI and DSSAT at Bell Mina. At Nabb and Lubbock the correlation was 50-60%. Further, multiple experiments were conducted for each location: a) a DSSAT rain-fed 10 year sequential run forced with daymet precipitation; b) a DSSAT sequential run with no precipitation data; and c) a DSSAT run forced with ALEXI soil moisture estimates alone. The preliminary results of all the experiments are quantified through soil moisture correlations and yield comparisons. In general, the preliminary results strongly suggest that DSSAT forced with ALEXI can provide significant information especially at locations where no significant precipitation data exists.

The Role of Health Care Provider and Partner Decisional Support in Patients' Cancer Treatment Decision-Making Satisfaction.

PubMed

Palmer-Wackerly, Angela L; Krieger, Janice L; Rhodes, Nancy D

2017-01-01

Cancer patients rely on multiple sources of support when making treatment decisions; however, most research studies examine the influence of health care provider support while the influence of family member support is understudied. The current study fills this gap by examining the influence of health care providers and partners on decision-making satisfaction. In a cross-sectional study via an online Qualtrics panel, we surveyed cancer patients who reported that they had a spouse or romantic partner when making cancer treatment decisions (n = 479). Decisional support was measured using 5-point, single-item scales for emotional support, informational support, informational-advice support, and appraisal support. Decision-making satisfaction was measured using Holmes-Rovner and colleagues' (1996) Satisfaction With Decision Scale. We conducted a mediated regression analysis to examine treatment decision-making satisfaction for all participants and a moderated mediation analysis to examine treatment satisfaction among those patients offered a clinical trial. Results indicated that partner support significantly and partially mediated the relationship between health care provider support and patients' decision-making satisfaction but that results did not vary by enrollment in a clinical trial. This study shows how and why decisional support from partners affects communication between health care providers and cancer patients.

A Site-sPecific Agricultural water Requirement and footprint Estimator (SPARE:WATER 1.0)

NASA Astrophysics Data System (ADS)

Multsch, S.; Al-Rumaikhani, Y. A.; Frede, H.-G.; Breuer, L.

2013-07-01

The agricultural water footprint addresses the quantification of water consumption in agriculture, whereby three types of water to grow crops are considered, namely green water (consumed rainfall), blue water (irrigation from surface or groundwater) and grey water (water needed to dilute pollutants). By considering site-specific properties when calculating the crop water footprint, this methodology can be used to support decision making in the agricultural sector on local to regional scale. We therefore developed the spatial decision support system SPARE:WATER that allows us to quantify green, blue and grey water footprints on regional scale. SPARE:WATER is programmed in VB.NET, with geographic information system functionality implemented by the MapWinGIS library. Water requirements and water footprints are assessed on a grid basis and can then be aggregated for spatial entities such as political boundaries, catchments or irrigation districts. We assume inefficient irrigation methods rather than optimal conditions to account for irrigation methods with efficiencies other than 100%. Furthermore, grey water is defined as the water needed to leach out salt from the rooting zone in order to maintain soil quality, an important management task in irrigation agriculture. Apart from a thorough representation of the modelling concept, we provide a proof of concept where we assess the agricultural water footprint of Saudi Arabia. The entire water footprint is 17.0 km3 yr-1 for 2008, with a blue water dominance of 86%. Using SPARE:WATER we are able to delineate regional hot spots as well as crop types with large water footprints, e.g. sesame or dates. Results differ from previous studies of national-scale resolution, underlining the need for regional estimation of crop water footprints.

A decision support system for prioritizing forested wetland restoration in the Yazoo Backwater Area, Mississippi

USGS Publications Warehouse

O'Hara, Charles G.; Davis, Angela A.; Kleiss, Barbara A.

2000-01-01

A working prototype decision support system (DSS) was developed for the Yazoo Backwater Area, Mississippi, to help planners and managers prioritize, plan, conduct, and optimize forested wetland restoration activities. The DSS comprises geographic information system (GIS) spatial data themes, application programs that provide a cumulative analysis of the relative ability of sites to function as wetlands, and output data that are specific to a given restoration analysis scenario. The DSS input includes GIS data themes such as geomorphology, soils, land use, elevation, farmed wetlands, flood frequency, topographic depressions, streams, public lands, roads, and permanent water bodies, which can be used as spatial templates to define areal hydrologic settings. These GIS data themes can then be ranked and combined to estimate the relative suitability of a potential wetland restoration site, thereby, determining relative wetland equivalence on the landscape. The GIS applications used in this DSS perform the following three functions: assess the ecology (the Eco-Assessor); reclassify land-use in areas selected for restoration (the Tree-Translator); and generate output data to compare restoration scenarios (the Parameter-Generator). Areas selected for reforestation are translated (in the GIS) into ?forested? land use, and the tree species that are ?planted? on the landscape (in the DSS) either compose an ecologically optimal or an economically optimal community of tree species. Output from the DSS can be compared and analyzed by using economic, statistical, graphical, and tabular methods. Output data for seven selected scenarios were generated for the Yazoo Backwater Area and are presented as examples to illustrate the flexibility of the DSS to identify areas that meet restoration objectives.

Uncertainty and probability in wildfire management decision support: An example from the United States [Chapter 4

Treesearch

Matthew Thompson; David Calkin; Joe H. Scott; Michael Hand

2017-01-01

Wildfire risk assessment is increasingly being adopted to support federal wildfire management decisions in the United States. Existing decision support systems, specifically the Wildland Fire Decision Support System (WFDSS), provide a rich set of probabilistic and risk‐based information to support the management of active wildfire incidents. WFDSS offers a wide range...

Interprofessional practice and decision support: an organizational framework applied to a mental health setting.

PubMed

Campbell, Susan; Stowe, Karen; Ozanne, Elissa M

2011-11-01

Decision support as a means to assist people in making healthcare decisions has been discussed extensively in the medical literature. However, the potential for use of decision support and decision aids with people with psychiatric disabilities in order to promote recovery has only begun to be researched and discussed in the mental health literature. Organizational factors that foster interprofessional practice within a decision support environment focused on mental health issues are examined in this paper.

Team performance in networked supervisory control of unmanned air vehicles: effects of automation, working memory, and communication content.

PubMed

McKendrick, Ryan; Shaw, Tyler; de Visser, Ewart; Saqer, Haneen; Kidwell, Brian; Parasuraman, Raja

2014-05-01

Assess team performance within a net-worked supervisory control setting while manipulating automated decision aids and monitoring team communication and working memory ability. Networked systems such as multi-unmanned air vehicle (UAV) supervision have complex properties that make prediction of human-system performance difficult. Automated decision aid can provide valuable information to operators, individual abilities can limit or facilitate team performance, and team communication patterns can alter how effectively individuals work together. We hypothesized that reliable automation, higher working memory capacity, and increased communication rates of task-relevant information would offset performance decrements attributed to high task load. Two-person teams performed a simulated air defense task with two levels of task load and three levels of automated aid reliability. Teams communicated and received decision aid messages via chat window text messages. Task Load x Automation effects were significant across all performance measures. Reliable automation limited the decline in team performance with increasing task load. Average team spatial working memory was a stronger predictor than other measures of team working memory. Frequency of team rapport and enemy location communications positively related to team performance, and word count was negatively related to team performance. Reliable decision aiding mitigated team performance decline during increased task load during multi-UAV supervisory control. Team spatial working memory, communication of spatial information, and team rapport predicted team success. An automated decision aid can improve team performance under high task load. Assessment of spatial working memory and the communication of task-relevant information can help in operator and team selection in supervisory control systems.

Socio-Ecohydrologic Agents And Services: Integrating Human And Natural Components To Address Coupled System Resilience

NASA Astrophysics Data System (ADS)

Pavao-zuckerman, M.; Pope, A.; Chan, D.; Curl, K.; Gimblett, H. R.; Hough, M.; House-Peters, L.; Lee, R.; Scott, C. A.

2012-12-01

Riparian corridors in arid regions are highly valued for their relative scarcity, and because healthy riparian systems support high levels of biodiversity, can meet human demand for water and water-related resources and functions. Our team is taking a transdiciplinary social-ecological systems approach to assessing riparian corridor resilience in two watersheds (the San Pedro River in USA and Mexico, and the Rio San Miguel in Mexico) through a project funded by the NSF CNH program ("Strengthening Resilience of Arid Region Riparian Corridors"). Multiple perspectives are integrated in the project, including hydrology, ecology, institutional dynamics, and decision making (at the level of both policy and individual choice), as well as the perspectives of various stakeholder groups and individuals in the watersheds. Here we discuss initial findings that center around linking changes in ecohydrology and livelihoods related to decisions in response to climatic, ecological, and social change. The research team is implementing two approaches to integrate the disparate disciplines participating in the research (and the varied perspectives among the stakeholders in this binational riparian context): (1) ecosystem service assessment, and (2) agent based model simulation. We are developing an ecosystem service perspective that provides a bridge between ecological dynamics in the landscape and varied stakeholder perspectives on the implications of ecohydrology for well-being (economic, cultural, ecological). Services are linked on one hand to the spatial patterns of traits of individuals within species (allowing a more predictive application of ecosystem services as they vary with community change in time), and to stakeholder perspectives (facilitating integration of ecosystem services into our understanding of decision making processes) in a case study in the San Pedro River National Conservation Area. The agent- based model (ABM) approach incorporates the influence of human decision-making on spatially-explicit landscapes in a mechanistic way, taking into account social interaction, adaptation, and decision-making at different levels, allowing individual stakeholders to make decisions based on their unique perceptions of their environment, be it economic, social, or ecological awareness. Initial parameterization of the ABM proceeds from a case study centered in the town of Rayón, Sonora, Mexico, where semi-structured interviews were used to elicit perceptions by water resource users of CNH function, change, and solutions relating to livelihood changes in response to several drivers. In both case studies, we see the potential and limitations for an approach to adaptive management and decision support related to water resources that links ecosystem services and agent-based modeling. Methodologically, synthetic approaches such as these may allow coupling of systems for improved assessment and analysis, while at the same time lack a connection to the perspectives of water users and managers on the ground. There is thus potential for a either a loss of system resilience in the face of external change, or an opportunity to increase system resilience by building off perspectives already in place within these coupled socio-ecohydrologic systems.

Implementation of workflow engine technology to deliver basic clinical decision support functionality.

PubMed

Huser, Vojtech; Rasmussen, Luke V; Oberg, Ryan; Starren, Justin B

2011-04-10

Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. We describe an implementation of a free workflow technology software suite (available at http://code.google.com/p/healthflow) and its application in the domain of clinical decision support. Our implementation seamlessly supports clinical logic testing on retrospective data and offers a user-friendly knowledge representation paradigm. With the presented software implementation, we demonstrate that workflow engine technology can provide a decision support platform which evaluates well against an established clinical decision support architecture evaluation framework. Due to cross-industry usage of workflow engine technology, we can expect significant future functionality enhancements that will further improve the technology's capacity to serve as a clinical decision support platform.

Elucidating the significance of spatial memory on movement decisions by African savannah elephants using state–space models

PubMed Central

Polansky, Leo; Kilian, Werner; Wittemyer, George

2015-01-01

Spatial memory facilitates resource acquisition where resources are patchy, but how it influences movement behaviour of wide-ranging species remains to be resolved. We examined African elephant spatial memory reflected in movement decisions regarding access to perennial waterholes. State–space models of movement data revealed a rapid, highly directional movement behaviour almost exclusively associated with visiting perennial water. Behavioural change point (BCP) analyses demonstrated that these goal-oriented movements were initiated on average 4.59 km, and up to 49.97 km, from the visited waterhole, with the closest waterhole accessed 90% of the time. Distances of decision points increased when switching to different waterholes, during the dry season, or for female groups relative to males, while selection of the closest waterhole decreased when switching. Overall, our analyses indicated detailed spatial knowledge over large scales, enabling elephants to minimize travel distance through highly directional movement when accessing water. We discuss the likely cognitive and socioecological mechanisms driving these spatially precise movements that are most consistent with our findings. By applying modern analytic techniques to high-resolution movement data, this study illustrates emerging approaches for studying how cognition structures animal movement behaviour in different ecological and social contexts. PMID:25808888

Spatial Downscaling of Alien Species Presences using Machine Learning

NASA Astrophysics Data System (ADS)

Daliakopoulos, Ioannis N.; Katsanevakis, Stelios; Moustakas, Aristides

2017-07-01

Large scale, high-resolution data on alien species distributions are essential for spatially explicit assessments of their environmental and socio-economic impacts, and management interventions for mitigation. However, these data are often unavailable. This paper presents a method that relies on Random Forest (RF) models to distribute alien species presence counts at a finer resolution grid, thus achieving spatial downscaling. A sufficiently large number of RF models are trained using random subsets of the dataset as predictors, in a bootstrapping approach to account for the uncertainty introduced by the subset selection. The method is tested with an approximately 8×8 km2 grid containing floral alien species presence and several indices of climatic, habitat, land use covariates for the Mediterranean island of Crete, Greece. Alien species presence is aggregated at 16×16 km2 and used as a predictor of presence at the original resolution, thus simulating spatial downscaling. Potential explanatory variables included habitat types, land cover richness, endemic species richness, soil type, temperature, precipitation, and freshwater availability. Uncertainty assessment of the spatial downscaling of alien species’ occurrences was also performed and true/false presences and absences were quantified. The approach is promising for downscaling alien species datasets of larger spatial scale but coarse resolution, where the underlying environmental information is available at a finer resolution than the alien species data. Furthermore, the RF architecture allows for tuning towards operationally optimal sensitivity and specificity, thus providing a decision support tool for designing a resource efficient alien species census.

Spatial modeling and classification of corneal shape.

PubMed

Marsolo, Keith; Twa, Michael; Bullimore, Mark A; Parthasarathy, Srinivasan

2007-03-01

One of the most promising applications of data mining is in biomedical data used in patient diagnosis. Any method of data analysis intended to support the clinical decision-making process should meet several criteria: it should capture clinically relevant features, be computationally feasible, and provide easily interpretable results. In an initial study, we examined the feasibility of using Zernike polynomials to represent biomedical instrument data in conjunction with a decision tree classifier to distinguish between the diseased and non-diseased eyes. Here, we provide a comprehensive follow-up to that work, examining a second representation, pseudo-Zernike polynomials, to determine whether they provide any increase in classification accuracy. We compare the fidelity of both methods using residual root-mean-square (rms) error and evaluate accuracy using several classifiers: neural networks, C4.5 decision trees, Voting Feature Intervals, and Naïve Bayes. We also examine the effect of several meta-learning strategies: boosting, bagging, and Random Forests (RFs). We present results comparing accuracy as it relates to dataset and transformation resolution over a larger, more challenging, multi-class dataset. They show that classification accuracy is similar for both data transformations, but differs by classifier. We find that the Zernike polynomials provide better feature representation than the pseudo-Zernikes and that the decision trees yield the best balance of classification accuracy and interpretability.

Knowledge to Action - Understanding Natural Hazards-Induced Power Outage Scenarios for Actionable Disaster Responses

NASA Astrophysics Data System (ADS)

Kar, B.; Robinson, C.; Koch, D. B.; Omitaomu, O.

2017-12-01

The Sendai Framework for Disaster Risk Reduction 2015-2030 identified the following four priorities to prevent and reduce disaster risks: i) understanding disaster risk; ii) strengthening governance to manage disaster risk; iii) investing in disaster risk reduction for resilience and; iv) enhancing disaster preparedness for effective response, and to "Build Back Better" in recovery, rehabilitation and reconstruction. While forecasting and decision making tools are in place to predict and understand future impacts of natural hazards, the knowledge to action approach that currently exists fails to provide updated information needed by decision makers to undertake response and recovery efforts following a hazard event. For instance, during a tropical storm event advisories are released every two to three hours, but manual analysis of geospatial data to determine potential impacts of the event tends to be time-consuming and a post-event process. Researchers at Oak Ridge National Laboratory have developed a Spatial Decision Support System that enables real-time analysis of storm impact based on updated advisory. A prototype of the tool that focuses on determining projected power outage areas and projected duration of outages demonstrates the feasibility of integrating science with decision making for emergency management personnel to act in real time to protect communities and reduce risk.

An extreme events laboratory to provide network centric collaborative situation assessment and decision making

NASA Astrophysics Data System (ADS)

Panulla, Brian J.; More, Loretta D.; Shumaker, Wade R.; Jones, Michael D.; Hooper, Robert; Vernon, Jeffrey M.; Aungst, Stanley G.

2009-05-01

Rapid improvements in communications infrastructure and sophistication of commercial hand-held devices provide a major new source of information for assessing extreme situations such as environmental crises. In particular, ad hoc collections of humans can act as "soft sensors" to augment data collected by traditional sensors in a net-centric environment (in effect, "crowd-sourcing" observational data). A need exists to understand how to task such soft sensors, characterize their performance and fuse the data with traditional data sources. In order to quantitatively study such situations, as well as study distributed decision-making, we have developed an Extreme Events Laboratory (EEL) at The Pennsylvania State University. This facility provides a network-centric, collaborative situation assessment and decision-making capability by supporting experiments involving human observers, distributed decision making and cognition, and crisis management. The EEL spans the information chain from energy detection via sensors, human observations, signal and image processing, pattern recognition, statistical estimation, multi-sensor data fusion, visualization and analytics, and modeling and simulation. The EEL command center combines COTS and custom collaboration tools in innovative ways, providing capabilities such as geo-spatial visualization and dynamic mash-ups of multiple data sources. This paper describes the EEL and several on-going human-in-the-loop experiments aimed at understanding the new collective observation and analysis landscape.

An integrated decision support system for diagnosing and managing patients with community-acquired pneumonia.

PubMed Central

Aronsky, D.; Haug, P. J.

1999-01-01

Decision support systems that integrate guidelines have become popular applications to reduce variation and deliver cost-effective care. However, adverse characteristics of decision support systems, such as additional and time-consuming data entry or manually identifying eligible patients, result in a "behavioral bottleneck" that prevents decision support systems to become part of the clinical routine. This paper describes the design and the implementation of an integrated decision support system that explores a novel approach for bypassing the behavioral bottleneck. The real-time decision support system does not require health care providers to enter additional data and consists of a diagnostic and a management component. Images Fig. 1 Fig. 2 Fig. 3 PMID:10566348

Offside Decisions by Expert Assistant Referees in Association Football: Perception and Recall of Spatial Positions in Complex Dynamic Events

ERIC Educational Resources Information Center

Gilis, Bart; Helsen, Werner; Catteeuw, Peter; Wagemans, Johan

2008-01-01

This study investigated the offside decision-making process in association football. The first aim was to capture the specific offside decision-making skills in complex dynamic events. Second, we analyzed the type of errors to investigate the factors leading to incorrect decisions. Federation Internationale de Football Association (FIFA; n = 29)…

Stakeholder views of management and decision support tools to integrate climate change into Great Lakes Lake Whitefish management

USGS Publications Warehouse

Lynch, Abigail J.; Taylor, William W.; McCright, Aaron M.

2016-01-01

Decision support tools can aid decision making by systematically incorporating information, accounting for uncertainties, and facilitating evaluation between alternatives. Without user buy-in, however, decision support tools can fail to influence decision-making processes. We surveyed fishery researchers, managers, and fishers affiliated with the Lake Whitefish Coregonus clupeaformis fishery in the 1836 Treaty Waters of Lakes Huron, Michigan, and Superior to assess opinions of current and future management needs to identify barriers to, and opportunities for, developing a decision support tool based on Lake Whitefish recruitment projections with climate change. Approximately 64% of 39 respondents were satisfied with current management, and nearly 85% agreed that science was well integrated into management programs. Though decision support tools can facilitate science integration into management, respondents suggest that they face significant implementation barriers, including lack of political will to change management and perceived uncertainty in decision support outputs. Recommendations from this survey can inform development of decision support tools for fishery management in the Great Lakes and other regions.

Structured decision making as a framework for large-scale wildlife harvest management decisions

USGS Publications Warehouse

Robinson, Kelly F.; Fuller, Angela K.; Hurst, Jeremy E.; Swift, Bryan L.; Kirsch, Arthur; Farquhar, James F.; Decker, Daniel J.; Siemer, William F.

2016-01-01

Fish and wildlife harvest management at large spatial scales often involves making complex decisions with multiple objectives and difficult tradeoffs, population demographics that vary spatially, competing stakeholder values, and uncertainties that might affect management decisions. Structured decision making (SDM) provides a formal decision analytic framework for evaluating difficult decisions by breaking decisions into component parts and separating the values of stakeholders from the scientific evaluation of management actions and uncertainty. The result is a rigorous, transparent, and values-driven process. This decision-aiding process provides the decision maker with a more complete understanding of the problem and the effects of potential management actions on stakeholder values, as well as how key uncertainties can affect the decision. We use a case study to illustrate how SDM can be used as a decision-aiding tool for management decision making at large scales. We evaluated alternative white-tailed deer (Odocoileus virginianus) buck-harvest regulations in New York designed to reduce harvest of yearling bucks, taking into consideration the values of the state wildlife agency responsible for managing deer, as well as deer hunters. We incorporated tradeoffs about social, ecological, and economic management concerns throughout the state. Based on the outcomes of predictive models, expert elicitation, and hunter surveys, the SDM process identified management alternatives that optimized competing objectives. The SDM process provided biologists and managers insight about aspects of the buck-harvest decision that helped them adopt a management strategy most compatible with diverse hunter values and management concerns.

Cyborg practices: call-handlers and computerised decision support systems in urgent and emergency care.

PubMed

Pope, Catherine; Halford, Susan; Turnbull, Joanne; Prichard, Jane

2014-06-01

This article draws on data collected during a 2-year project examining the deployment of a computerised decision support system. This computerised decision support system was designed to be used by non-clinical staff for dealing with calls to emergency (999) and urgent care (out-of-hours) services. One of the promises of computerised decisions support technologies is that they can 'hold' vast amounts of sophisticated clinical knowledge and combine it with decision algorithms to enable standardised decision-making by non-clinical (clerical) staff. This article draws on our ethnographic study of this computerised decision support system in use, and we use our analysis to question the 'automated' vision of decision-making in healthcare call-handling. We show that embodied and experiential (human) expertise remains central and highly salient in this work, and we propose that the deployment of the computerised decision support system creates something new, that this conjunction of computer and human creates a cyborg practice.

Development of a decision support system for analysis and solutions of prolonged standing in the workplace.

PubMed

Halim, Isa; Arep, Hambali; Kamat, Seri Rahayu; Abdullah, Rohana; Omar, Abdul Rahman; Ismail, Ahmad Rasdan

2014-06-01

Prolonged standing has been hypothesized as a vital contributor to discomfort and muscle fatigue in the workplace. The objective of this study was to develop a decision support system that could provide systematic analysis and solutions to minimize the discomfort and muscle fatigue associated with prolonged standing. The integration of object-oriented programming and a Model Oriented Simultaneous Engineering System were used to design the architecture of the decision support system. Validation of the decision support system was carried out in two manufacturing companies. The validation process showed that the decision support system produced reliable results. The decision support system is a reliable advisory tool for providing analysis and solutions to problems related to the discomfort and muscle fatigue associated with prolonged standing. Further testing of the decision support system is suggested before it is used commercially.

Development of a Decision Support System for Analysis and Solutions of Prolonged Standing in the Workplace

PubMed Central

Halim, Isa; Arep, Hambali; Kamat, Seri Rahayu; Abdullah, Rohana; Omar, Abdul Rahman; Ismail, Ahmad Rasdan

2014-01-01

Background Prolonged standing has been hypothesized as a vital contributor to discomfort and muscle fatigue in the workplace. The objective of this study was to develop a decision support system that could provide systematic analysis and solutions to minimize the discomfort and muscle fatigue associated with prolonged standing. Methods The integration of object-oriented programming and a Model Oriented Simultaneous Engineering System were used to design the architecture of the decision support system. Results Validation of the decision support system was carried out in two manufacturing companies. The validation process showed that the decision support system produced reliable results. Conclusion The decision support system is a reliable advisory tool for providing analysis and solutions to problems related to the discomfort and muscle fatigue associated with prolonged standing. Further testing of the decision support system is suggested before it is used commercially. PMID:25180141

The neural substrates of deliberative decision making: contrasting effects of hippocampus lesions on performance and vicarious trial-and-error behavior in a spatial memory task and a visual discrimination task

PubMed Central

Bett, David; Allison, Elizabeth; Murdoch, Lauren H.; Kaefer, Karola; Wood, Emma R.; Dudchenko, Paul A.

2012-01-01

Vicarious trial-and-errors (VTEs) are back-and-forth movements of the head exhibited by rodents and other animals when faced with a decision. These behaviors have recently been associated with prospective sweeps of hippocampal place cell firing, and thus may reflect a rodent model of deliberative decision-making. The aim of the current study was to test whether the hippocampus is essential for VTEs in a spatial memory task and in a simple visual discrimination (VD) task. We found that lesions of the hippocampus with ibotenic acid produced a significant impairment in the accuracy of choices in a serial spatial reversal (SR) task. In terms of VTEs, whereas sham-lesioned animals engaged in more VTE behavior prior to identifying the location of the reward as opposed to repeated trials after it had been located, the lesioned animals failed to show this difference. In contrast, damage to the hippocampus had no effect on acquisition of a VD or on the VTEs seen in this task. For both lesion and sham-lesion animals, adding an additional choice to the VD increased the number of VTEs and decreased the accuracy of choices. Together, these results suggest that the hippocampus may be specifically involved in VTE behavior during spatial decision making. PMID:23115549

Decision Making on Regional Landfill Site Selection in Hormozgan Province Using Smce

NASA Astrophysics Data System (ADS)

Majedi, A. S.; Kamali, B. M.; Maghsoudi, R.

2015-12-01

Landfill site selection and suitable conditions to bury hazardous wastes are among the most critical issues in modern societies. Taking several factors and limitations into account along with true decision making requires application of different decision techniques. To this end, current paper aims to make decisions about regional landfill site selection in Hormozgan province and utilizes SMCE technique combined with qualitative and quantitative criteria to select the final alternatives. To this respect, we first will describe the existing environmental situation in our study area and set the goals of our study in the framework of SMCE and will analyze the effective factors in regional landfill site selection. Then, methodological procedure of research was conducted using Delphi approach and questionnaires (in order to determine research validity, Chronbach Alpha (0.94) method was used). Spatial multi-criteria analysis model was designed in the form of criteria tree in SMCE using IL WIS software. Prioritization of respective spatial alternatives included: Bandar Abbas city with total 4 spatial alternatives (one zone with 1st priority, one zone with 3rd priority and two zones with 4thpriority) was considered the first priority, Bastak city with total 3 spatial alternatives (one zone with 2nd priority, one zone with 3rdpriorit and one zone with 4th priority) was the second priority and Bandar Abbas, Minab, Jask and Haji Abad cities were considered as the third priority.

Developing the U.S. Wildland Fire Decision Support System

Treesearch

Erin Noonan-Wright; Tonja S. Opperman; Mark A. Finney; Tom Zimmerman; Robert C. Seli; Lisa M. Elenz; David E. Calkin; John R. Fiedler

2011-01-01

A new decision support tool, the Wildland Fire Decision Support System (WFDSS) has been developed to support risk-informed decision-making for individual fires in the United States. WFDSS accesses national weather data and forecasts, fire behavior prediction, economic assessment, smoke management assessment, and landscape databases to efficiently formulate and apply...

Decision Support for Ecosystem Management (Chapter 28)

Treesearch

Keith Reynolds; Jennifer Bjork; Rachel Riemann Hershey; Dan Schmoldt; John Payne; Susan King; Lee DeCola; Mark J. Twery; Pat Cunningham

1999-01-01

This chapter presents a management perspective on decision support for ecosystem management.The Introduction provides a brief historical overview of decision support technology as it has been used in natural resource management, discusses the role of decision support in ecosystem management as we see it, and summarizes the current state of the technology.

Watermark: An Application and Methodology and Application for Interactive and intelligent Decision Support for Groundwater Systems

NASA Astrophysics Data System (ADS)

Pierce, S. A.; Wagner, K.; Schwartz, S.; Gentle, J. N., Jr.

2016-12-01

Critical water resources face the effects of historic drought, increased demand, and potential contamination, the need has never been greater to develop resources to effectively communicate conservation and protection across a broad audience and geographical area. The Watermark application and macro-analysis methodology merges topical analysis of context rich corpus from policy texts with multi-attributed solution sets from integrated models of water resource and other subsystems, such as mineral, food, energy, or environmental systems to construct a scalable, robust, and reproducible approach for identifying links between policy and science knowledge bases. The Watermark application is an open-source, interactive workspace to support science-based visualization and decision making. Designed with generalization in mind, Watermark is a flexible platform that allows for data analysis and inclusion of large datasets with an interactive front-end capable of connecting with other applications as well as advanced computing resources. In addition, the Watermark analysis methodology offers functionality that streamlines communication with non-technical users for policy, education, or engagement with groups around scientific topics of societal relevance. The technology stack for Watermark was selected with the goal of creating a robust and dynamic modular codebase that can be adjusted to fit many use cases and scale to support usage loads that range between simple data display to complex scientific simulation-based modelling and analytics. The methodology uses to topical analysis and simulation-optimization to systematically analyze the policy and management realities of resource systems and explicitly connect the social and problem contexts with science-based and engineering knowledge from models. A case example demonstrates use in a complex groundwater resources management study highlighting multi-criteria spatial decision making and uncertainty comparisons.

Tethys: A Platform for Water Resources Modeling and Decision Support Apps

NASA Astrophysics Data System (ADS)

Nelson, J.; Swain, N. R.

2015-12-01

The interactive nature of web applications or "web apps" makes it an excellent medium for conveying complex scientific concepts to lay audiences and creating decision support tools that harness cutting edge modeling techniques. However, the technical expertise required to develop web apps represents a barrier for would-be developers. This barrier can be characterized by the following hurdles that developers must overcome: (1) identify, select, and install software that meet the spatial and computational capabilities commonly required for water resources modeling; (2) orchestrate the use of multiple free and open source (FOSS) projects and navigate their differing application programming interfaces; (3) learn the multi-language programming skills required for modern web development; and (4) develop a web-secure and fully featured web portal to host the app. Tethys Platform has been developed to lower the technical barrier and minimize the initial development investment that prohibits many scientists and engineers from making use of the web app medium. It includes (1) a suite of FOSS that address the unique data and computational needs common to water resources web app development, (2) a Python software development kit that streamlines development, and (3) a customizable web portal that is used to deploy the completed web apps. Tethys synthesizes several software projects including PostGIS, 52°North WPS, GeoServer, Google Maps™, OpenLayers, and Highcharts. It has been used to develop a broad array of web apps for water resources modeling and decision support for several projects including CI-WATER, HydroShare, and the National Flood Interoperability Experiment. The presentation will include live demos of some of the apps that have been developed using Tethys to demonstrate its capabilities.

Validating a spatially distributed hydrological model with soil morphology data

NASA Astrophysics Data System (ADS)

Doppler, T.; Honti, M.; Zihlmann, U.; Weisskopf, P.; Stamm, C.

2013-10-01

Spatially distributed hydrological models are popular tools in hydrology and they are claimed to be useful to support management decisions. Despite the high spatial resolution of the computed variables, calibration and validation is often carried out only on discharge time-series at specific locations due to the lack of spatially distributed reference data. Because of this restriction, the predictive power of these models, with regard to predicted spatial patterns, can usually not be judged. An example of spatial predictions in hydrology is the prediction of saturated areas in agricultural catchments. These areas can be important source areas for the transport of agrochemicals to the stream. We set up a spatially distributed model to predict saturated areas in a 1.2 km2 catchment in Switzerland with moderate topography. Around 40% of the catchment area are artificially drained. We measured weather data, discharge and groundwater levels in 11 piezometers for 1.5 yr. For broadening the spatially distributed data sets that can be used for model calibration and validation, we translated soil morphological data available from soil maps into an estimate of the duration of soil saturation in the soil horizons. We used redox-morphology signs for these estimates. This resulted in a data set with high spatial coverage on which the model predictions were validated. In general, these saturation estimates corresponded well to the measured groundwater levels. We worked with a model that would be applicable for management decisions because of its fast calculation speed and rather low data requirements. We simultaneously calibrated the model to the groundwater levels in the piezometers and discharge. The model was able to reproduce the general hydrological behavior of the catchment in terms of discharge and absolute groundwater levels. However, the accuracy of the groundwater level predictions was not high enough to be used for the prediction of saturated areas. The groundwater level dynamics were not adequately reproduced and the predicted spatial patterns of soil saturation did not correspond to the patterns estimated from the soil map. Our results indicate that an accurate prediction of the groundwater level dynamics of the shallow groundwater in our catchment that is subject to artificial drainage would require a more complex model. Especially high spatial resolution and very detailed process representations at the boundary between the unsaturated and the saturated zone are expected to be crucial. The data needed for such a detailed model are not generally available. The high computational demand and the complex model setup would require more resources than the direct identification of saturated areas in the field. This severely hampers the practical use of such models despite their usefulness for scientific purposes.

SANDS: a service-oriented architecture for clinical decision support in a National Health Information Network.

PubMed

Wright, Adam; Sittig, Dean F

2008-12-01

In this paper, we describe and evaluate a new distributed architecture for clinical decision support called SANDS (Service-oriented Architecture for NHIN Decision Support), which leverages current health information exchange efforts and is based on the principles of a service-oriented architecture. The architecture allows disparate clinical information systems and clinical decision support systems to be seamlessly integrated over a network according to a set of interfaces and protocols described in this paper. The architecture described is fully defined and developed, and six use cases have been developed and tested using a prototype electronic health record which links to one of the existing prototype National Health Information Networks (NHIN): drug interaction checking, syndromic surveillance, diagnostic decision support, inappropriate prescribing in older adults, information at the point of care and a simple personal health record. Some of these use cases utilize existing decision support systems, which are either commercially or freely available at present, and developed outside of the SANDS project, while other use cases are based on decision support systems developed specifically for the project. Open source code for many of these components is available, and an open source reference parser is also available for comparison and testing of other clinical information systems and clinical decision support systems that wish to implement the SANDS architecture. The SANDS architecture for decision support has several significant advantages over other architectures for clinical decision support. The most salient of these are:

Whose decision is it anyway? How clinicians support decision-making participation after acquired brain injury.

PubMed

Knox, Lucy; Douglas, Jacinta M; Bigby, Christine

2013-01-01

To raise professional awareness of factors that may influence the support offered by clinicians to people with acquired brain injury (ABI), and to consider the potential implications of these factors in terms of post-injury rehabilitation and living. A review of the literature was conducted to identify factors that determine how clinicians provide support and influence opportunities for individuals with ABI to participate in decision making across the rehabilitation continuum. Clinical case studies are used to highlight two specific issues: (1) hidden assumptions on the part of the practitioner, and (2) perceptions of risk operating in clinical practice. There are a range of factors which may influence the decision-making support provided by clinicians and, ultimately, shape lifetime outcomes for individuals with ABI. A multidimensional framework may assist clinicians to identify relevant factors and consider their potential implications including those that influence how clinicians involved in supporting decision making approach this task. Participation in decision making is an undisputed human right and central to the provision of person-centred care. Further research is required to understand how clinical practice can maximise both opportunities and support for increased decision-making participation by individuals with ABI. There is an increasing focus on the rights of all individuals to be supported to participate in decision making about their life. A number of changes associated with ABI mean that individuals with ABI will require support with decision making. Clinicians have a critical role in providing this support over the course of the rehabilitation continuum. Clinicians need to be aware of the range of factors that may influence the decision-making support they provide. A multidimensional framework may be used by clinicians to identify influences on the decision-making support they provide.

Integrating seasonal climate prediction and agricultural models for insights into agricultural practice

PubMed Central

Hansen, James W

2005-01-01

Interest in integrating crop simulation models with dynamic seasonal climate forecast models is expanding in response to a perceived opportunity to add value to seasonal climate forecasts for agriculture. Integrated modelling may help to address some obstacles to effective agricultural use of climate information. First, modelling can address the mismatch between farmers' needs and available operational forecasts. Probabilistic crop yield forecasts are directly relevant to farmers' livelihood decisions and, at a different scale, to early warning and market applications. Second, credible ex ante evidence of livelihood benefits, using integrated climate–crop–economic modelling in a value-of-information framework, may assist in the challenge of obtaining institutional, financial and political support; and inform targeting for greatest benefit. Third, integrated modelling can reduce the risk and learning time associated with adaptation and adoption, and related uncertainty on the part of advisors and advocates. It can provide insights to advisors, and enhance site-specific interpretation of recommendations when driven by spatial data. Model-based ‘discussion support systems’ contribute to learning and farmer–researcher dialogue. Integrated climate–crop modelling may play a genuine, but limited role in efforts to support climate risk management in agriculture, but only if they are used appropriately, with understanding of their capabilities and limitations, and with cautious evaluation of model predictions and of the insights that arises from model-based decision analysis. PMID:16433092

Spatially explicit modeling of greater sage-grouse (Centrocercus urophasianus) habitat in Nevada and northeastern California: a decision-support tool for management

USGS Publications Warehouse

Coates, Peter S.; Casazza, Michael L.; Brussee, Brianne E.; Ricca, Mark A.; Gustafson, K. Benjamin; Overton, Cory T.; Sanchez-Chopitea, Erika; Kroger, Travis; Mauch, Kimberly; Niell, Lara; Howe, Kristy; Gardner, Scott; Espinosa, Shawn; Delehanty, David J.

2014-01-01

Greater sage-grouse (Centrocercus urophasianus, hereafter referred to as “sage-grouse”) populations are declining throughout the sagebrush (Artemisia spp.) ecosystem, including millions of acres of potential habitat across the West. Habitat maps derived from empirical data are needed given impending listing decisions that will affect both sage-grouse population dynamics and human land-use restrictions. This report presents the process for developing spatially explicit maps describing relative habitat suitability for sage-grouse in Nevada and northeastern California. Maps depicting habitat suitability indices (HSI) values were generated based on model-averaged resource selection functions informed by more than 31,000 independent telemetry locations from more than 1,500 radio-marked sage-grouse across 12 project areas in Nevada and northeastern California collected during a 15-year period (1998–2013). Modeled habitat covariates included land cover composition, water resources, habitat configuration, elevation, and topography, each at multiple spatial scales that were relevant to empirically observed sage-grouse movement patterns. We then present an example of how the HSI can be delineated into categories. Specifically, we demonstrate that the deviation from the mean can be used to classify habitat suitability into three categories of habitat quality (high, moderate, and low) and one non-habitat category. The classification resulted in an agreement of 93–97 percent for habitat versus non-habitat across a suite of independent validation datasets. Lastly, we provide an example of how space use models can be integrated with habitat models to help inform conservation planning. In this example, we combined probabilistic breeding density with a non-linear probability of occurrence relative to distance to nearest lek (traditional breeding ground) using count data to calculate a composite space use index (SUI). The SUI was then classified into two categories of use (high and low-to-no) and intersected with the HSI categories to create potential management prioritization scenarios based oninformation about sage-grouse occupancy coupled with habitat suitability. This provided an example of a conservation planning application that uses the intersection of the spatially-explicit HSI and empirically-based SUI to identify potential spatially explicit strategies for sage-grouse management. Importantly, the reported categories for the HSI and SUI can be reclassified relatively easily to employ alternative conservation thresholds that may be identified through decision-making processes with stake-holders, managers, and biologists. Moreover, the HSI/SUI interface map can be updated readily as new data become available.

Web-based geo-visualisation of spatial information to support evidence-based health policy: a case study of the development process of HealthTracks.

PubMed

Jardine, Andrew; Mullan, Narelle; Gudes, Ori; Cosford, James; Moncrieff, Simon; West, Geoff; Xiao, Jianguo; Yun, Grace; Someford, Peter

Place is of critical importance to health as it can reveal patterns of disease spread and clustering, associations with risk factors, and areas with greatest need for, or least access to healthcare services and promotion activities. Furthermore, in order to get a good understanding of the health status and needs of a particular area a broad range of data are required which can often be difficult and time consuming to obtain and collate. This process has been expedited by bringing together multiple data sources and making them available in an online geo-visualisation, HealthTracks, which consists of a mapping and reporting component. The overall aim of the HealthTracks project is to make spatial health information more accessible to policymakers, analysts, planners and program managers to inform decision-making across the Department of Health Western Australia. Preliminary mapping and reporting applications that have been utilised to inform service planning, increased awareness of the utility of spatial information and improved efficiency in data access were developed. The future for HealthTracks involves expanding the range of data available and developing new analytical capabilities in order to work towards providing external agencies, researchers and eventually the general public access to rich local area spatial data.

Decision support for the selection of reference sites using 137Cs as a soil erosion tracer

NASA Astrophysics Data System (ADS)

Arata, Laura; Meusburger, Katrin; Bürge, Alexandra; Zehringer, Markus; Ketterer, Michael E.; Mabit, Lionel; Alewell, Christine

2017-08-01

The classical approach of using 137Cs as a soil erosion tracer is based on the comparison between stable reference sites and sites affected by soil redistribution processes; it enables the derivation of soil erosion and deposition rates. The method is associated with potentially large sources of uncertainty with major parts of this uncertainty being associated with the selection of the reference sites. We propose a decision support tool to Check the Suitability of reference Sites (CheSS). Commonly, the variation among 137Cs inventories of spatial replicate reference samples is taken as the sole criterion to decide on the suitability of a reference inventory. Here we propose an extension of this procedure using a repeated sampling approach, in which the reference sites are resampled after a certain time period. Suitable reference sites are expected to present no significant temporal variation in their decay-corrected 137Cs depth profiles. Possible causes of variation are assessed by a decision tree. More specifically, the decision tree tests for (i) uncertainty connected to small-scale variability in 137Cs due to its heterogeneous initial fallout (such as in areas affected by the Chernobyl fallout), (ii) signs of erosion or deposition processes and (iii) artefacts due to the collection, preparation and measurement of the samples; (iv) finally, if none of the above can be assigned, this variation might be attributed to turbation processes (e.g. bioturbation, cryoturbation and mechanical turbation, such as avalanches or rockfalls). CheSS was exemplarily applied in one Swiss alpine valley where the apparent temporal variability called into question the suitability of the selected reference sites. In general we suggest the application of CheSS as a first step towards a comprehensible approach to test for the suitability of reference sites.

Tracing Crop Nitrogen Dynamics on the Field-Scale by Combining Multisensoral EO Data with an Integrated Process Model- A Validation Experiment for Cereals in Southern Germany

NASA Astrophysics Data System (ADS)

Hank, Tobias B.; Bach, Heike; Danner, Martin; Hodrius, Martina; Mauser, Wolfram

2016-08-01

Nitrogen, being the basic element for the construction of plant proteins and pigments, is one of the most important production factors for agricultural cultivation. High resolution and near real-time information on nitrogen status in the soil thus is of highest interest for economically and ecologically optimized fertilizer planning and application. Unfortunately, nitrogen storage in the soil column cannot be directly observed with Earth Observation (EO) instruments. Advanced EO supported process modelling approaches therefore must be applied that allow tracing the spatiotemporal dynamics of nitrogen transformation, translocation and transport in the soil and in the canopy. Before these models can be applied as decision support tools for smart farming, they must be carefully parameterized and validated. This study applies an advanced land surface process model (PROMET) to selected winter cereal fields in Southern Germany and correlates the model outputs to destructively sampled nitrogen data from the growing season of 2015 (17 sampling dates, 8 sample locations). The spatial parametrization of the process model thereby is supported by assimilating eight satellite images (5 times Landsat 8 OLI and 3 times RapidEye). It was found that the model is capable of realistically tracing the temporal and spatial dynamics of aboveground nitrogen uptake and allocation (R2 = 0.84, RMSE 31.3 kg ha-1).

Visual Analytics for the Food-Water-Energy Nexus in the Phoenix Active Management Area

NASA Astrophysics Data System (ADS)

Maciejewski, R.; Mascaro, G.; White, D. D.; Ruddell, B. L.; Aggarwal, R.; Sarjoughian, H.

2016-12-01

The Phoenix Active Management Area (AMA) is an administrative region of 14,500 km2 identified by the Arizona Department of Water Resources with the aim of reaching and maintaining the safe yield (i.e. balance between annual amount of groundwater withdrawn and recharged) by 2025. The AMA includes the Phoenix metropolitan area, which has experienced a dramatic population growth over the last decades with a progressive conversion of agricultural land into residential land. As a result of these changes, the water and energy demand as well as the food production in the region have significantly evolved over the last 30 years. Given the arid climate, a crucial role to support this growth has been the creation of a complex water supply system based on renewable and non-renewable resources, including the energy-intensive Central Arizona Project. In this talk, we present a preliminary characterization of the evolution in time of the feedbacks between food, water, and energy in the Phoenix AMA by analyzing secondary data (available from water and energy providers, irrigation districts, and municipalities), as well as satellite imagery and primary data collected by the authors. A preliminary visual analytics framework is also discussed describing current design practices and ideas for exploring networked components and cascading impacts within the FEW Nexus. This analysis and framework represent the first steps towards the development of an integrated modeling, visualization, and decision support infrastructure for comprehensive FEW systems decision making at decision-relevant temporal and spatial scales.

Summary of hydrologic modeling for the Delaware River Basin using the Water Availability Tool for Environmental Resources (WATER)

USGS Publications Warehouse

Williamson, Tanja N.; Lant, Jeremiah G.; Claggett, Peter; Nystrom, Elizabeth A.; Milly, Paul C.D.; Nelson, Hugh L.; Hoffman, Scott A.; Colarullo, Susan J.; Fischer, Jeffrey M.

2015-11-18

The Water Availability Tool for Environmental Resources (WATER) is a decision support system for the nontidal part of the Delaware River Basin that provides a consistent and objective method of simulating streamflow under historical, forecasted, and managed conditions. In order to quantify the uncertainty associated with these simulations, however, streamflow and the associated hydroclimatic variables of potential evapotranspiration, actual evapotranspiration, and snow accumulation and snowmelt must be simulated and compared to long-term, daily observations from sites. This report details model development and optimization, statistical evaluation of simulations for 57 basins ranging from 2 to 930 km2 and 11.0 to 99.5 percent forested cover, and how this statistical evaluation of daily streamflow relates to simulating environmental changes and management decisions that are best examined at monthly time steps normalized over multiple decades. The decision support system provides a database of historical spatial and climatic data for simulating streamflow for 2001–11, in addition to land-cover and general circulation model forecasts that focus on 2030 and 2060. WATER integrates geospatial sampling of landscape characteristics, including topographic and soil properties, with a regionally calibrated hillslope-hydrology model, an impervious-surface model, and hydroclimatic models that were parameterized by using three hydrologic response units: forested, agricultural, and developed land cover. This integration enables the regional hydrologic modeling approach used in WATER without requiring site-specific optimization or those stationary conditions inferred when using a statistical model.

Systematic Review of Medical Informatics-Supported Medication Decision Making.

PubMed

Melton, Brittany L

2017-01-01

This systematic review sought to assess the applications and implications of current medical informatics-based decision support systems related to medication prescribing and use. Studies published between January 2006 and July 2016 which were indexed in PubMed and written in English were reviewed, and 39 studies were ultimately included. Most of the studies looked at computerized provider order entry or clinical decision support systems. Most studies examined decision support systems as a means of reducing errors or risk, particularly associated with medication prescribing, whereas a few studies evaluated the impact medical informatics-based decision support systems have on workflow or operations efficiency. Most studies identified benefits associated with decision support systems, but some indicate there is room for improvement.

A geostatistical approach to the change-of-support problem and variable-support data fusion in spatial analysis

NASA Astrophysics Data System (ADS)

Wang, Jun; Wang, Yang; Zeng, Hui

2016-01-01

A key issue to address in synthesizing spatial data with variable-support in spatial analysis and modeling is the change-of-support problem. We present an approach for solving the change-of-support and variable-support data fusion problems. This approach is based on geostatistical inverse modeling that explicitly accounts for differences in spatial support. The inverse model is applied here to produce both the best predictions of a target support and prediction uncertainties, based on one or more measurements, while honoring measurements. Spatial data covering large geographic areas often exhibit spatial nonstationarity and can lead to computational challenge due to the large data size. We developed a local-window geostatistical inverse modeling approach to accommodate these issues of spatial nonstationarity and alleviate computational burden. We conducted experiments using synthetic and real-world raster data. Synthetic data were generated and aggregated to multiple supports and downscaled back to the original support to analyze the accuracy of spatial predictions and the correctness of prediction uncertainties. Similar experiments were conducted for real-world raster data. Real-world data with variable-support were statistically fused to produce single-support predictions and associated uncertainties. The modeling results demonstrate that geostatistical inverse modeling can produce accurate predictions and associated prediction uncertainties. It is shown that the local-window geostatistical inverse modeling approach suggested offers a practical way to solve the well-known change-of-support problem and variable-support data fusion problem in spatial analysis and modeling.

How to guide - transit operations decision support systems (TODSS).

DOT National Transportation Integrated Search

2014-12-01

Transit Operations Decision Support Systems (TODSS) are decision support systems designed to support dispatchers in real-time bus operations management in response to incidents, special events, and other changing conditions in order to restore servic...

Prospect theory or construal level theory? Diminishing sensitivity vs. psychological distance in risky decisions.

PubMed

Trautmann, Stefan T; van de Kuilen, Gijs

2012-01-01

Attitudes toward risks are central to organizational decisions. These attitudes are commonly modeled by prospect theory. Construal level theory has been proposed as an alternative theory of risky choice, accounting for psychological distance deriving from temporal, spatial and social aspects of risk that are typical of agency situations. Unnoticed in the literature, the two theories make contradicting predictions. The current study investigates which theory provides a better description of risky decisions in the presence of temporal, spatial, and social factors. We find that the psychophysical effects modeled by prospect theory dominate the psychological distance effects of construal level theory. Copyright © 2011 Elsevier B.V. All rights reserved.

Optimization of Decision-Making for Spatial Sampling in the North China Plain, Based on Remote-Sensing a Priori Knowledge

NASA Astrophysics Data System (ADS)

Feng, J.; Bai, L.; Liu, S.; Su, X.; Hu, H.

2012-07-01

In this paper, the MODIS remote sensing data, featured with low-cost, high-timely and moderate/low spatial resolutions, in the North China Plain (NCP) as a study region were firstly used to carry out mixed-pixel spectral decomposition to extract an useful regionalized indicator parameter (RIP) (i.e., an available ratio, that is, fraction/percentage, of winter wheat planting area in each pixel as a regionalized indicator variable (RIV) of spatial sampling) from the initial selected indicators. Then, the RIV values were spatially analyzed, and the spatial structure characteristics (i.e., spatial correlation and variation) of the NCP were achieved, which were further processed to obtain the scalefitting, valid a priori knowledge or information of spatial sampling. Subsequently, founded upon an idea of rationally integrating probability-based and model-based sampling techniques and effectively utilizing the obtained a priori knowledge or information, the spatial sampling models and design schemes and their optimization and optimal selection were developed, as is a scientific basis of improving and optimizing the existing spatial sampling schemes of large-scale cropland remote sensing monitoring. Additionally, by the adaptive analysis and decision strategy the optimal local spatial prediction and gridded system of extrapolation results were able to excellently implement an adaptive report pattern of spatial sampling in accordance with report-covering units in order to satisfy the actual needs of sampling surveys.

CorRECTreatment: A Web-based Decision Support Tool for Rectal Cancer Treatment that Uses the Analytic Hierarchy Process and Decision Tree

PubMed Central

Karakülah, G.; Dicle, O.; Sökmen, S.; Çelikoğlu, C.C.

2015-01-01

Summary Background The selection of appropriate rectal cancer treatment is a complex multi-criteria decision making process, in which clinical decision support systems might be used to assist and enrich physicians’ decision making. Objective The objective of the study was to develop a web-based clinical decision support tool for physicians in the selection of potentially beneficial treatment options for patients with rectal cancer. Methods The updated decision model contained 8 and 10 criteria in the first and second steps respectively. The decision support model, developed in our previous study by combining the Analytic Hierarchy Process (AHP) method which determines the priority of criteria and decision tree that formed using these priorities, was updated and applied to 388 patients data collected retrospectively. Later, a web-based decision support tool named corRECTreatment was developed. The compatibility of the treatment recommendations by the expert opinion and the decision support tool was examined for its consistency. Two surgeons were requested to recommend a treatment and an overall survival value for the treatment among 20 different cases that we selected and turned into a scenario among the most common and rare treatment options in the patient data set. Results In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratio<0.1). Depending on the decisions of experts, the consistency value for the most frequent cases was found to be 80% for the first decision step and 100% for the second decision step. Similarly, for rare cases consistency was 50% for the first decision step and 80% for the second decision step. Conclusions The decision model and corRECTreatment, developed by applying these on real patient data, are expected to provide potential users with decision support in rectal cancer treatment processes and facilitate them in making projections about treatment options. PMID:25848413

CorRECTreatment: a web-based decision support tool for rectal cancer treatment that uses the analytic hierarchy process and decision tree.

PubMed

Suner, A; Karakülah, G; Dicle, O; Sökmen, S; Çelikoğlu, C C

2015-01-01

The selection of appropriate rectal cancer treatment is a complex multi-criteria decision making process, in which clinical decision support systems might be used to assist and enrich physicians' decision making. The objective of the study was to develop a web-based clinical decision support tool for physicians in the selection of potentially beneficial treatment options for patients with rectal cancer. The updated decision model contained 8 and 10 criteria in the first and second steps respectively. The decision support model, developed in our previous study by combining the Analytic Hierarchy Process (AHP) method which determines the priority of criteria and decision tree that formed using these priorities, was updated and applied to 388 patients data collected retrospectively. Later, a web-based decision support tool named corRECTreatment was developed. The compatibility of the treatment recommendations by the expert opinion and the decision support tool was examined for its consistency. Two surgeons were requested to recommend a treatment and an overall survival value for the treatment among 20 different cases that we selected and turned into a scenario among the most common and rare treatment options in the patient data set. In the AHP analyses of the criteria, it was found that the matrices, generated for both decision steps, were consistent (consistency ratio<0.1). Depending on the decisions of experts, the consistency value for the most frequent cases was found to be 80% for the first decision step and 100% for the second decision step. Similarly, for rare cases consistency was 50% for the first decision step and 80% for the second decision step. The decision model and corRECTreatment, developed by applying these on real patient data, are expected to provide potential users with decision support in rectal cancer treatment processes and facilitate them in making projections about treatment options.

Developing a Dynamic SPARROW Water Quality Decision Support System Using NASA Remotely-Sensed Products

NASA Astrophysics Data System (ADS)

Al-Hamdan, M. Z.; Smith, R. A.; Hoos, A.; Schwarz, G. E.; Alexander, R. B.; Crosson, W. L.; Srikishen, J.; Estes, M., Jr.; Cruise, J.; Al-Hamdan, A.; Ellenburg, W. L., II; Flores, A.; Sanford, W. E.; Zell, W.; Reitz, M.; Miller, M. P.; Journey, C. A.; Befus, K. M.; Swann, R.; Herder, T.; Sherwood, E.; Leverone, J.; Shelton, M.; Smith, E. T.; Anastasiou, C. J.; Seachrist, J.; Hughes, A.; Graves, D.

2017-12-01

The USGS Spatially Referenced Regression on Watershed Attributes (SPARROW) surface water quality modeling system has been widely used for long term, steady state water quality analysis. However, users have increasingly requested a dynamic version of SPARROW that can provide seasonal estimates of nutrients and suspended sediment to receiving waters. The goal of this NASA-funded project is to develop a dynamic decision support system to enhance the southeast SPARROW water quality model and finer-scale dynamic models for selected coastal watersheds through the use of remotely-sensed data and other NASA Land Information System (LIS) products. The spatial and temporal scale of satellite remote sensing products and LIS modeling data make these sources ideal for the purposes of development and operation of the dynamic SPARROW model. Remote sensing products including MODIS vegetation indices, SMAP surface soil moisture, and OMI atmospheric chemistry along with LIS-derived evapotranspiration (ET) and soil temperature and moisture products will be included in model development and operation. MODIS data will also be used to map annual land cover/land use in the study areas and in conjunction with Landsat and Sentinel to identify disturbed areas that might be sources of sediment and increased phosphorus loading through exposure of the bare soil. These data and others constitute the independent variables in a regression analysis whose dependent variables are the water quality constituents total nitrogen, total phosphorus, and suspended sediment. Remotely-sensed variables such as vegetation indices and ET can be proxies for nutrient uptake by vegetation; MODIS Leaf Area Index can indicate sources of phosphorus from vegetation; soil moisture and temperature are known to control rates of denitrification; and bare soil areas serve as sources of enhanced nutrient and sediment production. The enhanced SPARROW dynamic models will provide improved tools for end users to manage water quality in near real time and for the formulation of future scenarios to inform strategic planning. Time-varying SPARROW outputs will aid water managers in decision making regarding allocation of resources in protecting aquatic habitats, planning for harmful algal blooms, and restoration of degraded habitats, stream segments, or lakes.

Energy Decision Science and Informatics | Integrated Energy Solutions |

Science.gov Websites

Science Advanced decision science methods include multi-objective and multi-criteria decision support. Our decision science methods, including multi-objective and multi-criteria decision support. For example, we

Sampling design for spatially distributed hydrogeologic and environmental processes

USGS Publications Warehouse

Christakos, G.; Olea, R.A.

1992-01-01

A methodology for the design of sampling networks over space is proposed. The methodology is based on spatial random field representations of nonhomogeneous natural processes, and on optimal spatial estimation techniques. One of the most important results of random field theory for physical sciences is its rationalization of correlations in spatial variability of natural processes. This correlation is extremely important both for interpreting spatially distributed observations and for predictive performance. The extent of site sampling and the types of data to be collected will depend on the relationship of subsurface variability to predictive uncertainty. While hypothesis formulation and initial identification of spatial variability characteristics are based on scientific understanding (such as knowledge of the physics of the underlying phenomena, geological interpretations, intuition and experience), the support offered by field data is statistically modelled. This model is not limited by the geometric nature of sampling and covers a wide range in subsurface uncertainties. A factorization scheme of the sampling error variance is derived, which possesses certain atttactive properties allowing significant savings in computations. By means of this scheme, a practical sampling design procedure providing suitable indices of the sampling error variance is established. These indices can be used by way of multiobjective decision criteria to obtain the best sampling strategy. Neither the actual implementation of the in-situ sampling nor the solution of the large spatial estimation systems of equations are necessary. The required values of the accuracy parameters involved in the network design are derived using reference charts (readily available for various combinations of data configurations and spatial variability parameters) and certain simple yet accurate analytical formulas. Insight is gained by applying the proposed sampling procedure to realistic examples related to sampling problems in two dimensions. ?? 1992.

Crop Frequency Mapping for Land Use Intensity Estimation During Three Decades

NASA Astrophysics Data System (ADS)

Schmidt, Michael; Tindall, Dan

2016-08-01

Crop extent and frequency maps are an important input to inform the debate around land value and competitive land uses, food security and sustainability of agricultural practices. Such spatial datasets are likely to support decisions on natural resource management, planning and policy. The complete Landsat Time Series (LTS) archive for 23 Landsat footprints in western Queensland from 1987 to 2015 was used in a multi-temporal mapping approach. Spatial, spectral and temporal information were combined in multiple crop-modelling steps, supported by on ground training data sampled across space and time for the classes Crop and No-Crop. Temporal information within summer and winter growing seasons for each year were summarised, and combined with various vegetation indices and band ratios computed from a mid-season spectral-composite image. All available temporal information was spatially aggregated to the scale of image segments in the mid- season composite for each growing season and used to train a random forest classifier for a Crop and No- Crop classification. Validation revealed that the predictive accuracy varied by growing season and region to be within k = 0.88 to 0.97 and are thus suitable for mapping current and historic cropping activity. Crop frequency maps were produced for all regions at different time intervals. The crop frequency maps were validated separately with a historic crop information time series. Different land use intensities and conversions e.g. from agricultural to pastures are apparent and potential drivers of these conversions are discussed.

Application of GNSS-RTK derived topographical maps for rapid environmental monitoring: a case study of Jack Finnery Lake (Perth, Australia).

PubMed

Schloderer, Glen; Bingham, Matthew; Awange, Joseph L; Fleming, Kevin M

2011-09-01

In environmental monitoring, environmental impact assessments and environmental audits, topographical maps play an essential role in providing a means by which the locations of sampling sites may be selected, in assisting with the interpretation of physical features, and in indicating the impact or potential impact on an area due to changes in the system being monitored (e.g., spatially changing features such as wetlands). Global Navigation Satellite Systems (GNSS) are hereby presented as a rapid method for monitoring spatial changes to support environmental monitoring decisions and policies. To validate the GNSS-based method, a comparison is made of results from a small-scale topographic survey using radio-based real-time kinematic GNSS (GNSS-RTK) and total station survey methods at Jack Finnery Lake, Perth, Australia. The accuracies achieved by the total station in this study were 2 cm horizontally and 6 cm vertically, while the GNSS-RTK also achieved an accuracy of 2 cm horizontally, but only 28 cm vertically. While the GNSS-RTK measurements were less accurate in the height component compared to those from the total station method, it is still capable of achieving accuracies sufficient for a topographic map at a scale of 1:1,750 that could support environmental monitoring tasks such as identifying spatial changes in small water bodies or wetlands. The time taken to perform the survey using GNSS-RTK, however, was much shorter compared to the total station method, thereby making it quite suitable for monitoring spatial changes within an environmental context, e.g., dynamic mining activities that require rapid surveys and the updating of the monitored data at regular intervals.

Does physician communication style impact patient report of decision quality for breast cancer treatment?

PubMed

Martinez, Kathryn A; Resnicow, Ken; Williams, Geoffrey C; Silva, Marlene; Abrahamse, Paul; Shumway, Dean A; Wallner, Lauren P; Katz, Steven J; Hawley, Sarah T

2016-12-01

Provider communication that supports patient autonomy has been associated with numerous positive patient outcomes. However, to date, no research has examined the relationship between perceived provider communication style and patient-assessed decision quality in breast cancer. Using a population-based sample of women with localized breast cancer, we assessed patient perceptions of autonomy-supportive communication from their surgeons and medical oncologists, as well as patient-reported decision quality. We used multivariable linear regression to examine the association between autonomy-supportive communication and subjective decision quality for surgery and chemotherapy decisions, controlling for sociodemographic and clinical factors, as well as patient-reported communication preference (non-directive or directive). Among the 1690 women included in the overall sample, patient-reported decision quality scores were positively associated with higher levels of perceived autonomy-supportive communication from surgeons (β=0.30; p<0.001) and medical oncologists (β=0.26; p<0.001). Patient communication style preference moderated the association between physician communication style received and perceived decision quality. Autonomy-supportive communication by physicians was associated with higher subjective decision quality among women with localized breast cancer. These results support future efforts to design interventions that enhance autonomy-supportive communication. Autonomy-supportive communication by cancer doctors can improve patients' perceived decision quality. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Does physician communication style impact patient report of decision quality for breast cancer treatment?

PubMed Central

Resnicow, Ken; Williams, Geoffrey C.; Silva, Marlene; Abrahamse, Paul; Shumway, Dean; Wallner, Lauren; Katz, Steven; Hawley, Sarah

2016-01-01

Objective Provider communication that supports patient autonomy has been associated with numerous positive patient outcomes. However, to date, no research has examined the relationship between perceived provider communication style and patient-assessed decision quality in breast cancer. Methods Using a population-based sample of women with localized breast cancer, we assessed patient perceptions of autonomy-supportive communication from their surgeons and medical oncologists, as well as patient-reported decision quality. We used multivariable linear regression to examine the association between autonomy-supportive communication and subjective decision quality for surgery and chemotherapy decisions, controlling for sociodemographic and clinical factors, as well as patient-reported communication preference (non-directive or directive). Results Among the 1,690 women included in the overall sample, patient-reported decision quality scores were positively associated with higher levels of perceived autonomy-supportive communication from surgeons (β=0.30; p<0.001) and medical oncologists (β=0.26; p<0.001). Patient communication style preference moderated the association between physician communication style received and perceived decision quality. Conclusion Autonomy-supportive communication by physicians was associated with higher subjective decision quality among women with localized breast cancer. These results support future efforts to design interventions that enhance autonomy-supportive communication. Practice Implications Autonomy-supportive communication by cancer doctors can improve patients’ perceived decision quality. PMID:27395750

Attribution of Net Carbon Change by Disturbance Type across Forest Lands of the Continental United States

NASA Astrophysics Data System (ADS)

Hagen, S. C.; Harris, N.; Saatchi, S. S.; Domke, G. M.; Woodall, C. W.; Pearson, T.

2016-12-01

We generated spatially comprehensive maps of carbon stocks and net carbon changes from US forestlands between 2005 and 2010 and attributed the changes to natural and anthropogenic processes. The prototype system created to produce these maps is designed to assist with national GHG inventories and support decisions associated with land management. Here, we present the results and methodological framework of our analysis. In summary, combining estimates of net C losses and gains results in net carbon change of 269±49 Tg C yr-1 (sink) in the coterminous US forest land, with carbon loss from harvest acting as the predominent source process.

On the effects of scale for ecosystem services mapping

USGS Publications Warehouse

Grêt-Regamey, Adrienne; Weibel, Bettina; Bagstad, Kenneth J.; Ferrari, Marika; Geneletti, Davide; Klug, Hermann; Schirpke, Uta; Tappeiner, Ulrike

2014-01-01

Ecosystems provide life-sustaining services upon which human civilization depends, but their degradation largely continues unabated. Spatially explicit information on ecosystem services (ES) provision is required to better guide decision making, particularly for mountain systems, which are characterized by vertical gradients and isolation with high topographic complexity, making them particularly sensitive to global change. But while spatially explicit ES quantification and valuation allows the identification of areas of abundant or limited supply of and demand for ES, the accuracy and usefulness of the information varies considerably depending on the scale and methods used. Using four case studies from mountainous regions in Europe and the U.S., we quantify information gains and losses when mapping five ES - carbon sequestration, flood regulation, agricultural production, timber harvest, and scenic beauty - at coarse and fine resolution (250 m vs. 25 m in Europe and 300 m vs. 30 m in the U.S.). We analyze the effects of scale on ES estimates and their spatial pattern and show how these effects are related to different ES, terrain structure and model properties. ES estimates differ substantially between the fine and coarse resolution analyses in all case studies and across all services. This scale effect is not equally strong for all ES. We show that spatially explicit information about non-clustered, isolated ES tends to be lost at coarse resolution and against expectation, mainly in less rugged terrain, which calls for finer resolution assessments in such contexts. The effect of terrain ruggedness is also related to model properties such as dependency on land use-land cover data. We close with recommendations for mapping ES to make the resulting maps more comparable, and suggest a four-step approach to address the issue of scale when mapping ES that can deliver information to support ES-based decision making with greater accuracy and reliability.

Assessing regional environmental quality by integrated use of remote sensing, GIS, and spatial multi-criteria evaluation for prioritization of environmental restoration.

PubMed

Rahman, Md Rejaur; Shi, Z H; Chongfa, Cai

2014-11-01

This study was an attempt to analyse the regional environmental quality with the application of remote sensing, geographical information system, and spatial multiple criteria decision analysis and, to project a quantitative method applicable to identify the status of the regional environment of the study area. Using spatial multi-criteria evaluation (SMCE) approach with expert knowledge in this study, an integrated regional environmental quality index (REQI) was computed and classified into five levels of regional environment quality viz. worse, poor, moderate, good, and very good. During the process, a set of spatial criteria were selected (here, 15 criterions) together with the degree of importance of criteria in sustainability of the regional environment. Integrated remote sensing and GIS technique and models were applied to generate the necessary factors (criterions) maps for the SMCE approach. The ranking, along with expected value method, was used to standardize the factors and on the other hand, an analytical hierarchy process (AHP) was applied for calculating factor weights. The entire process was executed in the integrated land and water information system (ILWIS) software tool that supports SMCE. The analysis showed that the overall regional environmental quality of the area was at moderate level and was partly determined by elevation. Areas under worse and poor quality of environment indicated that the regional environmental status showed decline in these parts of the county. The study also revealed that the human activities, vegetation condition, soil erosion, topography, climate, and soil conditions have serious influence on the regional environment condition of the area. Considering the regional characteristics of environmental quality, priority, and practical needs for environmental restoration, the study area was further regionalized into four priority areas which may serve as base areas of decision making for the recovery, rebuilding, and protection of the environment.

On the Effects of Scale for Ecosystem Services Mapping

PubMed Central

Grêt-Regamey, Adrienne; Weibel, Bettina; Bagstad, Kenneth J.; Ferrari, Marika; Geneletti, Davide; Klug, Hermann; Schirpke, Uta; Tappeiner, Ulrike

2014-01-01

Ecosystems provide life-sustaining services upon which human civilization depends, but their degradation largely continues unabated. Spatially explicit information on ecosystem services (ES) provision is required to better guide decision making, particularly for mountain systems, which are characterized by vertical gradients and isolation with high topographic complexity, making them particularly sensitive to global change. But while spatially explicit ES quantification and valuation allows the identification of areas of abundant or limited supply of and demand for ES, the accuracy and usefulness of the information varies considerably depending on the scale and methods used. Using four case studies from mountainous regions in Europe and the U.S., we quantify information gains and losses when mapping five ES - carbon sequestration, flood regulation, agricultural production, timber harvest, and scenic beauty - at coarse and fine resolution (250 m vs. 25 m in Europe and 300 m vs. 30 m in the U.S.). We analyze the effects of scale on ES estimates and their spatial pattern and show how these effects are related to different ES, terrain structure and model properties. ES estimates differ substantially between the fine and coarse resolution analyses in all case studies and across all services. This scale effect is not equally strong for all ES. We show that spatially explicit information about non-clustered, isolated ES tends to be lost at coarse resolution and against expectation, mainly in less rugged terrain, which calls for finer resolution assessments in such contexts. The effect of terrain ruggedness is also related to model properties such as dependency on land use-land cover data. We close with recommendations for mapping ES to make the resulting maps more comparable, and suggest a four-step approach to address the issue of scale when mapping ES that can deliver information to support ES-based decision making with greater accuracy and reliability. PMID:25549256

On the effects of scale for ecosystem services mapping.

PubMed

Grêt-Regamey, Adrienne; Weibel, Bettina; Bagstad, Kenneth J; Ferrari, Marika; Geneletti, Davide; Klug, Hermann; Schirpke, Uta; Tappeiner, Ulrike

2014-01-01

Ecosystems provide life-sustaining services upon which human civilization depends, but their degradation largely continues unabated. Spatially explicit information on ecosystem services (ES) provision is required to better guide decision making, particularly for mountain systems, which are characterized by vertical gradients and isolation with high topographic complexity, making them particularly sensitive to global change. But while spatially explicit ES quantification and valuation allows the identification of areas of abundant or limited supply of and demand for ES, the accuracy and usefulness of the information varies considerably depending on the scale and methods used. Using four case studies from mountainous regions in Europe and the U.S., we quantify information gains and losses when mapping five ES - carbon sequestration, flood regulation, agricultural production, timber harvest, and scenic beauty - at coarse and fine resolution (250 m vs. 25 m in Europe and 300 m vs. 30 m in the U.S.). We analyze the effects of scale on ES estimates and their spatial pattern and show how these effects are related to different ES, terrain structure and model properties. ES estimates differ substantially between the fine and coarse resolution analyses in all case studies and across all services. This scale effect is not equally strong for all ES. We show that spatially explicit information about non-clustered, isolated ES tends to be lost at coarse resolution and against expectation, mainly in less rugged terrain, which calls for finer resolution assessments in such contexts. The effect of terrain ruggedness is also related to model properties such as dependency on land use-land cover data. We close with recommendations for mapping ES to make the resulting maps more comparable, and suggest a four-step approach to address the issue of scale when mapping ES that can deliver information to support ES-based decision making with greater accuracy and reliability.

Addressing uncertainty in modelling cumulative impacts within maritime spatial planning in the Adriatic and Ionian region.

PubMed

Gissi, Elena; Menegon, Stefano; Sarretta, Alessandro; Appiotti, Federica; Maragno, Denis; Vianello, Andrea; Depellegrin, Daniel; Venier, Chiara; Barbanti, Andrea

2017-01-01

Maritime spatial planning (MSP) is envisaged as a tool to apply an ecosystem-based approach to the marine and coastal realms, aiming at ensuring that the collective pressure of human activities is kept within acceptable limits. Cumulative impacts (CI) assessment can support science-based MSP, in order to understand the existing and potential impacts of human uses on the marine environment. A CI assessment includes several sources of uncertainty that can hinder the correct interpretation of its results if not explicitly incorporated in the decision-making process. This study proposes a three-level methodology to perform a general uncertainty analysis integrated with the CI assessment for MSP, applied to the Adriatic and Ionian Region (AIR). We describe the nature and level of uncertainty with the help of expert judgement and elicitation to include all of the possible sources of uncertainty related to the CI model with assumptions and gaps related to the case-based MSP process in the AIR. Next, we use the results to tailor the global uncertainty analysis to spatially describe the uncertainty distribution and variations of the CI scores dependent on the CI model factors. The results show the variability of the uncertainty in the AIR, with only limited portions robustly identified as the most or the least impacted areas under multiple model factors hypothesis. The results are discussed for the level and type of reliable information and insights they provide to decision-making. The most significant uncertainty factors are identified to facilitate the adaptive MSP process and to establish research priorities to fill knowledge gaps for subsequent planning cycles. The method aims to depict the potential CI effects, as well as the extent and spatial variation of the data and scientific uncertainty; therefore, this method constitutes a suitable tool to inform the potential establishment of the precautionary principle in MSP.

Spatial vulnerability units - expert-based spatial modelling of socio-economic vulnerability in the Salzach catchment, Austria

NASA Astrophysics Data System (ADS)

Kienberger, S.; Lang, S.; Zeil, P.

2009-05-01

The assessment of vulnerability has moved to centre-stage of the debate between different scientific disciplines related to climate change and disaster risk management. Composed by a combination of social, economical, physical and environmental factors the assessment implies combining different domains as well as quantitative with qualitative data and makes it therefore a challenge to identify an integrated metric for vulnerability. In this paper we define vulnerability in the context of climate change, targeting the hazard "flood". The developed methodology is being tested in the Salzach river catchment in Austria, which is largely prone to floods. The proposed methodology allows the spatial quantification of vulnerability and the identification of vulnerability units. These units build upon the geon concept which acts as a framework for the regionalization of continuous spatial information according to defined parameters of homogeneity. Using geons, we are capable of transforming singular domains of information on specific systemic components to policy-relevant, conditioned information. Considering the fact that vulnerability is not directly measurable and due to its complex dimension and social construction an expert-based approach has been chosen. Established methodologies such as Multicriteria Decision Analysis, Delphi exercises and regionalization approaches are being integrated. The method not only enables the assessment of vulnerability independent from administrative boundaries, but also applies an aggregation mode which reflects homogenous vulnerability units. This supports decision makers to reflect on complex issues such as vulnerability. Next to that, the advantage is to decompose the units to their underlying domains. Feedback from disaster management experts indicates that the approach helps to improve the design of measures aimed at strengthening preparedness and mitigation. From this point of view, we reach a step closer towards validation of the proposed method, comprising critical user-oriented aspects like adequateness, practicability and usability of the provided results in general.

Towards ethical decision support and knowledge management in neonatal intensive care.

PubMed

Yang, L; Frize, M; Eng, P; Walker, R; Catley, C

2004-01-01

Recent studies in neonatal medicine, clinical nursing, and cognitive psychology have indicated the need to augment current decision-making practice in neonatal intensive care units with computerized, intelligent decision support systems. Rapid progress in artificial intelligence and knowledge management facilitates the design of collaborative ethical decision-support tools that allow clinicians to provide better support for parents facing inherently difficult choices, such as when to withdraw aggressive treatment. The appropriateness of using computers to support ethical decision-making is critically analyzed through research and literature review. In ethical dilemmas, multiple diverse participants need to communicate and function as a team to select the best treatment plan. In order to do this, physicians require reliable estimations of prognosis, while parents need a highly useable tool to help them assimilate complex medical issues and address their own value system. Our goal is to improve and structuralize the ethical decision-making that has become an inevitable part of modern neonatal care units. The paper contributes to clinical decision support by outlining the needs and basis for ethical decision support and justifying the proposed development efforts.

Implementation of workflow engine technology to deliver basic clinical decision support functionality

PubMed Central

2011-01-01

Background Workflow engine technology represents a new class of software with the ability to graphically model step-based knowledge. We present application of this novel technology to the domain of clinical decision support. Successful implementation of decision support within an electronic health record (EHR) remains an unsolved research challenge. Previous research efforts were mostly based on healthcare-specific representation standards and execution engines and did not reach wide adoption. We focus on two challenges in decision support systems: the ability to test decision logic on retrospective data prior prospective deployment and the challenge of user-friendly representation of clinical logic. Results We present our implementation of a workflow engine technology that addresses the two above-described challenges in delivering clinical decision support. Our system is based on a cross-industry standard of XML (extensible markup language) process definition language (XPDL). The core components of the system are a workflow editor for modeling clinical scenarios and a workflow engine for execution of those scenarios. We demonstrate, with an open-source and publicly available workflow suite, that clinical decision support logic can be executed on retrospective data. The same flowchart-based representation can also function in a prospective mode where the system can be integrated with an EHR system and respond to real-time clinical events. We limit the scope of our implementation to decision support content generation (which can be EHR system vendor independent). We do not focus on supporting complex decision support content delivery mechanisms due to lack of standardization of EHR systems in this area. We present results of our evaluation of the flowchart-based graphical notation as well as architectural evaluation of our implementation using an established evaluation framework for clinical decision support architecture. Conclusions We describe an implementation of a free workflow technology software suite (available at http://code.google.com/p/healthflow) and its application in the domain of clinical decision support. Our implementation seamlessly supports clinical logic testing on retrospective data and offers a user-friendly knowledge representation paradigm. With the presented software implementation, we demonstrate that workflow engine technology can provide a decision support platform which evaluates well against an established clinical decision support architecture evaluation framework. Due to cross-industry usage of workflow engine technology, we can expect significant future functionality enhancements that will further improve the technology's capacity to serve as a clinical decision support platform. PMID:21477364