858 resultados para GIS-based decisions


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To remain competitive, many agricultural systems are now being run along business lines. Systems methodologies are being incorporated, and here evolutionary computation is a valuable tool for identifying more profitable or sustainable solutions. However, agricultural models typically pose some of the more challenging problems for optimisation. This chapter outlines these problems, and then presents a series of three case studies demonstrating how they can be overcome in practice. Firstly, increasingly complex models of Australian livestock enterprises show that evolutionary computation is the only viable optimisation method for these large and difficult problems. On-going research is taking a notably efficient and robust variant, differential evolution, out into real-world systems. Next, models of cropping systems in Australia demonstrate the challenge of dealing with competing objectives, namely maximising farm profit whilst minimising resource degradation. Pareto methods are used to illustrate this trade-off, and these results have proved to be most useful for farm managers in this industry. Finally, land-use planning in the Netherlands demonstrates the size and spatial complexity of real-world problems. Here, GIS-based optimisation techniques are integrated with Pareto methods, producing better solutions which were acceptable to the competing organizations. These three studies all show that evolutionary computation remains the only feasible method for the optimisation of large, complex agricultural problems. An extra benefit is that the resultant population of candidate solutions illustrates trade-offs, and this leads to more informed discussions and better education of the industry decision-makers.

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Acquiring detailed knowledge of surface treatments effectiveness is required to improve performance-based decisions for allocating resources to preserve and maintain pavements on any road network. Measurement of treatment effectiveness is a complex task that requires historical records of treatments with observations of before and after performance trends. Lack of data is often an obstacle that impedes development and incorporation of surface maintenance treatments into pavement management. This paper analyzes the effect of surface treatments on asphalt paved arterial roads for several control sections of New Brunswick. The method uses a Transition Probability Matrix to capture main effects by mapping mean trends of surface improvement and pavement structure decay. It was found that surface treatments have an immediate effect reducing the rate of loss of structural capacity. Pavements with international roughness index (IRI) smaller than 1.4 m/km did not seem to benefit from surface treatments. Those with IRI higher than 1.66 m/km gained from 6 to 8 years of additional life. Reset value for surface treatments fall between 1.18 and 1.29 m/km. This paper aims to serve to practitioners seeking to capture and incorporate effectiveness of surface treatments (i.e., crack-sealing) into Pavement Management.

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Parthenium hysterophorus is a weed of global significance causing severe economic, environmental, human and animal health problems in Asia, Africa, Australia and the Pacific. In South Asia, P. hysterophorus occurs in India, Pakistan, Sri Lanka, Bangladesh and Nepal. A host-specific leaf-feeding beetle Zygogramma bicolorata from Mexico was introduced into India in 1984, as a biological control agent for P. hysterophorus. In this study, a GIS-based distribution map of P. hysterophorus and its biological control agent Z. bicolorata in South Asia based on meta-analysis is presented. The map highlights the limited published information on P. hysterophorus incidence in many of the states and territories in India, as well as in neighbouring Bangladesh, Bhutan, Nepal and Pakistan. Incidence of Z. bicolorata was recorded as three distinct clusters, covering many states in India. In Pakistan, Z. bicolorata was recorded in the Punjab region bordering India. A CLIMEX model based on the current distribution of Z. bicolorata in India suggests that the geographic range of this agent in India and Pakistan can extend to other P. hysterophorus-infested areas in the region. The CLIMEX model also suggests that all of Bangladesh and Sri Lanka, and parts of Nepal are climatically suitable for Z. bicolorata.

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Organisations are always focussed on ensuring that their business operations are performed in the most cost-effective manner, and that processes are responsive to ever-changing cost pressures. In many organisations, however, strategic cost-based decisions at the managerial level are not directly or quickly translatable to process-level operational support. A primary reason for this disconnect is the limited system-based support for cost-informed decisions at the process-operational level in real time. In this paper, we describe the different ways in which a workflow management system can support process-related decisions, guided by cost-informed considerations at the operational level, during execution. As a result, cost information is elevated from its non-functional attribute role to a first-class, fully functional process perspective. The paper defines success criteria that a WfMS should meet to provide such support, and discusses a reference implementation within the YAWL workflow environment that demonstrates how the various types of cost-informed decision rules are supported, using an illustrative example.

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The global importance of grasslands is indicated by their extent; they comprise some 26% of total land area and 80% of agriculturally productive land. The majority of grasslands are located in tropical developing countries where they are particularly important to the livelihoods of some one billion poor peoples. Grasslands clearly provide the feed base for grazing livestock and thus numerous high-quality foods, but such livestock also provide products such as fertilizer, transport, traction, fibre and leather. In addition, grasslands provide important services and roles including as water catchments, biodiversity reserves, for cultural and recreational needs, and potentially a carbon sink to alleviate greenhouse gas emissions. Inevitably, such functions may conflict with management for production of livestock products. Much of the increasing global demand for meat and milk, particularly from developing countries, will have to be supplied from grassland ecosystems, and this will provide difficult challenges. Increased production of meat and milk generally requires increased intake of metabolizable energy, and thus increased voluntary intake and/or digestibility of diets selected by grazing animals. These will require more widespread and effective application of improved management. Strategies to improve productivity include fertilizer application, grazing management, greater use of crop by-products, legumes and supplements and manipulation of stocking rate and herbage allowance. However, it is often difficult to predict the efficiency and cost-effectiveness of such strategies, particularly in tropical developing country production systems. Evaluation and on-going adjustment of grazing systems require appropriate and reliable assessment criteria, but these are often lacking. A number of emerging technologies may contribute to timely low-cost acquisition of quantitative information to better understand the soil-pasture-animal interactions and animal management in grassland systems. Development of remote imaging of vegetation, global positioning technology, improved diet markers, near IR spectroscopy and modelling provide improved tools for knowledge-based decisions on the productivity constraints of grazing animals. Individual electronic identification of animals offers opportunities for precision management on an individual animal basis for improved productivity. Improved outcomes in the form of livestock products, services and/or other outcomes from grasslands should be possible, but clearly a diversity of solutions are needed for the vast range of environments and social circumstances of global grasslands.

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"The increasing pressure for enterprises to join into agile business networks is changing the requirements on the enterprise computing systems. The supporting infrastructure is increasingly required to provide common facilities and societal infrastructure services to support the lifecycle of loosely-coupled, eContract-governed business networks. The required facilities include selection of those autonomously administered business services that the enterprises are prepared to provide and use, contract negotiations, and furthermore, monitoring of the contracted behaviour with potential for breach management. The essential change is in the requirement of a clear mapping between business-level concepts and the automation support for them. Our work has focused on developing B2B middleware to address the above challenges; however, the architecture is not feasible without management facilities for trust-aware decisions for entering business networks and interacting within them. This paper discusses how trust-based decisions are supported and positioned in the B2B middleware."

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The Burrishoole catchment is situated in County Mayo, on the northwest coast of the Republic of Ireland. Much of the catchment is covered by blanket peat that, in many areas, has become heavily eroded in recent years. This is thought to be due, primarily, to the adverse effects of forestry and agricultural activities in the area. Such activities include ploughing, drainage, the planting and harvesting of trees, and sheep farming, all of which are potentially damaging to such a sensitive landscape if not managed carefully. This article examines the sediment yield and hydrology of the Burrishoole catchment. Flow and sediment concentrations were measured at 8-hourly intervals from 5 February 2001 to 8 November 2001 with an automatic sampler and separate flow gauge, and hourly averages were recorded between 4 July 2002 and 6 September 2002 using an automatic river monitoring system [ARMS]. The authors describe the GIS-based model of soil erosion and transport that was applied to the Burrishoole catchment during this study. The results of these analyses were compared, in a qualitative manner, with the aerial photography available for the Burrishoole catchment to see whether areas that were predicted to contribute large proportions of eroded material to the drainage network corresponded with areas where peat erosion could be identified through photo-interpretation.

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Digital maps of the coral reef ecosystem (<~30m deep) of Majuro Atoll, Republic of the Marshall Islands, were created through visual interpretation of remote sensing imagery. Digital Globe’s Quickbird II satellite images were acquired between 2004 and 2006 and georeferenced to within 1.6 m of their true positions. Reef ecosystem features were digitized directly into a GIS at a display scale of 1:4000 using a minimum feature size of 1000 square meters. Benthic features were categorized according to a classification scheme with attributes including zone (location, such as lagoon or forereef, etc.), structure (bottom type, such as sand or patch reef, etc.) and percent hard bottom. Ground validation of habitat features was conducted at 311 sites in 2009. Resulting maps consisted of 1829 features covering 366 square kilometers. Results demonstrate that reef zones occurred in a typical progression of narrow bands from offshore, though forereef, reef flat, shoreline, land, backreef, and lagoon habitats. Lagoon was the largest zone mapped and covered nearly 80% of the atoll, although much of it was too deep to have structures identified from the satellite imagery. Dominant habitat structures by area were pavement and aggregate reef, which covered 29% and 18% of the mapped structures, respectively. Based on the number of features, individual and aggregated patch reefs comprised over 40% of the features mapped. Products include GIS based maps, field videos and pictures, satellite imagery, PDF atlas, and this summary report. Maps and associated data can be used to support science and management activities on Majuro reef ecosystems including inventory, monitoring, conservation, and sustainable development applications.

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Land-based pollution is commonly identified as a major contributor to the observed deterioration of shallow-water coral reef ecosystem health. Human activity on the coastal landscape often induces nutrient enrichment, hypoxia, harmful algal blooms, toxic contamination and other stressors that have degraded the quality of coastal waters. Coral reef ecosystems throughout Puerto Rico, including Jobos Bay, are under threat from coastal land uses such as urban development, industry and agriculture. The objectives of this report were two-fold: 1. To identify potentially harmful land use activities to the benthic habitats of Jobos Bay, and 2. To describe a monitoring plan for Jobos Bay designed to assess the impacts of conservation practices implemented on the watershed. This characterization is a component of the partnership between the U.S. Department of Agriculture (USDA) and the National Oceanic and Atmospheric Administration (NOAA) established by the Conservation Effects Assessment Project (CEAP) in Jobos Bay. CEAP is a multi-agency effort to quantify the environmental benefits of conservation practices used by private landowners participating in USDA programs. The Jobos Bay watershed, located in southeastern Puerto Rico, was selected as the first tropical CEAP Special Emphasis Watershed (SEW). Both USDA and NOAA use their respective expertise in terrestrial and marine environments to model and monitor Jobos Bay resources. This report documents NOAA activities conducted in the first year of the three-year CEAP effort in Jobos Bay. Chapter 1 provides a brief overview of the project and background information on Jobos Bay and its watershed. Chapter 2 implements NOAA’s Summit to Sea approach to summarize the existing resource conditions on the watershed and in the estuary. Summit to Sea uses a GIS-based procedure that links patterns of land use in coastal watersheds to sediment and pollutant loading predictions at the interface between terrestrial and marine environments. The outcome of Summit to Sea analysis is an inventory of coastal land use and predicted pollution threats, consisting of spatial data and descriptive statistics, which allows for better management of coral reef ecosystems. Chapters 3 and 4 describe the monitoring plan to assess the ecological response to conservation practices established by USDA on the watershed. Jobos Bay is the second largest estuary in Puerto Rico, but has more than three times the shoreline of any other estuarine area on the island. It is a natural harbor protected from offshore wind and waves by a series of mangrove islands and the Punta Pozuelo peninsula. The Jobos Bay marine ecosystem includes 48 km² of mangrove, seagrass, coral reef and other habitat types that span both intertidal and subtidal areas. Mapping of Jobos Bay revealed 10 different benthic habitats of varying prevalence, and a large area of unknown bottom type covering 38% of the entire bay. Of the known benthic habitats, submerged aquatic vegetation, primarily seagrass, is the most common bottom type, covering slightly less than 30% of the bay. Mangroves are the dominant shoreline feature, while coral reefs comprise only 4% of the total benthic habitat. However, coral reefs are some of the most productive habitats found in Jobos Bay, and provide important habitat and nursery grounds for fish and invertebrates of commercial and recreational value.

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在已有区域试验研究和观测数据、水土流失因子研究成果基础上,基于坡面土壤侵蚀机理对区域水土流失过程进行分析,基于结合GIS空间分析功能,进行了区域尺度上水土流失模型设计的初步尝试,并提出了模型所需参数的提取方法及精度要求,本模型在延河流域试运算结果反映了接近现实的土壤侵蚀时空分布趋势和分异。

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As a typical geological and environmental hazard, landslide has been causing more and more property and life losses. However, to predict its accurate occurring time is very difficult or even impossible due to landslide's complex nature. It has been realized that it is not a good solution to spend a lot of money to treat with and prevent landslide. The research trend is to study landslide's spatial distribution and predict its potential hazard zone under certain region and certain conditions. GIS(Geographical Information System) is a power tools for data management, spatial analysis based on reasonable spatial models and visualization. It is new and potential study field to do landslide hazard analysis and prediction based on GIS. This paper systematically studies the theory and methods for GIS based landslide hazard analysis. On the basis of project "Mountainous hazard study-landslide and debris flows" supported by Chinese Academy of Sciences and the former study foundation, this paper carries out model research, application, verification and model result analysis. The occurrence of landslide has its triggering factors. Landslide has its special landform and topographical feature which can be identify from field work and remote sensing image (aerial photo). Historical record of landslide is the key to predict the future behaviors of landslide. These are bases for landslide spatial data base construction. Based on the plenty of literatures reviews, the concept framework of model integration and unit combinations is formed. Two types of model, CF multiple regression model and landslide stability and hydrological distribution coupled model are bought forward. CF multiple regression model comes form statistics and possibility theory based on data. Data itself contains the uncertainty and random nature of landslide hazard, so it can be seen as a good method to study and understand landslide's complex feature and mechanics. CF multiple regression model integrates CF (landslide Certainty Factor) and multiple regression prediction model. CF can easily treat with the problems of data quantifying and combination of heteroecious data types. The combination of CF can assist to determine key landslide triggering factors which are then inputted into multiple regression model. CF regression model can provide better prediction results than traditional model. The process of landslide can be described and modeled by suitable physical and mechanical model. Landslide stability and hydrological distribution coupled model is such a physical deterministic model that can be easily used for landslide hazard analysis and prediction. It couples the general limit equilibrium method and hydrological distribution model based on DEM, and can be used as a effective approach to predict the occurrence of landslide under different precipitation conditions as well as landslide mechanics research. It can not only explain pre-existed landslides, but also predict the potential hazard region with environmental conditions changes. Finally, this paper carries out landslide hazard analysis and prediction in Yunnan Xiaojiang watershed, including landslide hazard sensitivity analysis and regression prediction model based on selected key factors, determining the relationship between landslide occurrence possibility and triggering factors. The result of landslide hazard analysis and prediction by coupled model is discussed in details. On the basis of model verification and validation, the modeling results are showing high accuracy and good applying potential in landslide research.

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The recognition that urban groundwater is a potentially valuable resource for potable and industrial uses due to growing pressures on perceived less polluted rural groundwater has led to a requirement to assess the groundwater contamination risk in urban areas from industrial contaminants such as chlorinated solvents. The development of a probabilistic risk based management tool that predicts groundwater quality at potential new urban boreholes is beneficial in determining the best sites for future resource development. The Borehole Optimisation System (BOS) is a custom Geographic Information System (GIs) application that has been developed with the objective of identifying the optimum locations for new abstraction boreholes. BOS can be applied to any aquifer subject to variable contamination risk. The system is described in more detail by Tait et al. [Tait, N.G., Davison, J.J., Whittaker, J.J., Lehame, S.A. Lerner, D.N., 2004a. Borehole Optimisation System (BOS) - a GIs based risk analysis tool for optimising the use of urban groundwater. Environmental Modelling and Software 19, 1111-1124]. This paper applies the BOS model to an urban Permo-Triassic Sandstone aquifer in the city centre of Nottingham, UK. The risk of pollution in potential new boreholes from the industrial chlorinated solvent tetrachloroethene (PCE) was assessed for this region. The risk model was validated against contaminant concentrations from 6 actual field boreholes within the study area. In these studies the model generally underestimated contaminant concentrations. A sensitivity analysis showed that the most responsive model parameters were recharge, effective porosity and contaminant degradation rate. Multiple simulations were undertaken across the study area in order to create surface maps indicating areas of low PCE concentrations, thus indicating the best locations to place new boreholes. Results indicate that northeastern, eastern and central regions have the lowest potential PCE concentrations in abstraction groundwater and therefore are the best sites for locating new boreholes. These locations coincide with aquifer areas that are confined by low permeability Mercia Mudstone deposits. Conversely southern and northwestern areas are unconfined and have shallower depth to groundwater. These areas have the highest potential PCE concentrations. These studies demonstrate the applicability of BOS as a tool for informing decision makers on the development of urban groundwater resources. (c) 2007 Elsevier Ltd. All rights reserved.

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Increasing emphasis is being placed on the evaluation of health-related quality of life. However, there is no consensus on the definition of this concept and as a result there are a plethora of existing measurement instruments. Head-to-head comparisons of the psychometric properties of existing instruments are necessary to facilitate evidence-based decisions about which instrument should be chosen for routine use. Therefore, an individualised instrument (the modified Patient Generated Index), a generic instrument (the Short Form 36) and a disease-specific instrument (the Quality of Life after Myocardial Infarction questionnaire) were administered to patients with ischaemic heart disease (n=117) and the evidence for the validity, reliability and sensitivity of each instrument was examined and compared. The modified Patient Generated Index compared favourably with the other instruments but none of the instruments examined provided sound evidence for sensitivity to change. Therefore, any recommendation for the use of the individualised approach in the routine collection of health-related quality of life data in clinical practice must be conditional upon the submission of further evidence to support the sensitivity of such instruments.

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This paper examines the degree to which tree-associated Coleoptera (beetles) and pollen could be used to predict the degree of ‘openness’ in woodland. The results from two modern insect and pollen analogue studies from ponds at Dunham Massey, Cheshire and Epping Forest, Greater London are presented. We explore the reliability of modern pollen rain and sub-fossil beetle assemblages to represent varying degrees of canopy cover for up to 1000m from a sampling site. Modern woodland canopy structure around the study sites has been assessed using GIS-based mapping at increasing radial distances as an independent check on the modern insect and pollen data sets. These preliminary results suggest that it is possible to use tree-associated Coleoptera to assess the degree of local vegetation openness. Additionally, it appears that insect remains may indicate the relative intensity of land use by grazing animals. Our results also suggest most insects are collected from within a 100m to 200m radius of the sampling site. The pollen results suggest that local vegetation and density of woodland in the immediate area of the sampling site can have a strong role in determining the pollen signal.

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We use a network of cores from 77 peatland sites to determine controls on peat C content and peat C accumulation over the last 2000 years (since 2 ka) across Russia's West Siberian Lowland (WSL), the world's largest wetland region. Our results show a significant influence of fossil plant composition on peat C content, with peats dominated by Sphagnum having a lower C content. Radiocarbon-derived C accumulation since 2 ka at 23 sites is highly variable from site to site, but displays a significant N–S trend of decreasing accumulation at higher latitudes. Northern WSL peatlands show relatively small C accumulation of 7 to 35 kg C m-2 since 2 ka. In contrast, peatlands south of 60°N show larger accumulation of 42 to 88 kg C m-2. Carbon accumulation since 2 ka varies significantly with modern mean annual air temperature, with maximum C accumulation found between -1 and 0°C. Rates of apparent C accumulation since 2 ka show no significant relationship to long-term Holocene averages based on total C accumulation. A GIS-based extrapolation of our site data suggests that a substantial amount (~40%) of total WSL peat C has accumulated since 2 ka, with much of this accumulation south of 60°N. The large peatlands in the southern WSL may be an important component of the Eurasian terrestrial C sink, and future warming could result in a shift northward in long-term WSL C sequestration.