818 resultados para GIS BASED SIMULATION
Resumo:
In Oman, during the last three decades, agricultural water use and groundwater extraction has dramatically increased to meet the needs of a rapidly growing population and major changes in lifestyle. This has triggered agricultural land-use changes which have been poorly investigated. In view of this our study aimed at analysing patterns of shortterm land-use changes (2007-2009) in the five irrigated mountain oases of Ash Sharayjah, Al’Ayn, Al’Aqr, Qasha’ and Masayrat ar Ruwajah situated in the northern Oman Hajar mountains of Al Jabal Al Akhdar where competitive uses of irrigation water are particularly apparent. Comprehensive GIS-based field surveys were conducted over three years to record changes in terrace use in these five oases where farmers have traditionally adapted to rain-derived variations of irrigation water supply, e.g. by leaving agricultural terraces of annual crops uncultivated in drought years. Results show that the area occupied with field crops decreased in the dry years of 2008 and 2009 for all oases. In Ash Sharayjah, terrace areas grown with field crops declined from 4.7 ha (32.4 % of total terrace area) in 2007 to 3.1 ha (21.6 %) in 2008 and 3.0 ha (20.5 %) in 2009. Similarly, the area proportion of field crops shrunk in Al’Ayn, Qasha’ and Masayrat from 35.2, 36.3 and 49.6 % in 2007 to 19.8, 8.5 and 41.3 % in 2009, respectively. In Al’Aqr, the area of field crops slightly increased from 0.3 ha (17.0 %) in 2007 to 0.7 (39.1 %) in 2008, and decreased to 0.5 ha (28.8 %) in 2009. During the same period annual dry matter yields of the cash crop garlic in Ash Sharayjah increased from 16.3 t ha-1 in 2007 to 19.8 t ha-1 in 2008 and 18.3 t ha-1 in 2009, while the same crop yielded only 0.4, 1.6 and 1.1 t ha-1 in Masayrat. In 2009, the total estimated agricultural area of the new town of Sayh Qatanah above the five oases was around 13.5 ha. Our results suggest that scarcity of irrigation water as a result of low precipitation and increased irrigation and home water consumption in the new urban settlements above the five oases have led to major shifts in the land-use pattern and increasingly threaten the centuries-long tradition and drought-resilience of agriculture in the oases of the studied watershed.
Resumo:
El presente proyecto de investigación tiene como objetivo general evaluar la efectividad de los esfuerzos de una unidad de negocio particular de la compañía Novartis de Colombia S.A. en el área de la percepción de marca mediante un sistema de simulación que implementa una metodología para la medición de esta última. Se tiene en cuenta que contar con datos exactos acerca de cómo los clientes finales perciben una marca es un tarea dispendiosa y que aún no tiene una fórmula matemática, por lo tanto, es muy subjetivo el proceso de entender a los consumidores por parte de los directivos de la empresa. El proceso planea que por medio del procedimiento planteado que se basa en una simulación por computador y más concretamente con una modelación basada en agentes se permita acercar a las partes involucradas en el proceso de compra, es decir, la empresa involucrada, vendedores, clientes y finalmente clientes potenciales.
Resumo:
Cuando las empresas evalúan los resultados de su planeación estratégica y de mercadeo se enfrentan en numerosas ocasiones al escepticismo sobre cómo dicha planeación favoreció o afectó la percepción hacia la empresa y sus productos. Este proyecto propone por medio del uso de una herramienta de simulación computacional reducir el factor de incertidumbre de LG Electronics en el valor percibido de marca por la población de Bogotá D.C. en cada una de sus líneas de producto; el grado de inversión en mercadeo, publicidad, distribución y servicio. Para ello los consumidores son modelados como agentes inteligentes con poder de recomendación, quienes se basan principalmente en la experiencia generada por el producto y en el grado de influencia de las estrategias de mercadeo que afectan su decisión de compra, de preferencia y de permanencia. Adicionalmente se mide la retribución en utilidades y en recordación de marca de las inversiones en mercadeo que la compañía realiza.
Resumo:
Al hacer la evaluación de los resultados asociados con procesos de planeación estratégica y mercadeo en las empresas, la dirección enfrenta un cierto nivel de incertidumbre al no saber si estos planes afectaron positiva o negativamente la posición de la empresa en su entorno. El presente trabajo hace uso de una herramienta de simulación basada en agentes inteligentes para reducir el mencionado factor de incertidumbre, en este caso, para la empresa Corgranos S.A. Se espera modelar el comportamiento de los grupos poblacionales directa e indirectamente involucrados con la empresa para así afinar los esfuerzos que se efectúan sobre cada uno de ellos, siendo la diferencia entre las suposiciones iniciales y los resultados de la simulación el verdadero aporte del trabajo.
Resumo:
El presente proyecto de investigación tiene como objetivo general evaluar la efectividad de los esfuerzos en la percepción de una marca a través de la compañía “Distr & Co.” en Colombia, teniendo como fuente principal un sistema de simulación basado en agentes inteligentes; con el que se busca mejorar la metodología para medir el desempeño de una marca dada. El proceso plantea que por medio de la modelación basada en agentes se pueda dar acercamiento a las partes involucradas en los procesos de compra, es decir, la empresa, vendedores, clientes y finalmente clientes potenciales.
Estado situacional de los modelos basados en agentes y su impacto en la investigación organizacional
Resumo:
En un mundo hiperconectado, dinámico y cargado de incertidumbre como el actual, los métodos y modelos analíticos convencionales están mostrando sus limitaciones. Las organizaciones requieren, por tanto, herramientas útiles que empleen tecnología de información y modelos de simulación computacional como mecanismos para la toma de decisiones y la resolución de problemas. Una de las más recientes, potentes y prometedoras es el modelamiento y la simulación basados en agentes (MSBA). Muchas organizaciones, incluidas empresas consultoras, emplean esta técnica para comprender fenómenos, hacer evaluación de estrategias y resolver problemas de diversa índole. Pese a ello, no existe (hasta donde conocemos) un estado situacional acerca del MSBA y su aplicación a la investigación organizacional. Cabe anotar, además, que por su novedad no es un tema suficientemente difundido y trabajado en Latinoamérica. En consecuencia, este proyecto pretende elaborar un estado situacional sobre el MSBA y su impacto sobre la investigación organizacional.
Resumo:
El presente trabajo de investigación fue realizado con el propósito de modelar el proceso de percepción de marca a partir del análisis de los componentes provenientes de la marca “Bodytech”, esto con el fin de simular el proceso de percepción de marca y evaluar la efectividad de la misma. El proceso que se modela es el de percepción – razonamiento – acción y se hace con el fin de evaluar los gastos en cada uno de los “componentes” que antes mencionaron Para realizar el análisis se hizo uso de un sistema de simulación basada en agentes, el cual recibe valores de diferentes variables analizadas por medio de tres herramientas: (1) un diagrama de grupos poblacionales, (2) un diagrama de desagregación de los núcleos temáticos de la marca y (3) las conclusiones obtenidas de una entrevista que se realizó a los responsables de gestionar la marca. Dicho proceso se lleva a cabo con el fin de poder determinar los valores relacionados al gasto en cada uno de los núcleos temáticos que llevan al sistema a evaluar la percepción de marca y la efectividad de estos gastos. Posteriormente, basados en los resultados del sistema de simulación, se obtiene un escenario que puede ser entendido y parcialmente predicho que le permitirán a Bodytech tener una herramienta de valoración de percepción de su marca.
Resumo:
The common GIS-based approach to regional analyses of soil organic carbon (SOC) stocks and changes is to define geographic layers for which unique sets of driving variables are derived, which include land use, climate, and soils. These GIS layers, with their associated attribute data, can then be fed into a range of empirical and dynamic models. Common methodologies for collating and formatting regional data sets on land use, climate, and soils were adopted for the project Assessment of Soil Organic Carbon Stocks and Changes at National Scale (GEFSOC). This permitted the development of a uniform protocol for handling the various input for the dynamic GEFSOC Modelling System. Consistent soil data sets for Amazon-Brazil, the Indo-Gangetic Plains (IGP) of India, Jordan and Kenya, the case study areas considered in the GEFSOC project, were prepared using methodologies developed for the World Soils and Terrain Database (SOTER). The approach involved three main stages: (1) compiling new soil geographic and attribute data in SOTER format; (2) using expert estimates and common sense to fill selected gaps in the measured or primary data; (3) using a scheme of taxonomy-based pedotransfer rules and expert-rules to derive soil parameter estimates for similar soil units with missing soil analytical data. The most appropriate approach varied from country to country, depending largely on the overall accessibility and quality of the primary soil data available in the case study areas. The secondary SOTER data sets discussed here are appropriate for a wide range of environmental applications at national scale. These include agro-ecological zoning, land evaluation, modelling of soil C stocks and changes, and studies of soil vulnerability to pollution. Estimates of national-scale stocks of SOC, calculated using SOTER methods, are presented as a first example of database application. Independent estimates of SOC stocks are needed to evaluate the outcome of the GEFSOC Modelling System for current conditions of land use and climate. (C) 2007 Elsevier B.V. All rights reserved.
Resumo:
The aim of this three year project funded by the Countryside Council for Wales (CCW) is to develop techniques firstly, to refine and update existing targets for habitat restoration and re-creation at the landscape scale and secondly, to develop a GIS-based model for the implementation of those targets at the local scale. Landscape Character Assessment (LCA) is being used to map Landscape Types across the whole of Wales as the first stage towards setting strategic habitat targets. The GIS habitat model uses data from the digital Phase I Habitat Survey for Wales to determine the suitability of individual sites for restoration to specific habitat types, including broadleaf woodland. The long-term aim is to develop a system that strengthens the character of Welsh landscapes and provides real biodiversity benefits based upon realistic targets given limited resources for habitat restoration and re-creation.
Predictive vegetation mapping in the Mediterranean context: Considerations and methodological issues
Resumo:
The need to map vegetation communities over large areas for nature conservation and to predict the impact of environmental change on vegetation distributions, has stimulated the development of techniques for predictive vegetation mapping. Predictive vegetation studies start with the development of a model relating vegetation units and mapped physical data, followed by the application of that model to a geographic database and over a wide range of spatial scales. This field is particularly important for identifying sites for rare and endangered species and locations of high biodiversity such as many areas of the Mediterranean Basin. The potential of the approach is illustrated with a mapping exercise in the alti-meditterranean zone of Lefka Ori in Crete. The study established the nature of the relationship between vegetation communities and physical data including altitude, slope and geomorphology. In this way the knowledge of community distribution was improved enabling a GIS-based model capable of predicting community distribution to be constructed. The paper describes the development of the spatial model and the methodological problems of predictive mapping for monitoring Mediterranean ecosystems. The paper concludes with a discussion of the role of predictive vegetation mapping and other spatial techniques, such as fuzzy mapping and geostatistics, for improving our understanding of the dynamics of Mediterranean ecosystems and for practical management in a region that is under increasing pressure from human impact.
Resumo:
The field site network (FSN) plays a central role in conducting joint research within all Assessing Large-scale Risks for biodiversity with tested Methods (ALARM) modules and provides a mechanism for integrating research on different topics in ALARM on the same site for measuring multiple impacts on biodiversity. The network covers most European climates and biogeographic regions, from Mediterranean through central European and boreal to subarctic. The project links databases with the European-wide field site network FSN, including geographic information system (GIS)-based information to characterise the test location for ALARM researchers for joint on-site research. Maps are provided in a standardised way and merged with other site-specific information. The application of GIS for these field sites and the information management promotes the use of the FSN for research and to disseminate the results. We conclude that ALARM FSN sites together with other research sites in Europe jointly could be used as a future backbone for research proposals
Resumo:
This paper discusses how the use of computer-based modelling tools has aided the design of a telemetry unit for use with oil well logging. With the aid of modern computer-based simulation techniques, the new design is capable of operating at data rates of 2.5 times faster than previous designs.
Resumo:
As wind generation increases, system impact studies rely on predictions of future generation and effective representation of wind variability. A well-established approach to investigate the impact of wind variability is to simulate generation using observations from 10 m meteorological mast-data. However, there are problems with relying purely on historical wind-speed records or generation histories: mast-data is often incomplete, not sited at a relevant wind generation sites, and recorded at the wrong altitude above ground (usually 10 m), each of which may distort the generation profile. A possible complimentary approach is to use reanalysis data, where data assimilation techniques are combined with state-of-the-art weather forecast models to produce complete gridded wind time-series over an area. Previous investigations of reanalysis datasets have placed an emphasis on comparing reanalysis to meteorological site records whereas this paper compares wind generation simulated using reanalysis data directly against historic wind generation records. Importantly, this comparison is conducted using raw reanalysis data (typical resolution ∼50 km), without relying on a computationally expensive “dynamical downscaling” for a particular target region. Although the raw reanalysis data cannot, by nature of its construction, represent the site-specific effects of sub-gridscale topography, it is nevertheless shown to be comparable to or better than the mast-based simulation in the region considered and it is therefore argued that raw reanalysis data may offer a number of significant advantages as a data source.
Resumo:
Many of the next generation of global climate models will include aerosol schemes which explicitly simulate the microphysical processes that determine the particle size distribution. These models enable aerosol optical properties and cloud condensation nuclei (CCN) concentrations to be determined by fundamental aerosol processes, which should lead to a more physically based simulation of aerosol direct and indirect radiative forcings. This study examines the global variation in particle size distribution simulated by 12 global aerosol microphysics models to quantify model diversity and to identify any common biases against observations. Evaluation against size distribution measurements from a new European network of aerosol supersites shows that the mean model agrees quite well with the observations at many sites on the annual mean, but there are some seasonal biases common to many sites. In particular, at many of these European sites, the accumulation mode number concentration is biased low during winter and Aitken mode concentrations tend to be overestimated in winter and underestimated in summer. At high northern latitudes, the models strongly underpredict Aitken and accumulation particle concentrations compared to the measurements, consistent with previous studies that have highlighted the poor performance of global aerosol models in the Arctic. In the marine boundary layer, the models capture the observed meridional variation in the size distribution, which is dominated by the Aitken mode at high latitudes, with an increasing concentration of accumulation particles with decreasing latitude. Considering vertical profiles, the models reproduce the observed peak in total particle concentrations in the upper troposphere due to new particle formation, although modelled peak concentrations tend to be biased high over Europe. Overall, the multi-model-mean data set simulates the global variation of the particle size distribution with a good degree of skill, suggesting that most of the individual global aerosol microphysics models are performing well, although the large model diversity indicates that some models are in poor agreement with the observations. Further work is required to better constrain size-resolved primary and secondary particle number sources, and an improved understanding of nucleation and growth (e.g. the role of nitrate and secondary organics) will improve the fidelity of simulated particle size distributions.
Resumo:
There is little consensus on how agriculture will meet future food demands sustainably. Soils and their biota play a crucial role by mediating ecosystem services that support agricultural productivity. However, a multitude of site-specific environmental factors and management practices interact to affect the ability of soil biota to perform vital functions, confounding the interpretation of results from experimental approaches. Insights can be gained through models, which integrate the physiological, biological and ecological mechanisms underpinning soil functions. We present a powerful modelling approach for predicting how agricultural management practices (pesticide applications and tillage) affect soil functioning through earthworm populations. By combining energy budgets and individual-based simulation models, and integrating key behavioural and ecological drivers, we accurately predict population responses to pesticide applications in different climatic conditions. We use the model to analyse the ecological consequences of different weed management practices. Our results demonstrate that an important link between agricultural management (herbicide applications and zero, reduced and conventional tillage) and earthworms is the maintenance of soil organic matter (SOM). We show how zero and reduced tillage practices can increase crop yields while preserving natural ecosystem functions. This demonstrates how management practices which aim to sustain agricultural productivity should account for their effects on earthworm populations, as their proliferation stimulates agricultural productivity. Synthesis and applications. Our results indicate that conventional tillage practices have longer term effects on soil biota than pesticide control, if the pesticide has a short dissipation time. The risk of earthworm populations becoming exposed to toxic pesticides will be reduced under dry soil conditions. Similarly, an increase in soil organic matter could increase the recovery rate of earthworm populations. However, effects are not necessarily additive and the impact of different management practices on earthworms depends on their timing and the prevailing environmental conditions. Our model can be used to determine which combinations of crop management practices and climatic conditions pose least overall risk to earthworm populations. Linking our model mechanistically to crop yield models would aid the optimization of crop management systems by exploring the trade-off between different ecosystem services.