925 resultados para Socio-Spatial Development
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Includes bibliography
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Incluye Bibliografía
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This study aimed to analyze the spatial distribution of dengue risk and its association with socio-environmental conditions. This was an ecological study of the counts of autochthonous dengue cases in the municipality of Campinas, São Paulo State, Brazil, in the year 2007, aggregated according to 47 coverage areas of municipal health centers. Spatial models for mapping diseases were constructed with Bayesian hierarchical models, based on Integrated Nested Laplace Approximation (INLA). The analyses were stratified according to two age groups, 0 to 14 years and above 14 years. The results indicate that the spatial distribution of dengue risk is not associated with socio-environmental conditions in the 0 to 14 year age group. In the age group older than 14 years, the relative risk of dengue increases significantly as the level of socio-environmental deprivation increases. Mapping of socio-environmental deprivation and dengue cases proved to be a useful tool for data analysis in dengue surveillance systems.
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Climatic factors directly influence growth and productivity of plants inside greenhouses, where temperature can be considered one of the major parameter in this context. Thus, the aim of this research was to develop a low cost device for thermal sensing and data acquisition, and use it in data collection and analysis of spatial variability of temperature inside a greenhouse with tropical climate. The developed equipment for thermal measurements showed a high degree of accuracy and fast responses in measurements, proving its efficiency. The data analysis interpretations were made from the elaborations of variograms and of tridimensional maps generated by a geostatistical software. The processed data analysis presented that a greenhouse without thermal control has spatial variations of air temperature, both in the sampled horizontals layers as in the three analyzed vertical columns, presenting variations of up to 3.6 ºC in certain times.
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Background: Infant mortality is an important measure of human development, related to the level of welfare of a society. In order to inform public policy, various studies have tried to identify the factors that influence, at an aggregated level, infant mortality. The objective of this paper is to analyze the regional pattern of infant mortality in Brazil, evaluating the effect of infrastructure, socio-economic, and demographic variables to understand its distribution across the country. Methods: Regressions including socio-economic and living conditions variables are conducted in a structure of panel data. More specifically, a spatial panel data model with fixed effects and a spatial error autocorrelation structure is used to help to solve spatial dependence problems. The use of a spatial modeling approach takes into account the potential presence of spillovers between neighboring spatial units. The spatial units considered are Minimum Comparable Areas, defined to provide a consistent definition across Census years. Data are drawn from the 1980, 1991 and 2000 Census of Brazil, and from data collected by the Ministry of Health (DATASUS). In order to identify the influence of health care infrastructure, variables related to the number of public and private hospitals are included. Results: The results indicate that the panel model with spatial effects provides the best fit to the data. The analysis confirms that the provision of health care infrastructure and social policy measures (e. g. improving education attainment) are linked to reduced rates of infant mortality. An original finding concerns the role of spatial effects in the analysis of IMR. Spillover effects associated with health infrastructure and water and sanitation facilities imply that there are regional benefits beyond the unit of analysis. Conclusions: A spatial modeling approach is important to produce reliable estimates in the analysis of panel IMR data. Substantively, this paper contributes to our understanding of the physical and social factors that influence IMR in the case of a developing country.
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The presented study carried out an analysis on rural landscape changes. In particular the study focuses on the understanding of driving forces acting on the rural built environment using a statistical spatial model implemented through GIS techniques. It is well known that the study of landscape changes is essential for a conscious decision making in land planning. From a bibliography review results a general lack of studies dealing with the modeling of rural built environment and hence a theoretical modelling approach for such purpose is needed. The advancement in technology and modernity in building construction and agriculture have gradually changed the rural built environment. In addition, the phenomenon of urbanization of a determined the construction of new volumes that occurred beside abandoned or derelict rural buildings. Consequently there are two types of transformation dynamics affecting mainly the rural built environment that can be observed: the conversion of rural buildings and the increasing of building numbers. It is the specific aim of the presented study to propose a methodology for the development of a spatial model that allows the identification of driving forces that acted on the behaviours of the building allocation. In fact one of the most concerning dynamic nowadays is related to an irrational expansion of buildings sprawl across landscape. The proposed methodology is composed by some conceptual steps that cover different aspects related to the development of a spatial model: the selection of a response variable that better describe the phenomenon under study, the identification of possible driving forces, the sampling methodology concerning the collection of data, the most suitable algorithm to be adopted in relation to statistical theory and method used, the calibration process and evaluation of the model. A different combination of factors in various parts of the territory generated favourable or less favourable conditions for the building allocation and the existence of buildings represents the evidence of such optimum. Conversely the absence of buildings expresses a combination of agents which is not suitable for building allocation. Presence or absence of buildings can be adopted as indicators of such driving conditions, since they represent the expression of the action of driving forces in the land suitability sorting process. The existence of correlation between site selection and hypothetical driving forces, evaluated by means of modeling techniques, provides an evidence of which driving forces are involved in the allocation dynamic and an insight on their level of influence into the process. GIS software by means of spatial analysis tools allows to associate the concept of presence and absence with point futures generating a point process. Presence or absence of buildings at some site locations represent the expression of these driving factors interaction. In case of presences, points represent locations of real existing buildings, conversely absences represent locations were buildings are not existent and so they are generated by a stochastic mechanism. Possible driving forces are selected and the existence of a causal relationship with building allocations is assessed through a spatial model. The adoption of empirical statistical models provides a mechanism for the explanatory variable analysis and for the identification of key driving variables behind the site selection process for new building allocation. The model developed by following the methodology is applied to a case study to test the validity of the methodology. In particular the study area for the testing of the methodology is represented by the New District of Imola characterized by a prevailing agricultural production vocation and were transformation dynamic intensively occurred. The development of the model involved the identification of predictive variables (related to geomorphologic, socio-economic, structural and infrastructural systems of landscape) capable of representing the driving forces responsible for landscape changes.. The calibration of the model is carried out referring to spatial data regarding the periurban and rural area of the study area within the 1975-2005 time period by means of Generalised linear model. The resulting output from the model fit is continuous grid surface where cells assume values ranged from 0 to 1 of probability of building occurrences along the rural and periurban area of the study area. Hence the response variable assesses the changes in the rural built environment occurred in such time interval and is correlated to the selected explanatory variables by means of a generalized linear model using logistic regression. Comparing the probability map obtained from the model to the actual rural building distribution in 2005, the interpretation capability of the model can be evaluated. The proposed model can be also applied to the interpretation of trends which occurred in other study areas, and also referring to different time intervals, depending on the availability of data. The use of suitable data in terms of time, information, and spatial resolution and the costs related to data acquisition, pre-processing, and survey are among the most critical aspects of model implementation. Future in-depth studies can focus on using the proposed model to predict short/medium-range future scenarios for the rural built environment distribution in the study area. In order to predict future scenarios it is necessary to assume that the driving forces do not change and that their levels of influence within the model are not far from those assessed for the time interval used for the calibration.
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China is a large country characterized by remarkable growth and distinct regional diversity. Spatial disparity has always been a hot issue since China has been struggling to follow a balanced growth path but still confronting with unprecedented pressures and challenges. To better understand the inequality level benchmarking spatial distributions of Chinese provinces and municipalities and estimate dynamic trajectory of sustainable development in China, I constructed the Composite Index of Regional Development (CIRD) with five sub pillars/dimensions involving Macroeconomic Index (MEI), Science and Innovation Index (SCI), Environmental Sustainability Index (ESI), Human Capital Index (HCI) and Public Facilities Index (PFI), endeavoring to cover various fields of regional socioeconomic development. Ranking reports on the five sub dimensions and aggregated CIRD were provided in order to better measure the developmental degrees of 31 or 30 Chinese provinces and municipalities over 13 years from 1998 to 2010 as the time interval of three “Five-year Plans”. Further empirical applications of this CIRD focused on clustering and convergence estimation, attempting to fill up the gap in quantifying the developmental levels of regional comprehensive socioeconomics and estimating the dynamic convergence trajectory of regional sustainable development in a long run. Four clusters were benchmarked geographically-oriented in the map on the basis of cluster analysis, and club-convergence was observed in the Chinese provinces and municipalities based on stochastic kernel density estimation.
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Organic farming means a holistic application of agricultural land-use, hence, this study aimed to assess ecological and socio-economic aspects that show benefits of the strategy and achievements of organic farming in comparison to conventional farming in Darjeeling District, State of West Bengal, India and Kanagawa Prefecture/Kanto in Central Japan. The objective of this study has been empirically analysed on aspects of crop diversity, yield, income and sales prices in the two study regions, where 50 households each, i.e. in total 100 households were interviewed at farm-level. Therefore, the small sample size does not necessarily reflect the broad-scale of the use and benefit of organic farming in both regions. The problems faced in mountainous regions in terms of agriculture and livelihoods for small-scale farmers, which are most affected and dependant on their immediate environment, such as low yields, income and illegal felling leading to soil erosion and landslides, are analyzed. Furthermore, factors such as climate, soils, vegetation and relief equally play an important role for these farmers, in terms of land-use. To supplement and improve the income of farmers, local NGOs have introduced organic farming and high value organic cash crops such as ginger, tea, orange and cardamom and small income generating means (floriculture, apiary etc.). For non-certified and certified organic products the volume is given for India, while for Japan only certified organic production figures are given, as there are several definitions for organic in Japan. Hence, prior to the implementation of organic laws and standards, even reduced chemical input was sold as non-certified organic. Furthermore, the distribution and certification system of both countries are explained in detail, including interviews with distribution companies and cooperatives. Supportive observations from Kanagawa Prefecture and the Kanto region are helpful and practical suggestions for organic farmers in Darjeeling District. Most of these are simple and applicable soil management measures, natural insect repelling applications and describe the direct marketing system practiced in Japan. The former two include compost, intercropping, Effective Microorganisms (EM), clover, rice husk charcoal and wood vinegar. More supportive observations have been made at organic and biodynamic tea estates in Darjeeling District, which use citronella, neem, marigold, leguminous and soil binding plants for soil management and natural insect control. Due to the close ties between farmers and consumers in Japan, certification is often neither necessary nor wanted by the producers. They have built a confidence relationship with their customers; thus, such measures are simply not required. Another option is group certification, instead of the expensive individual certification. The former aims at lower costs for farmers who have formed a cooperative or a farmers' group. Consumer awareness for organic goods is another crucial aspect to help improve the situation of organic farmers. Awareness is slightly more advanced in Kanto than in Darjeeling District, as it is improved due to the close (sales) ties between farmers and consumers in Kanto. Interviews conducted with several such cooperatives and companies underline the positive system of TEIKEI. The introduction of organic farming in the study regions has shown positive effects for those involved, even though it still in its beginning stages in Darjeeling District. This study was only partly able to assess the benefits of organic agriculture at its present level for Darjeeling District, while more positively for the organic farmers of Kanto. The organic farming practice needs further improvement, encouragement and monitoring for the Darjeeling District farmers by locals, consumers, NGOs and politicians. The supportive observations from Kanagawa Prefecture and the Kanto region are a small step in this direction, showing how, simple soil improvements and thus, yield and income increases, as well as direct sales options can enhance the livelihood of organic farmers without destroying their environment and natural resources.
Immediate Search in the IDE as an Example of Socio-Technical Congruence in Search-Driven Development
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Search-driven development is mainly concerned with code reuse but also with code navigation and debugging. In this essay we look at search-driven navigation in the IDE. We consider Smalltalk-80 as an example of a programming system with search-driven navigation capabilities and explore its human factors. We present how immediate search results lead to a user experience of code browsing rather than one of waiting for and clicking through search results. We explore the socio-technical congruence of immediate search, ie unification of tasks and breakpoints with method calls, which leads to simpler and more extensible development tools. Eventually we conclude with remarks on the socio-technical congruence of search-driven development.
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Access and accessibility are important determinants of people’s ability to utilise natural resources, and have a strong impact on household welfare. Physical accessibility of natural resources, on the other hand, has generally been regarded as one of the most important drivers of land-use and land-cover changes. Based on two case studies, this article discusses evidence of the impact of access to services and access to natural resources on household poverty and on the environment. We show that socio-cultural distances are a key limiting factor for gaining access to services, and thereby for improved household welfare. We also discuss the impact of socio-cultural distances on access to natural resources, and show that large-scale commercial exploitation of natural resources tends to occur beyond the spatial reach of socio-culturally and economically marginalised population segments. We conclude that it is essential to pay more attention to improving the structural environment that presently leaves social minority groups marginalised. Innovative approaches that use natural resource management to induce poverty reduction – for example, through compensation of local farmers for environmental services – appear to be promising avenues that can lead to integration of the objectives of poverty reduction and sustainable environmental stewardship.