990 resultados para socio-spatial assimilation


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Vietnam has developed rapidly over the past 15 years. However, progress was not uniformly distributed across the country. Availability, adequate visualization and analysis of spatially explicit data on socio-economic and environmental aspects can support both research and policy towards sustainable development. Applying appropriate mapping techniques allows gleaning important information from tabular socio-economic data. Spatial analysis of socio-economic phenomena can yield insights into locally-specifi c patterns and processes that cannot be generated by non-spatial applications. This paper presents techniques and applications that develop and analyze spatially highly disaggregated socioeconomic datasets. A number of examples show how such information can support informed decisionmaking and research in Vietnam.

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The mid-Holocene (6 kyr BP; thousand years before present) is a key period to study the consistency between model results and proxy-based reconstruction data as it corresponds to a standard test for models and a reasonable number of proxy-based records is available. Taking advantage of this relatively large amount of information, we have compared a compilation of 50 air and sea surface temperature reconstructions with the results of three simulations performed with general circulation models and one carried out with LOVECLIM, a model of intermediate complexity. The conclusions derived from this analysis confirm that models and data agree on the large-scale spatial pattern but the models underestimate the magnitude of some observed changes and that large discrepancies are observed at the local scale. To further investigate the origin of those inconsistencies, we have constrained LOVECLIM to follow the signal recorded by the proxies selected in the compilation using a data-assimilation method based on a particle filter. In one simulation, all the 50 proxy-based records are used while in the other two only the continental or oceanic proxy-based records constrain the model results. As expected, data assimilation leads to improving the consistency between model results and the reconstructions. In particular, this is achieved in a robust way in all the experiments through a strengthening of the westerlies at midlatitude that warms up northern Europe. Furthermore, the comparison of the LOVECLIM simulations with and without data assimilation has also objectively identified 16 proxy-based paleoclimate records whose reconstructed signal is either incompatible with the signal recorded by some other proxy-based records or with model physics.

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The Socio-Economic Atlas of Kenya is the first of its kind to offer high-resolution spatial depictions and analyses of data collected in the 2009 Kenya Population and Housing Census . The combination of geographic and socio-eco - nomic data enables policymakers at all levels, development experts, and other interested readers to gain a spatial understanding of dynamics affecting Kenya. Where is the informal economic sector most prominent? Which areas have adequate water and sanitation? Where is population growth being slowed effectively? How do education levels vary throughout the country? And where are poverty rates lowest? Answers to questions such as these, grouped into seven broad themes, are visually illustrated on high-resolution maps. By supplying precise information at the sub-location level and summarizing it at the county level, the atlas facilitates better planning that accounts for local contexts and needs. It is a valuable decision-support tool for government institutions at different administrative levels, educational institutions, and others. Three organizations – two in Kenya and one in Switzerland – worked together to create the atlas: the Kenya National Bureau of Statistics (KNBS), the Nanyuki-based Centre for Training and Integrated Research in ASAL Development (CETRAD), and the Centre for Development and Environment (CDE) at the University of Bern. Close cooperation between KNBS, CETRAD, and CDE maximized synergies and knowledge exchange.

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This paper analyses local geographical contexts targeted by transnational large-scale land acquisitions (>200 ha per deal) in order to understand how emerging patterns of socio-ecological characteristics can be related to processes of large-scale foreign investment in land. Using a sample of 139 land deals georeferenced with high spatial accuracy, we first analyse their target contexts in terms of land cover, population density, accessibility, and indicators for agricultural potential. Three distinct patterns emerge from the analysis: densely populated and easily accessible croplands (35% of land deals); remote forestlands with lower population densities (34% of land deals); and moderately populated and moderately accessible shrub- or grasslands (26% of land deals). These patterns are consistent with processes described in the relevant case study literature, and they each involve distinct types of stakeholders and associated competition over land. We then repeat the often-cited analysis that postulates a link between land investments and target countries with abundant so-called “idle” or “marginal” lands as measured by yield gap and available suitable but uncultivated land; our methods differ from the earlier approach, however, in that we examine local context (10-km radius) rather than countries as a whole. The results show that earlier findings are disputable in terms of concepts, methods, and contents. Further, we reflect on methodologies for exploring linkages between socioecological patterns and land investment processes. Improving and enhancing large datasets of georeferenced land deals is an important next step; at the same time, careful choice of the spatial scale of analysis is crucial for ensuring compatibility between the spatial accuracy of land deal locations and the resolution of available geospatial data layers. Finally, we argue that new approaches and methods must be developed to empirically link socio-ecological patterns in target contexts to key determinants of land investment processes. This would help to improve the validity and the reach of our findings as an input for evidence-informed policy debates.

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This paper examines how the geospatial accuracy of samples and sample size influence conclusions from geospatial analyses. It does so using the example of a study investigating the global phenomenon of large-scale land acquisitions and the socio-ecological characteristics of the areas they target. First, we analysed land deal datasets of varying geospatial accuracy and varying sizes and compared the results in terms of land cover, population density, and two indicators for agricultural potential: yield gap and availability of uncultivated land that is suitable for rainfed agriculture. We found that an increase in geospatial accuracy led to a substantial and greater change in conclusions about the land cover types targeted than an increase in sample size, suggesting that using a sample of higher geospatial accuracy does more to improve results than using a larger sample. The same finding emerged for population density, yield gap, and the availability of uncultivated land suitable for rainfed agriculture. Furthermore, the statistical median proved to be more consistent than the mean when comparing the descriptive statistics for datasets of different geospatial accuracy. Second, we analysed effects of geospatial accuracy on estimations regarding the potential for advancing agricultural development in target contexts. Our results show that the target contexts of the majority of land deals in our sample whose geolocation is known with a high level of accuracy contain smaller amounts of suitable, but uncultivated land than regional- and national-scale averages suggest. Consequently, the more target contexts vary within a country, the more detailed the spatial scale of analysis has to be in order to draw meaningful conclusions about the phenomena under investigation. We therefore advise against using national-scale statistics to approximate or characterize phenomena that have a local-scale impact, particularly if key indicators vary widely within a country.

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El presente trabajo se propone identificar y caracterizar las unidades de análisis espacio-territorial (fracciones censales) de la actividad primaria intensiva, específicamente hortícola, y examinar el peso relativo de la actividad del Partido de La Plata en el contexto provincial y nacional. Se analizan las variables sobre mano de obra, superficie total, superficie cultivada a campo y bajo cubierta, régimen de tenencia de la tierra y componentes tecnológicos. Se examinan y comparan los censos hortícola de la Provincia de Buenos Aires 1998 y Nacional Agropecuario 2002 (CNA02). Los resultados son presentados en tablas, gráficos y mapas temáticos procesados en SIG ArcView.

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El presente trabajo se propone identificar y caracterizar las unidades de análisis espacio-territorial (fracciones censales) de la actividad primaria intensiva, específicamente hortícola, y examinar el peso relativo de la actividad del Partido de La Plata en el contexto provincial y nacional. Se analizan las variables sobre mano de obra, superficie total, superficie cultivada a campo y bajo cubierta, régimen de tenencia de la tierra y componentes tecnológicos. Se examinan y comparan los censos hortícola de la Provincia de Buenos Aires 1998 y Nacional Agropecuario 2002 (CNA02). Los resultados son presentados en tablas, gráficos y mapas temáticos procesados en SIG ArcView.

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El presente trabajo se propone identificar y caracterizar las unidades de análisis espacio-territorial (fracciones censales) de la actividad primaria intensiva, específicamente hortícola, y examinar el peso relativo de la actividad del Partido de La Plata en el contexto provincial y nacional. Se analizan las variables sobre mano de obra, superficie total, superficie cultivada a campo y bajo cubierta, régimen de tenencia de la tierra y componentes tecnológicos. Se examinan y comparan los censos hortícola de la Provincia de Buenos Aires 1998 y Nacional Agropecuario 2002 (CNA02). Los resultados son presentados en tablas, gráficos y mapas temáticos procesados en SIG ArcView.

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Recent applications of Foucauldian categories in geography, spatial history and the history of town planning have opened up interesting new perspectives, with respect to both the evolution of spatial knowledge and the genealogy of territorial techniques and their relation to larger socio-political projects, that would be enriched if combined with other discursive traditions. This article proposes to conceptualise English parliamentary enclosureea favourite episode for Marxist historiography, frequently read in a strictly materialist fashioneas a precedent of a new form of sociospatial governmentality, a political technology that inaugurates a strategic manipulation of territory for social change on the threshold between feudal and capitalist spatial rationalities. I analyse the sociospatial dimensions of parliamentary enclosure’s technical and legal innovations and compare them to the forms of communal self-regulation of land use customs and everyday regionalisations that preceded it. Through a systematic, replicable mechanism of reterritorialisation, enclosure acts normalised spatial regulations, blurred regional differences in the social organisation of agriculture and erased the modes of autonomous social reproduction linked to common land. Their exercise of dispossession of material resources, social capital and community representations is interpreted therefore as an inaugural logic that would pervade the emergent spatial rationality later known as planning.

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Recent applications of Foucauldian categories in geography, spatial history and the history of town planning have opened up interesting new perspectives, with respect to both the evolution of spatial knowledge and the genealogy of territorial techniques and their relation to larger socio-political projects, that would be enriched if combined with other discursive traditions. This article proposes to conceptualise English parliamentary enclosureea favourite episode for Marxist historiography, frequently read in a strictly materialist fashioneas a precedent of a new form of sociospatial governmentality, a political technology that inaugurates a strategic manipulation of territory for social change on the threshold between feudal and capitalist spatial rationalities. I analyse the sociospatial dimensions of parliamentary enclosure’s technical and legal innovations and compare them to the forms of communal self-regulation of land use customs and everyday regionalisations that preceded it. Through a systematic, replicable mechanism of reterritorialisation, enclosure acts normalised spatial regulations, blurred regional differences in the social organisation of agriculture and erased the modes of autonomous social reproduction linked to common land. Their exercise of dispossession of material resources, social capital and community representations is interpreted therefore as an inaugural logic that would pervade the emergent spatial rationality later known as planning.

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High-impact, localized intense rainfall episodes represent a major socio-economic problem for societies worldwide, and at the same time these events are notoriously difficult to simulate properly in climate models. Here, the authors investigate how horizontal resolution and model formulation influence this issue by applying the HARMONIE regional climate model (HCLIM) with three different setups; two using convection parameterization at 15 and 6.25 km horizontal resolution (the latter within the “grey-zone” scale), with lateral boundary conditions provided by ERA-Interim reanalysis and integrated over a pan-European domain, and one with explicit convection at 2 km resolution (HCLIM2) over the Alpine region driven by the 15 km model. Seven summer seasons were sampled and validated against two high-resolution observational data sets. All HCLIM versions underestimate the number of dry days and hours by 20-40%, and overestimate precipitation over the Alpine ridge. Also, only modest added value were found of “grey-zone” resolution. However, the single most important outcome is the substantial added value in HCLIM2 compared to the coarser model versions at sub-daily time scales. It better captures the local-to-regional spatial patterns of precipitation reflecting a more realistic representation of the local and meso-scale dynamics. Further, the duration and spatial frequency of precipitation events, as well as extremes, are closer to observations. These characteristics are key ingredients in heavy rainfall events and associated flash floods, and the outstanding results using HCLIM in convection-permitting setting are convincing and encourage further use of the model to study changes in such events in changing climates.

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This work introduces a new variational Bayes data assimilation method for the stochastic estimation of precipitation dynamics using radar observations for short term probabilistic forecasting (nowcasting). A previously developed spatial rainfall model based on the decomposition of the observed precipitation field using a basis function expansion captures the precipitation intensity from radar images as a set of ‘rain cells’. The prior distributions for the basis function parameters are carefully chosen to have a conjugate structure for the precipitation field model to allow a novel variational Bayes method to be applied to estimate the posterior distributions in closed form, based on solving an optimisation problem, in a spirit similar to 3D VAR analysis, but seeking approximations to the posterior distribution rather than simply the most probable state. A hierarchical Kalman filter is used to estimate the advection field based on the assimilated precipitation fields at two times. The model is applied to tracking precipitation dynamics in a realistic setting, using UK Met Office radar data from both a summer convective event and a winter frontal event. The performance of the model is assessed both traditionally and using probabilistic measures of fit based on ROC curves. The model is shown to provide very good assimilation characteristics, and promising forecast skill. Improvements to the forecasting scheme are discussed

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This thesis addresses data assimilation, which typically refers to the estimation of the state of a physical system given a model and observations, and its application to short-term precipitation forecasting. A general introduction to data assimilation is given, both from a deterministic and' stochastic point of view. Data assimilation algorithms are reviewed, in the static case (when no dynamics are involved), then in the dynamic case. A double experiment on two non-linear models, the Lorenz 63 and the Lorenz 96 models, is run and the comparative performance of the methods is discussed in terms of quality of the assimilation, robustness "in the non-linear regime and computational time. Following the general review and analysis, data assimilation is discussed in the particular context of very short-term rainfall forecasting (nowcasting) using radar images. An extended Bayesian precipitation nowcasting model is introduced. The model is stochastic in nature and relies on the spatial decomposition of the rainfall field into rain "cells". Radar observations are assimilated using a Variational Bayesian method in which the true posterior distribution of the parameters is approximated by a more tractable distribution. The motion of the cells is captured by a 20 Gaussian process. The model is tested on two precipitation events, the first dominated by convective showers, the second by precipitation fronts. Several deterministic and probabilistic validation methods are applied and the model is shown to retain reasonable prediction skill at up to 3 hours lead time. Extensions to the model are discussed.

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We study the persistence phenomenon in a socio-econo dynamics model using computer simulations at a nite temperature on hypercubic lattices in dimensions up to ve. The model includes a \social" local eld which contains the magnetization at time t. The nearest neighbour quenched interactions are drawn from a binary distribution which is a function of the bond concentration, p. The decay of the persistence probability in the model depends on both the spatial dimension and p. We nd no evidence of \blocking" in this model. We also discuss the implications of our results for possible applications in the social and economic elds. It is suggested that the absence, or otherwise, of blocking could be used as a criterion to decide on the validity of a given model in dierent scenarios.

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Humans are able to mentally adopt the spatial perspective of others and understand the world from their point of view. We propose that spatial perspective taking (SPT) could have developed from the physical alignment of perspectives. This would support the notion that others have put forward claiming that SPT is an embodied cognitive process. We investigated this issue by contrasting several accounts in terms of the assumed processes and the nature of the embodiment. In a series of four experiments we found substantial evidence that the transformations during SPT comprise large parts of the body schema, which we did not observe for object rotation. We further conclude that the embodiment of SPT is best conceptualised as the self-initiated emulation of a body movement, supporting the notion of endogenous motoric embodiment. Overall our results are much more in agreement with an ‘embodied’ transformation account than with the notion of sensorimotor interference. Finally we discuss our findings in terms of SPT as a possible evolutionary stepping stone towards more complex alignments of socio-cognitive perspectives.