Set Of Spatial Units Research Articles

Population Change and Residential Segregation in Italian Small Areas, 2011–2021: An Analysis With New Spatial Units

This article explores spatial patterns of demographic change and residential segregation in Italy over the past decade, a topic which has not been studied in detail in the literature. Population ageing and migration are unfolding rapidly in a number of European countries, generating tensions and challenges at local level. Aggregate regional or national statistics can conceal significant variations at local level, which are of considerable interest and relevance. This is particularly the case in Italy, where spatial heterogeneity and regional disparities are marked. The analysis presented in this paper uses a new source of data derived from large public archives, which permits comparisons to be made at local level with the 2011 census of population. In this way, it is possible to map out and to analyse demographic trends at a fine level of spatial definition. In order to exploit the potential of these data, the authors use a new set of spatial units which were derived by applying automatic rezoning procedures. These output areas are well suited to the study of the age structure of local populations, population change, and migration in a uniform way across the entire national territory, as the empirical results confirm.

A comparison of multiple neighborhood matrix specifications for spatio-temporal model fitting: a case study on COVID-19 data.

Establishing proper neighbor relations between a set of spatial units under analysis is essential when carrying out a spatial or spatio-temporal analysis. However, it is usual that researchers choose some of the most typical (and simple) neighborhood structures, such as the first-order contiguity matrix, without exploring other options. In this paper, we compare the performance of different neighborhood matrices in the context of modeling the weekly relative risk of COVID-19 over small areas located in or near Valencia, Spain. Specifically, we construct contiguity-based, distance-based, covariate-based (considering mobility flows and sociodemographic characteristics), and hybrid neighborhood matrices. We evaluate the goodness of fit, the overall predictive quality, the ability to detect high-risk spatio-temporal units, the capability to capture the spatio-temporal autocorrelation in the data, and the goodness of smoothing for a set of spatio-temporal models based on each of the neighborhood matrices. The results show that contiguity-based matrices, some of the distance-based matrices, and those based on sociodemographic characteristics perform better than the matrices based on k-nearest neighbors and those involving mobility flows. In addition, we test the linear combination of some of the constructed neighborhood matrices and the reweighting of these matrices after eliminating weak neighbor relations, without any model improvement.

Electoral support for the 5 Star Movement in Milan: An ecological analysis of social and spatial factors

ABSTRACT After the 2018 general election, several scholars remarked on the failure of the 5 Star Movement (5SM) to increase its vote in Milan. While the role of demographic and socioeconomic factors has been highlighted, little attention has been devoted to spatial dynamics. The authors analyze the greater city of Milan using a new set of spatial units that capture the characteristics of the local populations which voted at specific polling stations. They regress support for the 5SM in each electoral district on a range of demographic, socioeconomic and spatial variables. The results show that more disadvantaged districts just outside the municipality have a strong propensity to support the 5SM. Many of the individuals and families living in these areas were negatively affected by economic crisis and continue to experience strain. These are not places of extreme marginality but have unsatisfied needs that are largely ignored by the traditional parties.

The pollution source assessment tool for Sydney's drinking water catchments

WaterNSW funds a range of interventions to minimise pollution within the drinking water catchments of Sydney. To assist with the process of targeting this expenditure, WaterNSW has developed a spatial analysis tool, known as the Pollution Source Assessment Tool (PSAT), which uses a hybrid of multi-criteria analysis and load-based methods to highlight high pollution potential sites and critical source areas for pathogens, nutrients and suspended sediment. The design of the PSAT enables results to be summarised by any set of spatial units and with any combination of pollution sources. The most recent PSAT outputs have been used at multiple scales; to guide identification of priorities across the whole of the drinking water catchments of Sydney and also to target programmes on individual properties, sites and urban areas.

Deforestation and managerial scales in Côte d’Ivoire

ABSTRACTWe provide evidence that a factor contributing to the specific patterns of deforestation in Côte d’Ivoire is the set of spatial units of management used to structure wood extraction. Timber harvests were organized through a system of harvest perimeters, called “chantier,” for nearly a century. Chantiers were initiated as managerial instruments. However, their use as spatial tool for profit maximization led to positional anarchy. The lack of support for sustainable harvests from the legislation, the restoration system, and the tree-based policy governing the use of their content made the chantier the basis of a one-way resources extraction. Managerial scales facilitated clearing of forests. None served to regenerate forests. Using historical and official documents, satellite and cartographic data, we attempted to demonstrate how managerial scales aiming to organize logging have contributed to deforestation. We discuss the phases of fragmentation in the rainforest, the managerial scales, and the environmental context in which they were applied. We summarize the legislation that governed the managerial scales and how these scales organized space but the tree species-based policies and activities resulted in the forest’s dilapidation. The final section addresses the use of these scales in the creation of data for policy making.

Metropolitane Peripherien in Deutschland: Ein empirischer Überblick

Abstract This paper aims at tracking selected developments at the peripheries of metropolitan areas in Germany from an empirical perspective. It includes the 11 regions that were dedicated as “metropolitan” by the official German spatial development policy, based on empirical criteria and also on the desire to help establish political consensus and self-organization at the regional level. It also portrays selected cases of metropolitan regions in more detail, namely the Berlin-Brandenburg, Frankfurt/Rhein-Main and Munich regions. These cases represent some of the far most densely populated, spatially differentiated urbanized areas in Germany and thus seem to be suitable in terms of international comparison. The metropolitan peripheries comprise a highly variegated set of spatial units in the vicinity of the agglomerations, consisting of typical suburban areas (housing, industrial), small and medium-sized core cities, major infrastructure complexes etc. Different from conventional stereotypes, these spatia...

Assessing Uncertainty in Support-Adjusted Spatial Misalignment Problems

Existing data from multiple sources (e.g., surveillance systems, health registries, governmental agencies) are the foundation for analysis and inference in many studies and programs. More often than not, these data have been collected on different geographical or spatial units, and each of these may be different from the ones of interest. Numerous statistical issues are associated with combining such disparate data. Florida's efforts to move toward implementation of The Centers for Disease Control and Prevention's (CDC's) Environmental Public Health Tracking (EPHT) Program aptly illustrate these issues, which are typical of almost any study designed to measure the association between environmental hazards and health outcomes. In this article, we consider the inferential issues that arise when a potential explanatory variable is measured on one set of spatial units, but then must be predicted on a different set of spatial units. We compare the results from two different approaches to linking health and environmental data on different spatial units, focusing on the need to account for spatial scale and the support of spatial data in the analysis. We compare methods for assessing uncertainty and the potential bias that arises from using predicted variables in spatial regression models. Our focus is on relatively simple methods and concepts that can be transferred to the states' departments of health, the organizations responsible for implementing EPHT.

The geography of overweight in Quebec: a multilevel perspective.

Explore the contextual aspects of overweight in Quebec through multilevel modelling, using a purposely designed set of spatial units and a few area-based characteristics. Data came from the Canadian Community Health Survey (CCHS Cycle 2.1). Multilevel logistic regressions were performed to test for the presence of an independent contextual effect on overweight and obesity (BMI > or = 25 kg/m2), separately for men and women. Modelling considered individual attributes, including some lifestyle aspects, and contextual characteristics. A geographic grid integrating spatial elements related to overweight and obesity in the literature was developed. Also, an area-level residuals analysis was carried out to identify spatial units presenting higher or lower odds of being overweight. After accounting for individual and area-level characteristics, there remain significant geographic variations in overweight in Quebec. Although this contextual effect is small for men and women, many spatial units differ significantly from the provincial average. There are differences between the geography of overweight in men and women which suggest that socio-economic mechanisms and land use patterns underlying overweight might be different between genders. Also, there is considerable variability within rural and urban areas. A complex geography of overweight is revealed. Small-scale studies, as well as methodological and data developments, are needed to deepen our understanding of this geography.

Classification of Spatial Properties for Spatial Allocation Modeling

Given a set of spatial units, such as land parcels and grid cells, how to allocate subsets of it to activities of interest while satisfying certain criteria? Such a decision process is here called spatial allocation. Though many problems of spatial allocation share this generic construct, each may have a quite unique set of criteria and interpret even the same criteria in its own way. Such diversity makes it difficult to model spatial allocation problems in unambiguous terms that are amenable to algorithmic solution. This paper proposes a classification scheme for spatial properties that helps to address a variety of spatial properties in establishing spatial allocation criteria. The implication of the paper is that a number of spatial properties and spatial allocation criteria can be decomposed into a few kinds of primitive spatial properties and their relations.

A spatial rainfall simulator for crop production modeling in Southern Africa

This paper describes a methodology for simulating rainfall in dekads across a set of spatial units in areas where long-term meteorological records are available for a small number of sites only. The work forms part of a larger simulation model of the food system in a district of Zimbabwe, which includes a crop production component for yields of maize, small grains and groundnuts. Only a limited number of meteorological stations are available within or surrounding the district that have long time series of rainfall records. Preliminary analysis of rainfall data for these stations suggested that intra-seasonal temporal correlation was negligible, but that rainfall at any given station was correlated with rainfall at neighbouring stations. This spatial correlation structure can be modeled using a multivariate normal distribution consisting of 30 related variables, representing dekadly rainfall in each of the 30 wards. For each ward, log-transformed rainfall for each of the 36 dekads in the year was characterized by a mean and standard deviation, which were interpolated from surrounding meteorological stations. A covariance matrix derived from a distance measure was then used to represent the spatial correlation between wards. Sets of random numbers were then drawn from this distribution to simulate rainfall across the wards in any given dekad. Cross-validation of estimated rainfall parameters against observed parameters for the one meteorological station within the district suggests that the interpolation process works well. The methodology developed is useful in situations where long-term climatic records are scarce and where rainfall shows pronounced spatial correlation, but negligible temporal correlation.

Spatial growth and population dynamics of a perennial tussock grass (Achnatherum calamagrostis) in a badland area

Summary 1 Achnatherum calamagrostis (L.) Beauv. is a perennial, tussock forming grass which is conspicuously successful as a pioneer in badlands in submediterranean areas. We analysed its population dynamics using a matrix population model that is intermediate between traditional demographic models and fully spatially explicit models. 2 Tussocks are considered as a set of spatial units, each classified according to the number and state (seedling, juvenile or adults) of the tillers it contains. The growth rate (λi) determined from the model estimates the spatial spread of A. calamagrostis as a rate of increase in the number of occupied quadrats. 3 We constructed six projection matrices from data for populations on two substrate types, in 2 years with differing climatic conditions and considering the whole life cycle or eliminating sexual reproduction or vegetative multiplication. 4 All the matrices predicted growth rates greater than one. Sexual reproduction was an important process for spatial spread in A. calamagrostis, unlike many other perennial grasses. In contrast, new colonization by vegetative reproduction contributed little to spatial growth of populations, although some expansion may still be possible in the absence of sexual reproduction. 5 A. calamagrostis, like other tussock‐forming plants, exhibits a conservative tactic of slow spread. Tiller dynamics serve mainly for consolidation and maintenance of the plant in already occupied space and sexual reproduction is the main way to ensure colonization of new safe‐sites. Climatic conditions influenced growth rates which increased during non‐drought years above the near maintenance value seen in drought years.