Depicting urban boundaries from a mobility network of spatial interactions: A case study of Great Britain with geo-located Twitter data

Existing urban boundaries are usually defined by government agencies for administrative, economic, and political purposes. Defining urban boundaries that consider socio-economic relationships and citizen commute patterns is important for many aspects of urban and regional planning. In this paper, we describe a method to delineate urban boundaries based upon human interactions with physical space inferred from social media. Specifically, we depicted the urban boundaries of Great Britain using a mobility network of Twitter user spatial interactions, which was inferred from over 69 million geo-located tweets. We define the non-administrative anthropographic boundaries in a hierarchical fashion based on different physical movement ranges of users derived from the collective mobility patterns of Twitter users in Great Britain. The results of strongly connected urban regions in the form of communities in the network space yield geographically cohesive, non-overlapping urban areas, which provide a clear delineation of the non-administrative anthropographic urban boundaries of Great Britain. The method was applied to both national (Great Britain) and municipal scales (the London metropolis). While our results corresponded well with the administrative boundaries, many unexpected and interesting boundaries were identified. Importantly, as the depicted urban boundaries exhibited a strong instance of spatial proximity, we employed a gravity model to understand the distance decay effects in shaping the delineated urban boundaries. The model explains how geographical distances found in the mobility patterns affect the interaction intensity among different non-administrative anthropographic urban areas, which provides new insights into human spatial interactions with urban space.Comment: 32 pages, 7 figures, International Journal of Geographic Information Scienc

A min-cut approach to functional regionalization, with a case study of the Italian local labour market areas

In several economical, statistical and geographical applications, a territory must be subdivided into functional regions. Such regions are not fixed and politically delimited, but should be identified by analyzing the interactions among all its constituent localities. This is a very delicate and important task, that often turns out to be computationally difficult. In this work we propose an innovative approach to this problem based on the solution of minimum cut problems over an undirected graph called here transitions graph. The proposed procedure guarantees that the obtained regions satisfy all the statistical conditions required when considering this type of problems. Results on real-world instances show the effectiveness of the proposed approach

Deliniation of metropolitan areas in Poland: A functional approach

Delineation of urban functional areas helps policymakers and urban planners understand the connections between the core cities and areas surrounding them, and subsequently develop policies and solutions that can serve local populations. This article develops a readily applicable econometric method for delineation that considers functional aspects of cities and their surroundings. We perform delineation analysis using the data for 78 Polish core cities, grouping them by population size. Using the satellite data on lights emitted at night, population density, commuter numbers as well as the number of houses and apartments built in each commune, we apply a threshold regression model to determine the boundaries of functional urban areas. Our main results suggest that the mean radius of functional urban areas (FUAs) around the largest (most populous) cities is, on average, 21 km, while it is between 13 and 16 km for smaller cities. We then test how the econometric results compare with the perceptions of local inhabitants through a citizen science project (CSP) conducted as a robustness check

Urban dynamics in the Flemish countryside: a comparative study on morphological patterns and local economy dynamics

The article examines two aspects of urbanisation in the rural areas of Flanders, the northern part of Belgium. On the one hand, the evolution of the built environment is studied in terms of built-up density and the corresponding morphological sprawl pattern, from the beginning of the 19th century up until now. On the other hand, the economy dynamics in the rural areas are investigated. This shift in economic activities can be seen as part of a broader urbanisation process, with aspects such as tertiarisation and broadening of agriculture. The main driving factors behind these transformations are discussed based on literature study. It becomes clear that urbanisation of the countryside is the combined result of economic, physical, cultural and political evolutions. The comparative study in eight case municipalities with different spatial characteristics maps the evolution of the built environment and continuity of the economic activities. Temporal and regional differences are analysed and related to more location-specific driving factors. The sprawl pattern seems to have a historical ground, whereas the difference in density is related to the evolution path. Regarding the local economy dynamics, no clear regional differences can be found. The professions and other business services category has the highest density. The amount of tertiary activities proves the importance of tertiarisation on the countryside. Both studied evolutions tend to change the open space profoundly. Therefore, insights are crucial in order to develop location specific policies

Multilevel comparison of large urban systems

For the first time the systems of cities in seven countries or regions among the largest in the world (China, India, Brazil, Europe, the Former Soviet Union (FSU), the United States and South Africa) are made comparable through the building of spatio-temporal standardised statistical databases. We first explain the concept of a generic evolutionary urban unit ("city") and its necessary adaptations to the information provided by each national statistical system. Second, the hierarchical structure and the urban growth process are compared at macro-scale for the seven countries with reference to Zipf's and Gibrat's model: in agreement with an evolutionary theory of urban systems, large similarities shape the hierarchical structure and growth processes in BRICS countries as well as in Europe and United States, despite their positions at different stages in the urban transition that explain some structural peculiarities. Third, the individual trajectories of some 10,000 cities are mapped at micro-scale following a cluster analysis of their evolution over the last fifty years. A few common principles extracted from the evolutionary theory of urban systems can explain the diversity of these trajectories, including a specific pattern in their geographical repartition in the Chinese case. We conclude that the observations at macro-level when summarized as stylised facts can help in designing simulation models of urban systems whereas the urban trajectories identified at micro-level are consistent enough for constituting the basis of plausible future population projections.Comment: 14 pages, 9 figures; Pumain, Denise, et al. "Multilevel comparison of large urban systems." Cybergeo: European Journal of Geography (2015

Computer-aided boundary delineation of agricultural lands

The National Agricultural Statistics Service of the United States Department of Agriculture (USDA) presently uses labor-intensive aerial photographic interpretation techniques to divide large geographical areas into manageable-sized units for estimating domestic crop and livestock production. Prototype software, the computer-aided stratification (CAS) system, was developed to automate the procedure, and currently runs on a Sun-based image processing system. With a background display of LANDSAT Thematic Mapper and United States Geological Survey Digital Line Graph data, the operator uses a cursor to delineate agricultural areas, called sampling units, which are assigned to strata of land-use and land-cover types. The resultant stratified sampling units are used as input into subsequent USDA sampling procedures. As a test, three counties in Missouri were chosen for application of the CAS procedures. Subsequent analysis indicates that CAS was five times faster in creating sampling units than the manual techniques were

The Role of Landscape Connectivity in Planning and Implementing Conservation and Restoration Priorities. Issues in Ecology

Landscape connectivity, the extent to which a landscape facilitates the movements of organisms and their genes, faces critical threats from both fragmentation and habitat loss. Many conservation efforts focus on protecting and enhancing connectivity to offset the impacts of habitat loss and fragmentation on biodiversity conservation, and to increase the resilience of reserve networks to potential threats associated with climate change. Loss of connectivity can reduce the size and quality of available habitat, impede and disrupt movement (including dispersal) to new habitats, and affect seasonal migration patterns. These changes can lead, in turn, to detrimental effects for populations and species, including decreased carrying capacity, population declines, loss of genetic variation, and ultimately species extinction. Measuring and mapping connectivity is facilitated by a growing number of quantitative approaches that can integrate large amounts of information about organisms’ life histories, habitat quality, and other features essential to evaluating connectivity for a given population or species. However, identifying effective approaches for maintaining and restoring connectivity poses several challenges, and our understanding of how connectivity should be designed to mitigate the impacts of climate change is, as yet, in its infancy. Scientists and managers must confront and overcome several challenges inherent in evaluating and planning for connectivity, including: •characterizing the biology of focal species; •understanding the strengths and the limitations of the models used to evaluate connectivity; •considering spatial and temporal extent in connectivity planning; •using caution in extrapolating results outside of observed conditions; •considering non-linear relationships that can complicate assumed or expected ecological responses; •accounting and planning for anthropogenic change in the landscape; •using well-defined goals and objectives to drive the selection of methods used for evaluating and planning for connectivity; •and communicating to the general public in clear and meaningful language the importance of connectivity to improve awareness and strengthen policies for ensuring conservation. Several aspects of connectivity science deserve additional attention in order to improve the effectiveness of design and implementation. Research on species persistence, behavioral ecology, and community structure is needed to reduce the uncertainty associated with connectivity models. Evaluating and testing connectivity responses to climate change will be critical to achieving conservation goals in the face of the rapid changes that will confront many communities and ecosystems. All of these potential areas of advancement will fall short of conservation goals if we do not effectively incorporate human activities into connectivity planning. While this Issue identifies substantial uncertainties in mapping connectivity and evaluating resilience to climate change, it is also clear that integrating human and natural landscape conservation planning to enhance habitat connectivity is essential for biodiversity conservation

Market structure and hospital efficiency: Evaluating potential effects of deregulation in a national health service

In this article we examine the potential effect of market structure on hospital technical efficiency as a measure of performance controlled by ownership and regulation. This study is relevant to provide an evaluation of the potential effects of recommended and initiated deregulation policies in order to promote market reforms in the context of a European National Health Service. Our goal was reached through three main empirical stages. Firstly, using patient origin data from hospitals in the region of Catalonia in 1990, we estimated geographic hospital markets through the Elzinga--Hogarty approach, based on patient flows. Then we measured the market level of concentration using the Herfindahl--Hirschman index. Secondly, technical and scale efficiency scores for each hospital was obtained specifying a Data Envelopment Analysis. According to the data nearly two--thirds of the hospitals operate under the production frontier with an average efficiency score of 0.841. Finally, the determinants of the efficiency scores were investigated using a censored regression model. Special attention was paid to test the hypothesis that there is an efficiency improvement in more competitive markets. The results suggest that the number of competitors in the market contributes positively to technical efficiency and there is some evidence that the differences in efficiency scores are attributed to several environmental factors such as ownership, market structure and regulation effects.Geographic markets, market concentration, technical efficiency, data envelopment analysis, censored regression model

DEVELOPMENT OF A SPATIALY EXPLICIT HABITAT PATCH MODEL (C-PAN) AND COMPARATIVE ANALYSIS OF PATCH MODELING TECHNIQUES: THE CRAFTING OF A NEW TOOL FOR CONSERVATION PLANNERS

ABSTRACT Ecological theories including island biogeography, intermediate disturbance, metapopulation and metacommunity all suggest that habitat patches of larger size and those comprised of substantial configurations of interior or core habitat possess the greatest potential for long-term species viability. As a direct means of mitigating edge encroachment and fragmentation\u27s other adverse effects, there is a growing consensus among conservation planners that assembling larger, more cohesive tracts with substantial core area is of ecological value in conservation planning. Larger and more cohesive patches are believed to sustain larger and more viable local populations, enhance overall biodiversity, incorporate a wider array of natural disturbance regimes, and maintain more vulnerable, specialist species for the long term. Therefore, it is important that size and cohesion metrics be incorporated in patch and reserve modeling and design. This research developed a spatially explicit patch modeling approach designed to incorporate these metrics. This new modeling tool is entitled the Cohesive-Patch Aggregation and Network (C-PAN) model. It was created using ArcMap 9.3 and the Spatial Modeler extension. The model was first tested at a pilot scale (the State of South Carolina) and then up-scaled to evaluate a much larger area (the Northern Appalachian/Acadian Ecoregion). The C-PAN approach is most appropriate for use on species requiring substantial core area and those sensitive to edge characteristics. It is also intended to serve as an alternative approach to heavily parameterized patch modeling methods when species-specific parameterization data are not available. There exist a number of potential benefits associated with C-PAN usage. The C-PAN model searches landscapes for highly cohesive patches with substantial core area within an existing GIS framework. The aggregation and overlay processes used by the model also appeared to be an improvement over highly parameterized approaches which utilize region-growing components for generating patches. Additionally, the Landscape Cohesion Index (LCI) that is generated as part of the patch generation process proved beneficial for measuring fragmentation metrics across multiple sites and landscapes. This may be the first patch modeling approach to use landscape cohesion scores as a means of seeding patches based on their core area composition from the onset of the modeling process. The LCI allows users to delineate patches based on the statistical uniqueness of their core composition. This frees the user from selecting potentially unknown parameter settings when using other more complex approaches. Instead, it allows patches to be delineated and ranked based on how cohesive they are within the landscape. Both of these features may prove attractive to users as they ultimately make the tool more readily accessible to less technical practitioners. The C-PAN model was then used to generate a unique set of patches in the Northern Appalachian/Acadian Ecoregion. C-PAN was then compared to two ArcGIS (v9.3) based commonly used patch generation tools. The tools, Corridor Designer (v1) and FunConn (v1) were used for this analysis because they represent two highly utilized approaches which are most similar to the C-PAN model in both modeling mechanics and process. The patch outputs from the three tools were then compared and evaluated. This analysis was aimed at addressing a void within the literature of comparing the results of multiple patch modeling approaches. This analysis also served as a means of validating the C-PAN approach by comparing patch outputs of the three approaches. C-PAN performed well when compared to the existing patch modeling tools of Corridor Design and FunConn. For all of the spatial and target capture metrics measured, C-PAN ranked first or second among all approaches. The results indicated that the C-PAN patch modeling approach performed as well, and better, in the patch metrics evaluated here (patch area, edge/area ratios, average nearest neighbor, average Human Footprint (HF) score, Last of the Wild (LOW) capture, and patch commission. At relatively high patch selectiveness, the outputs of C-PAN and Corridor design were the most similar in size and distribution across the ecoregion-scale study area. Furthermore, of the three patch delineation tools, C-PAN appears to provide users with greater site discrimination capabilities than Corridor Design or FunConn. This resulted in providing users with a more selective set of discrete patches than the FunConn approach. Both C-PAN and Corridor Design were effective in delineating highly homogenous patches. These results indicate that the C-PAN patch modeling approach outperforms Corridor Designer and FunConn when measures of patch cohesion and core area are of importance. A graph theory based connectivity analysis was then conducted in order to identify and compare linkages between patches from the three patch modeling scenarios. The landscape networks modeled for each of the three scenarios indicated that while local connectivity in portions of the ecoregion may exist, widespread connectivity across the ecoregion as a whole was less likely. This was apparent in the C-PAN and Corridor Design patch scenarios, as multiple connections were delineated across the majority of the study area. Alternatively, no connections were delineated linking portions of the large graphs located within the central portion of the ecoregion with smaller and more linear graphs located in the periphery of the region. This was attributable to natural bottlenecks and relatively high Human Footprint (HF) values in those potential linkage areas. The landscape network derived as part of the FunConn patch scenario indicated even further diminished connectivity within portions of the ecoregion. The C-PAN patch network scenario was comprised of the greatest number of patches. This ultimately resulted in the delineation of multiple and potentially functional redundancies in the landscape network. Increasing the number of patches also improved distance metrics within the minimum spanning tree for this scenario. More patches served as intermediate stepping stones which resulted in shorter linkage and edge lengths and smaller average area corridor requirements. The FunConn patch landscape network however connected significantly fewer patches. This resulted in the longest linkage and edge distances and the largest average corridors within the ecoregion. This represents an apparent tradeoff between the number of potentially beneficial redundant connections and total landscape network corridor area. While more connections may contribute to increased landscape connectivity and landscape function, the increased area requirement make it more costly to implement. On the other hand, fewer connections may be less costly from an implementation standpoint, but may also reduce landscape connectivity and ecological function. The landscape networks were then used to test a simplifying assumption often used in conservation planning: that coarse-scale corridors may provide overlapping or \u27umbrella\u27 effects for other scenarios. This was accomplished by conducting an analysis of corridor overlap among these three scenarios. This work is among the first corridor gap analyses to be conducted at the ecoregion-scale. The corridor gap analysis indicated that 5% of the corridor area for all 3 scenarios was spatially coincident, 34% was coincident over 2 scenarios, while the majority of corridor area (59%) was non-redundant. These results are intriguing for two reasons. First, this gap analysis proved to be a useful tool in identifying potential priority conservation areas. Areas held in common may prove to be no-regret areas for conservation action as they provide overlapping coverage across multiple conservation scenarios. Second, the significant coverage gaps among corridors from these three scenarios indicates that selecting \u27what\u27 to connect at the ecoregion-scale has significant implications for selected corridors. As there was so little modeled corridor area in common among scenarios, there is little reason to believe alternate corridors would be functionally equivalent. This indicates that connecting any one set of habitat nodes would not likely serve as a corridor umbrella for all other scenarios. The ecoregion-scale connectivity analysis conducted here was also useful in flagging areas for conservation prioritization based on their connectivity role within an ecoregion-scale context. Connectivity analysis at this scale may also prove useful for evaluating connectivity at local scales. Any one of the subgraphs found within these modeled landscape networks could help inform local scale conservation efforts. Similarly, local scale connectivity and conservation actions could be added to the ecoregion-scale landscape network. As with many things, a successful landscape network is made up of the sum of its locally implemented parts. Of additional interest, the large size and area requirements of ecoregion-scale corridors may prove to be potential mechanisms by which landscape scale gradients and processes can be included within present day networks of protected lands. While this research did not explore this explicitly, ecoregion-scale corridors may prove to be a provocative means by which natural disturbance regimes, environmental gradients, and shifting species ranges may be captured in conservation networks by virtue of their large size. As such, it may be worth considering ecoregion-scale corridors as implementable conservation components that may facilitate planning for persistence in the face of global climate change