Spanish unemployment: normative versus analytical regionalisation procedures

In applied regional analysis, statistical information is usually published at different territorial levels with the aim of providing information of interest for different potential users. When using this information, there are two different choices: first, to use normative regions (towns, provinces, etc.), or, second, to design analytical regions directly related with the analysed phenomena. In this paper, provincial time series of unemployment rates in Spain are used in order to compare the results obtained by applying two analytical regionalisation models (a two stages procedure based on cluster analysis and a procedure based on mathematical programming) with the normative regions available at two different scales: NUTS II and NUTS I. The results have shown that more homogeneous regions were designed when applying both analytical regionalisation tools. Two other obtained interesting results are related with the fact that analytical regions were also more stable along time and with the effects of scale in the regionalisation process. Keywords: Unemployment, normative region, analytical region, regionalisation. JEL Codes: E24, R23, C61.

Spanish unemployment: Normative versus analytical regionalisation procedures

In applied regional analysis, statistical information is usually published at different territorial levels with the aim of providing information of interest for different potential users. When using this information, there are two different choices: first, to use normative regions (towns, provinces, etc.), or, second, to design analytical regions directly related with the analysed phenomena. In this paper, provincial time series of unemployment rates in Spain are used in order to compare the results obtained by applying two analytical regionalisation models (a two stages procedure based on cluster analysis and a procedure based on mathematical programming) with the normative regions available at two different scales: NUTS II and NUTS I. The results have shown that more homogeneous regions were designed when applying both analytical regionalisation tools. Two other obtained interesting results are related with the fact that analytical regions were also more stable along time and with the effects of scale in the regionalisation process.unemployment, regionalisation, analytical region, normative region

Design of Homogeneous Territorial Units: A Methodological Proposal

One of the main questions to solve when analysing geographically added information consists of the design of territorial units adjusted to the objectives of the study. This is related with the reduction of the effects of the Modifiable Areal Unit Problem (MAUP). In this paper an optimisation model to solve regionalisation problems is proposed. This model seeks to reduce some disadvantages found in previous works about automated regionalisation tools.contiguity constraint, zone design, optimisation, modifiable areal unit problem

Design of homogenous territorial units: a methodological proposal

One of the main questions to solve when analysing geographically added information consists of the design of territorial units adjusted to the objectives of the study. In fact, in those cases where territorial information is aggregated, ad-hoc criteria are usually applied as there are not regionalization methods flexible enough. Moreover, and without taking into account the aggregation method applied, there is an implicit risk that is known in the literature as Modifiable Areal Unit Problem (MAUP) (Openshaw, 1984). This problem is related with the high sensitivity of statistical and econometric results to different aggregations of geographical data, which can negatively affect the robustness of the analysis. In this paper, an optimization model is proposed with the aim of identifying homogenous territorial units related with the analyzed phenomena. This model seeks to reduce some disadvantages found in previous works about automated regionalisation tools. In particular, the model not only considers the characteristics of each element to group but also, the relationships among them, trying to avoid the MAUP. An algoritm, known as RASS (Regionalization Algorithm with Selective Search) it also proposed in order to obtain faster results from the model. The obtained results permit to affirm that the proposed methodology is able to identify a great variety of territorial configurations, taking into account the contiguity constraint among the different elements to be grouped.

Load balancing for massively multiplayer online games

Supporting thousands, possibly hundreds of thousands, of players is a requirement that must be satisfied when delivering server based online gaming as a commercial concern. Such a requirement may be satisfied by utilising the cumulative processing resources afforded by a cluster of servers. Clustering of servers allow great flexibility, as the game provider may add servers to satisfy an increase in processing demands, more players, or remove servers for routine maintenance or upgrading. If care is not taken, the way processing demands are distributed across a cluster of servers may hinder such flexibility and also hinder player interaction within a game. In this paper we present an approach to load balancing that is simple and effective, yet maintains the flexibility of a cluster while promoting player interaction

Regionalisation of groundwater droughts using hydrograph classification

Groundwater drought is a spatially and temporally variable phenomenon. Here we describe the development and application of a method to regionalize and quantify groundwater drought based on categorisation of Standardised Groundwater level Index (SGI) time series. The categorisation scheme uses non-hierarchical k-means cluster analysis. This has been applied to 74 SGI time series for the period January 1983 to August 2012 for a case study from Lincolnshire, UK. Six SGI time series clusters have been identified. For each cluster a correlation can be established between the mean SGI and a mean Standardised Precipitation Index (SPI) associated with an optimal SPI accumulation period, qmax. Based on a comparison of SPI time series for each cluster and SPI estimated for the whole study area, it is inferred that the clusters are largely independent of heterogeneity in the diving meteorology across the study region and are primarily a function of catchment and hydrogeological factors. This inference is supported by the observation that the majority of sites in each cluster are associated with one of three principal aquifers in the study region. The groundwater drought characteristics of the three largest clusters (CL1, CL2 and CL4 that constitute ~80% of the sites) have been analyzed. There is a common linear relationship between drought magnitude and duration for each of three clusters. However, there are differences in the character of the groundwater drought events between the three clusters as a function of autocorrelation of the mean SGI time series for each cluster. For example, CL1 has a relatively short period of significant SGI autocorrelation compared with CL2 (15 and 23 months respectively); CL1 has more than twice the number of drought episodes (39 episodes) than CL2 (15 episodes), and the average and maximum duration of droughts in CL1 (4.6 and 27 months) are less than half those of CL2 (11.3 and 61 months). The drought characteristics of CL4 are intermediate between those of CL1 and CL2. Differences in characteristics between the three clusters are also seen in their response to three major multi-annual droughts that occurred during the analysis period. For example, sites in CL2 with the longest SGI autocorrelation experience the greatest magnitude droughts and are the slowest to recover from drought, with groundwater drought conditions typically persisting at least six months longer than at sites in the other two clusters. Membership of the clusters reflects differences in the autocorrelation of the SGI time series that in turn is shown to be related to unsaturated zone thickness at individual boreholes. This last observation emphasises the importance of catchment and aquifer characteristics as (non-trivial) controls on groundwater drought hydrographs

The Innovative FlexPlan Grid-Planning Methodology: How Storage and Flexible Resources Could Help in De-Bottlenecking the European System

The FlexPlan Horizon2020 project aims at establishing a new grid-planning methodology which considers the opportunity to introduce new storage and flexibility resources in electricity transmission and distribution grids as an alternative to building new grid elements, in accordance with the intentions of the Clean Energy for all Europeans regulatory package of the European Commission. FlexPlan creates a new innovative grid-planning tool whose ambition is to go beyond the state of the art of planning methodologies by including the following innovative features: assessment of the best planning strategy by analysing in one shot a high number of candidate expansion options provided by a pre-processor tool, simultaneous mid- and long-term planning assessment over three grid years (2030, 2040, 2050), incorporation of a full range of cost–benefit analysis criteria into the target function, integrated transmission distribution planning, embedded environmental analysis (air quality, carbon footprint, landscape constraints), probabilistic contingency methodologies in replacement of the traditional N-1 criterion, application of numerical decomposition techniques to reduce calculation efforts and analysis of variability of yearly renewable energy sources (RES) and load time series through a Monte Carlo process. Six regional cases covering nearly the whole European continent are developed in order to cast a view on grid planning in Europe till 2050. FlexPlan will end up formulating guidelines for regulators and planning offices of system operators by indicating to what extent system flexibility can contribute to reducing overall system costs (operational + investment) yet maintaining current system security levels and which regulatory provisions could foster such process. This paper provides a complete description of the modelling features of the planning tool and pre-processor and provides the first results of their application in small-scale scenariosThe research leading to these results/this publication received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 86381

Optimising regionalisation techniques: identifying centres of endemism in the extraordinarily endemic-rich Cape Floristic Region

We used a very large dataset (>40% of all species) from the endemic-rich Cape Floristic Region (CFR) to explore the impact of different weighting techniques, coefficients to calculate similarity among the cells, and clustering approaches on biogeographical regionalisation. The results were used to revise the biogeographical subdivision of the CFR. We show that weighted data (down-weighting widespread species), similarity calculated using Kulczinsky's second measure, and clustering using UPGMA resulted in the optimal classification. This maximized the number of endemic species, the number of centres recognized, and operational geographic units assigned to centres of endemism (CoEs). We developed a dendrogram branch order cut-off (BOC) method to locate the optimal cut-off points on the dendrogram to define candidate clusters. Kulczinsky's second measure dendrograms were combined using consensus, identifying areas of conflict which could be due to biotic element overlap or transitional areas. Post-clustering GIS manipulation substantially enhanced the endemic composition and geographic size of candidate CoEs. Although there was broad spatial congruence with previous phytogeographic studies, our techniques allowed for the recovery of additional phytogeographic detail not previously described for the CFR

Classifying the biodiversity of the Great Barrier Reef World Heritage Area for the classification phase of the representative areas program

This technical report outlines the methods that the Great Barrier Reef Marine Park Authority used to classify the biodiversity of the marine environs of the Great Barrier Reef World Heritage Area for the Representative Areas Program. Classification was the first step in the multiphase Representative Areas Program that eventuated in a new network of no-take areas, free from extractive activities, in the Great Barrier Reef Marine Park

Properties and biases of the global heat flow compilation

Geothermal heat flow is inferred from the gradient of temperature values in boreholes or short-penetration probe measurements. Such measurements are expensive and logistically challenging in remote locations and, therefore, often targeted to regions of economic interest. As a result, measurements are not distributed evenly. Some tectonic, geologic and even topographic settings are overrepresented in global heat flow compilations; other settings are underrepresented or completely missing. These limitations in representation have implications for empirical heat flow models that use catalogue data to assign heat flow by the similarity of observables. In this contribution, we analyse the sampling bias in the Global Heat Flow database of the International Heat Flow Commission; the most recent and extensive heat flow catalogue, and discuss the implications for accurate prediction and global appraisals. We also suggest correction weights to reduce the bias when the catalogue is used for empirical modelling. From comparison with auxiliary variables, we find that each of the following settings is highly overrepresented for heat flow measurements; continental crust, sedimentary rocks, volcanic rocks, and Phanerozoic regions with hydrocarbon exploration. Oceanic crust, cratons, and metamorphic rocks are underrepresented. The findings also suggest a general tendency to measure heat flow in areas where the values are elevated; however, this conclusion depends on which auxiliary variable is under consideration to determine the settings. We anticipate that using our correction weights to balance disproportional representation will improve empirical heat flow models for remote regions and assist in the ongoing assessment of the Global Heat Flow database