In order to measure progress in achieving the Sustainable Development Goals (SDGs) by 2030, 169 targets have been approved globally. Even though interest in implementing these goals is high, many states have not yet established a set of subnational indicators to measure the implementation of the SDGs and have not completed their own assessment of progress in achieving these global goals. This study aims to measure the progress toward achieving the SDG at local and regional level in Romania by calculating the SDG Index. For the calculation of the SDG Index at subnational level, we propose an integrated approach based on 90 indicators, stored and processed in a PostgreSQL object-relational database. The results show the concentration of the highest performances of sustainable development in some specific geographical areas. The rural areas and the extended peripheral regions in the eastern and southern part of the country are the poorest performers.

This paper investigates local-scale social vulnerability to flood hazards in Romania, aiming to identify the most vulnerable social and demographic groups across a wide range of geographical locations by considering three dimensions: demographic, socioeconomic, and the built environment. The purpose of the paper is threefold: first, it strives to improve the Social Vulnerability model (SoVI®) by applying a different weighting method adapted to the Romanian context, taking into consideration the municipalities exposed to flood movements. Second, it aims to develop an assessment model for the most vulnerable communities by measuring the heterogeneity according to local indicators related to disaster risks. Third, it aims to facilitate emergency managers to identify community sub-groups that are more susceptible to loss and to increase the resilience of local communities. To perform local-level vulnerability mapping, 28 variables were selected and three aggregated indexes were constructed with the help of the ArcGIS software. Moreover, a model of Geographically Weighted Regression (GWR) between communities directly affected by floods and localities with high- and very high values of the Local Social Vulnerability Index (LoSoVI) was used to explore the spatial relationship among them and to compare the appropriateness of Ordinary Least Square (OLS) and GWR for such modelling. The established GWR model has revealed that the negative effects of flood hazards are often associated with communities with a high degree of social vulnerability. Thus, the analysis is able to provide a more comprehensive picture on communities in desperate need of financial resources in order to have the ability to diminish the negative impacts of flood hazards and to provide a more sustainable society.

K e y w o r d s: local income, inequality, spatial clusters of income distribution, exploratory spatial data analysis, RomaniaA B S T R A C T with the EU average, although this was achieved at the cost of an increasing internal, sub-national divergence [17], [6]. Centre for Research on Settlements and Urbanism Journal of Settlements and Spatial PlanningJ o u r n a l h o m e p a g e: http://jssp.reviste.ubbcluj.roThe main aim of this study is to describe the spatial patterns of local income inequalities by employing techniques of spatial exploratory data analysis. Global and local measures of spatial autocorrelation were computed in order to obtain estimates for the existing spatial autocorrelation at the local income level. Using this information, we determined the spatial clusters of significantly auto-correlated local income distribution. The first major result of the paper consists in the measurement of the local income levels, an innovative contribution to the advancement in this field since there are no official statistics on local level economic data in Romania. The second major result of the paper consists in the identification and delineation of specific spatial structures at high spatial resolution. It enables the precise designation of peripheral regions for spatial planning interventions. The third major outcome of the paper brings empirical evidence for the existence of highly significant spatial interactions and for the strong spatial interconnections between areas of similar local income levels.

Night-time lights satellite images provide a new opportunity to measure regional inequality in real-time by developing the Night Light Development Index (NLDI). The NLDI was extracted using the Gini coefficient approach based on population and night light spatial distribution in Romania. Night-time light data were calculated using a grid with a 0.15 km 2 area, based on Defense Meteorological Satellite Program (DMSP) /Operational Linescan System (OLS satellite imagery for the 1992-2013 period and based on the National Polar-orbiting Partnership-Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) satellite imagery for the 2014-2018 period. Two population density grids were created at the level of equal cells (0.15 km 2 ) using ArcGIS and PostgreSQL software, and census data from 1992 and 2011. Subsequently, based on this data and using the Gini index approach, the Night Light Development Index (NLDI) was calculated within the MATLAB software. The NLDI was obtained for 42 administrative counties (nomenclature of territorial units for statistics level 3 (NUTS-3 units)) for the 1992-2018 period. The statistical relationship between the NLDI and the socio-economic, demographic, and geographic variables highlighted a strong indirect relationship with local tax income and gross domestic product (GDP) per capita. The polynomial model proved to be better in estimating income based on the NLDI and R 2 coefficients showed a significant improvement in total variation explained compared to the linear regression model. The NLDI calculated on the basis of night-time lights satellite images proved to be a good proxy for measuring regional inequalities. Therefore, it can play a crucial role in monitoring the progress made in the implementation of Sustainable Development Goal 10 (reduced inequalities).The adoption of the 2030 Agenda with its 17 Sustainable Development Goals (SDGs) created a framework for a radical change in the use of geospatial and EO solutions: 60% of the 169 SDG-related targets and 232 indicators can be directly monitored with EO solutions [4]. SDG 10 aims at reducing inequalities, which include, among other actions, empirical evidence production and monitoring the evolution of inequalities within and among countries. The monitoring of the latter is not difficult for most countries where national accounts and national statistical offices have been established [33]. The difficulties are related to the measurement of sub-national regional inequalities, with two shortcuts: scarce statistical data and a considerable time delay in calculating regional GDPs. Our study links statistical and geospatial frameworks for improved monitoring and reporting on SDG 10. At the same time, to our knowledge, this is the first attempt to introduce EO solutions in measuring SDG 10 at the sub-national level.We chose Romania as the study area for three reasons: it is one of the most unequal countries of the European Union (EU) [34-40]; these regional inequalities have been generated in the last 20 years [41][42][43]; and the country ...

The paper depicts the emergence of metropolitan region policies in Europe as being linked to the globalization debate and demonstrates how the idea of supporting metropolitan regions as national growth engines appeared to become not only an element of European regional policy but has appeared more and more in national urban policies as well. We propose to regard the diffusion of the underlying spatial development ideas as being linked to Europeanization processes as a form of transnational socialization and learning. We demonstrate how the urban dimension has been more and more strengthened in EU regional policies since the early 1990s and how influential some national level policies might have been for the European level. Some new member states show recent shifts towards more neoliberal development models arguing for more competitiveness through metropolization. We propose that this interrelates to a general shift towards the paradigm of a regional policy based on growth potentials and competitiveness across the EU. While the cohesion objective is nevertheless maintained, there seems to be a widespread consensus among policy-makers in Europe that to a certain extent the metropolitan paradigm is a logical and unavoidable result of economic transformation and globalization and is needed to achieve overall competitiveness.