The accentuated dynamics of the real estate markets of the last 20 years, determined that a large part of the territories in the immediate vicinity of the big urban centers, to change their category of land use, in an accelerated rhythm. Most of the time, the land use changes according to the market requirements, the predominantly agricultural lands being occupied by constructions with residential or industrial functions. Identifying these changes is a difficult task due to the heterogeneity of spatial databases that come from different real estate development projects, so determining and implementing new methods to track land changes are currently highly required. This paper presents a methodologically innovative index-based approach for the rapid mapping of built-up areas, using Landsat-5, Landsat-7, and Landsat-8 satellite imagery. The approach described in this study differs from other conventional methods by the way the analysis was performed and also by the thematic indices used in the processes of built-up area delineation. The method, structured in a complex model, based on Remote Sensing and GIS techniques, can be divided into three distinct phases. The first stage is related to the pre-processing of the remote sensing data. The second stage involves the calculation of the normalized difference vegetation index (NDVI), the modified normalized difference water index (MNDWI), and the bare soil index (BI) correlated with the extraction of all areas not covered by vegetation; respectively, the elimination from the result of all areas covered by water, bare land, or uncultivated arable land. The result of this stage is represented by a distinct thematic layer that contains only built-up areas and other associated territories. The last step of the model is represented by the validation of the results, which was performed based on statistical methods and also by direct comparison with field reality, obtaining a validation coefficient which is generally above 85% for any of the methods used. The validation process shows us that by applying this method, the fast mapping of the built-up areas is significantly enhanced and the model is suitable to be implemented on a larger scale in any practical and theoretical application that aims at the rapid mapping of the built-up areas and their evolutionary modeling.

Spatial planning decisions form the basis of territorial progress by enhancing the resilience and opportunities for local and regional development. Therefore, decisions made as a result of multidisciplinary studies based on GIS assessment of all involved factors can provide a real and up-to-date image of the analyzed territory. In this context, geomorphic processes are among the factors restricting development, affecting built-up areas, transport infrastructure, and economic activities. This paper assesses geomorphic processes at the level of Cluj County, Romania, which mainly consist of active landslides that directly impact the accessibility of communities and their degree of safety, while accelerated soil erosion severely affects the output of land used for agriculture. GIS technology and a semi-quantitative model for determining the landslide hazard were used to classify landslides across occurrence probability classes. This methodology was implemented in Romania through Government Decision no. 447/2003. The USLE model was used to determine the soil erosion. As a result, the territory of Cluj County, which is the study area of this paper, was entirely included in one of the classes of risk concerning active geomorphic processes. Another important aspect consisted of categorizing transport infrastructure according to risk classes. A population risk assessment was also performed, taking into account the degree of accessibility of the territorial emergency department in the event that such hazards and processes occur. These results form the basis of proposals to efficiently plan the county territory, adapting decisions to the present trends in the evolution.

Natural and Migration Balance of the Population in Sibiu County between 1992 and 2021. Sibiu County has been characterised by a better demographic situation than the rest of Romania in the past three decades. The birth rate in Sibiu County has been around 10‰ for many years, above the national and regional average. The mortality rate had similar values, around 10‰ for many years, resulting in a natural balance rate around zero. However, during the pandemic (2020-2021), the birth rate dropped, and the mortality rate increased, which determined a negative natural balance rate at the level of Sibiu County, as low as -4.5‰ in 2021. The net migration rate, on the other hand, has been positive every year since 2006, reaching the highest value of 3.41‰ in 2019, right before the pandemic. The positive net migration rate determined also positive values of the total balance rate in Sibiu County between 2006 and 2019, reaching the highest value of 3.13‰ in 2019. However, the steep decline of the natural balance rate during the pandemic also affected the total balance rate, which became negative in both 2020 and 2021. Nevertheless, the total balance rate is expected to reverse back to positive values after the end of the pandemic. Within Sibiu County, the suburbanization is the major recent process that has an important demographic impact. Areas around the city of Sibiu, especially the commune of Șelimbăr and the town of Cisnădie, have experienced a huge demographic growth, due to migration, but also due to the natural balance rate, which increased suddenly because most of the migrants are young families. Similar situations, although at a lower scale, were recorded in other communes around the city of Sibiu, such as Șura Mare, Șura Mică and Cristian, as well as in communes in Hârtibaciu Plateau (Roșia, Nocrich, Vurpăr, Merghindeal, Chirpăr, Iacobeni), characterised by high birth rates. In contrast, many communes in the western and north-western parts of Sibiu County, such as those in Secașe Plateau (Ludoș, Păuca, Loamneș, Apoldu de Jos), Târnava Mare Corridor and the surrounding hills (Micăsasa, Șeica Mare, Axente Sever, Blăjel, Bazna, Alma, Ațel) and even in Mărginimea Sibiului (Tilișca, Râu Sadului, Jina) experienced a population decline due to outmigration and a negative natural balance rate and a negative net migration rate. Keywords: natural balance, net migration rate, population dynamics, Sibiu County, Romania

The Settlements and the Impact of Suburbanization on the Demographic Age Structure in Sibiu County, Romania. The process of suburbanization has had an impact on the settlement system in Sibiu County. Demographic data collected from the last two censuses (2011 and 2021) as well as from the National Institute of Statistics show that the cities of Sibiu and Mediaș experienced a demographic decline in the last decades, while their suburban areas increased demographically. The highest growth has been recorded in the commune of Șelimbăr and in the town of Cisnădie, as well as in other communes around the city of Sibiu (Șura Mare, Șura Mică, Cristian, Roșia). While there is no data regarding the age of the migrants from the core cities to their respective suburban areas, the analysis shows that most of them are young adults and their (future) children. This has led to a sharp change in the age structure of the population both in the core cities and in the suburban settlements. On the one hand, the cities of Sibiu and Mediaș experienced a decline in young and adult population, and an increase of the weight of the elderly population. On the other hand, suburban settlements have registered not just an increase in terms of population, but also in the weight of the young and adult population. Therefore, we witness a process of sharp rejuvenation in the suburban settlements (mostly in Șelimbăr and Cisnădie), at the same time with the intensification of demographic ageing in many parts of Sibiu County, including the two cities, Sibiu and Mediaș. At the same time, suburbanization brought along a number of issues, such as the insufficient number of educational institutions in the suburban areas and increased traffic due to the large number of commuters. Keywords: suburbanization, settlements, cities, age structure, Sibiu County, Romania.