Currently, there is little information regarding the recent spatiotemporal dynamics of upper timberline in the Carpathian Mountains. We reconstructed the temporal (1887–2018) and spatial dynamics of upper timberline in the Rodna Mountains (Eastern Carpathians) based on seven sets of maps and aerial photographs and explained its variability in relation to three main drivers: air temperature, land morphometry and anthropogenic pressure. The impact of natural drivers (temperature, morphometry) on timberline position was evaluated using a high-resolution digital elevation model, local and regional instrumental and modelled climate databases. The impact of anthropogenic factors on timberline position was documented from published sources such as local paleolimnological studies and historical documents. Results show that timberline rose on average with 113 ± 2 m on the northern slope of the Rodna Mts (currently reaching 1640 m above sea level (a.s.l.)) and with 182 ± 2 m on the southern slope (up to an elevation of 1539 m a.s.l.). Our results suggest that this pattern might be connected with the rising temperature over the recent decades. On the northern slope where land morphometry restricts anthropogenic activities, timberline reached the highest elevation. On the more accessible southern slope, anthropogenic land-use changes likely moderated timberline elevational rise under increasing temperatures.

The world has changed rapidly in recent months as a result of the impact of the COVID-19 pandemic on all areas of socio-economic life. The crisis directed, in a first phase, the efforts of the whole society in the direction of ensuring the public health, and later also towards the economic recovery by resuming the human activities. In this context, housing has been a point of stability and a starting point for all efforts, and access to adequate housing has proven its importance for ensuring the health and well-being of the population. The purpose of the research is to highlight a series of housing affordability problems pre-existent and new problems arising from the influence of the COVID-19 pandemic on the housing sector in Romania. The present research highlights pre-existing problems in the general picture of housing at the national level, how these issues condition access to adequate and affordable housing, the emergence of new risk groups in the population in terms of access to housing, highlights the impact of the pandemic on the ability of households to bear housing costs and proves that housing insecurity is exacerbated by the effects of the crisis. The analyzes used data provided by the National Institute of Statistics, Eurostat, the Quality of Life Research Institute as well as reports prepared by specialized European organizations.

<p>Landscape fragmentation is the expression of patchiness and spatial heterogeneity of land cover pattern. After the breakdown of the socialism regime in 1989, Romania has undergone significant changes at the level of political, institutional and socio-economic profile, which determined researchers to consider this country an experimental territory for land use and landscape research.</p><p>The aim of present study is to detect hotspots of changes of forests landscape fragmentation patterns in the Romanian Carpathian Mountains over the last 28 years. In order to meet our demand we applied a holistic approach to assess the multiple teleconnections between forest cover changes and the degree of fragmentation at regional scale for two distinct periods that make up the 1990-2018 period: (1) 1990-2006 (land restitution period or transition period to the market economy) and (2) 2006-2018 (post-accession period to the European Union).</p><p>The analysis were carried out using freely available time series CORINE Land Cover data of 1990, 2006 and 2018 provided by Copernicus Land Monitoring Services. The initial spatial datasets were processed with the help of Geographic Information Systems (GIS), while GUIDOS, a free software toolbox dedicated to quantitative analysis of digital landscape images, was used to generate spatial and statistics data of the degree of forest landscape fragmentation.</p><p>Our findings indicate that the first period of analysis was more dynamic regarding forest cover changes with a gross area gain of 316 304 ha (7.59%) and a gross area loss of 147 496 ha (3.54%) leading to a net forest area change of 168 808 ha (4.05%) which reflects the level of forest recovery. The change pattern of fragmentation classes showed that 332 045 ha (71.47%) of fragmentation decrease is found for the transition of dominant forest in 1990 into the less fragmented class interior in 2006, while 67 418 ha (65.10%) of all fragmentation increase is found for transition from interior in 1990 to dominant in 2006. The other side, for the period from 2006 to 2018 we found a gross area gain of 127 146 ha (2.93%) and a gross area loss of 212 933 ha (4.91%) leading to a net forest area change of -85 787 ha (-1.98%) which emphasizes the level of forest disturbance. In the same time frame, the high values of fragmentation pattern have been registered for the same classes, 56.82% for fragmentation decrease and 70.60% for fragmentation increase, respectively. The results highlight the reversible impact of land use change on land cover pattern, spatially shaped through afforestation in the first period of analysis and through deforestation in the second period. The afforestation process were determined by high rate of external migration, while deforestation process is a consequence of land restitution laws (Law no. 247/2005), which caused considerable mutations in the ownership of land.</p><p>The study emphasizes the impacts of land use policies and land management practices on the pattern of forest landscape and the usefulness of Guidos Toolbox, a universal digital image object analysis, to detect hotspots of changes at regional scale.</p>

Historical reconstruction of land-use and land cover dynamic often require comparing maps derived from different sources. Geographic information systems allow the extraction and quantitative analysis of information from historical maps. This study refers to the diachronic analysis of land use dynamics in the geographical area of Rădăuți municipality, territorial-administrative unit located in the northeastern part of Suceava county, Romania. The analysis is based on the use of geospatial techniques in extracting information from historical maps, for emphasizing the land cover and land use dynamic from a spatial and temporal point of view. The cartographic and statistic analysis is based on the identification of a variety of land use categories: croplands, woodlands, water bodies, artificial surfaces, degraded and unproductive lands. Selection of historical maps at a large scale (Austrian cadastral maps, scale 1:2 880; the topographical plans, scale 1:5 000 and ortophotos, scale 1:5 000, updated with aerial images using Terra Incognita 2.41 software) allows a detalied analysis on the land use dynamics in the above-mentioned area. Complementary, temporal dyanamic of the land use categories is highlighted by the choice of some benchmark years, i.e. 1856, 1978 and 2015 corresponding to a different historical, geographic, social and economic context. The results obtained emphasize the territorial distribution and the dynamic of land use categories conditioned by natural and socioeconomic driving factors which influenced with different frequency and intensity during of 159 years. The analysis revealed that the urban landscape has been very dynamic, displaying significant changes in most type of land use, most notably in the case of urban built-up, which emphasize substantial increases, from 134,93 hectares in 1856 to 773,42 hectares in 2015. The analysis of land use dynamic is very useful for planners, because it can argue the best decisions regarding sustainable development of urban areas.

<p>Urbanization and agriculture intensification accelerate the land use and cover conversions unbalancing the surface energy budget. Land Surface Temperature (LST) represents the land radiative skin temperature which is derived from solar radiation and is one of the most important indicators of local climate variability. The present work aims to analyze the effects of land use land cover changes (LULCC) on spatial pattern distribution of Land Surface Temperature in the first ring of Suceava Metropolitan Area over the last 35 years. In order to meet our demand we have conducted a spatio-temporal analysis using Geographical Information Systems (GIS) and Remote Sensing (RS) techniques. We have used two satellite images from Landsat 5 TM (23 August 1985) and 8 OLI/TIRS (23 August 2020) in order to create land cover maps by applying a supervised classification with spectral angle algorithm and to estimate Land Surface Temperature through the Plank Equation. Given that we have applied the supervised classification to define the four major land cover classes (bare soil, built-up area, vegetation and water bodies) we have used the classification-based method to determine the surface emissivity. The overall accuracies of the land cover maps of 1985 and 2020 were found to be 93.45%, and 96%, while the Kappa coefficients were found to be 0.90 and 0.94 for the years 1985 and 2020, respectively. The land cover change matrix showed that during the study period, 140.67 km<sup>2</sup> representing 34.60% of the total study area faced mutual conversion among four land cover types while 265.90 km<sup>2</sup> representing 65.40%  of the total study area remained unaltered. More exactly, built-up area and vegetation surfaces increased by 78.31% and 3.78%, respectively, while bare soil and water bodies decreased by 38.71% and 10.21%, respectively. LSTs found in the study area ranged from 18.27 to 33.91°C and 21.67 to 40.48°C for the years 1985 and 2020. The increases of spatially distributed maximum, mean and minimum LST were found 6.57°C, 3.84°C and 3.40°C, respectively. This means a LST increase by around 0.11°C per year for the study period of 35 years. Moreover, the results showed that covers without vegetation and artificial surfaces have recorded the highest temperatures: 26.18 to 30.11°C and 25.49 to 29.66°C for bare soil and built-up area, respectively. The increases of mean LSTs were 4.16°C, 3.96°C, 3.92°C and 3.53°C for the bare soil, vegetation, built-up area and water bodies, respectively, during the study period. On the other hand, in 1985 the highest maximum LST was 33.91°C in the built-up area followed by 31.26°C, 28.11°C and 24.90°C by bare soil, vegetation and water bodies, respectively, while in 2020 the highest maximum LST was 40.48°C in the built-up area followed by 35.28°C, 33.54°C and 28.98°C by bare soil, vegetation and water bodies, respectively. Based on the above findings, policymakers and urban planners should be concerned about future urban expansion and agriculture management in order to reduce the LST-related urban heat island or drought intensification problem.</p>