Changes in the precipitation variability in Romania and its relation to the circulation weather types

Many studies link the observed changes in local climate to the variations in the atmospheric circulation. A tested method of describing atmospheric circulation is by employing the weather or circulations types. This paper presents an objective classification of the atmospheric circulation affecting Romania, between 1951 and 2010, and its relation to the significant changes in the amount of precipitation after 198

Ratio of Land Consumption Rate to Population Growth Rate in the Major Metropolitan Areas of Romania

In 2015, the 2030 Agenda for Sustainable Development was adopted by all United Nations Member States and includes a set of 17 Sustainable Development Goals. The indicator, “Ratio of land consumption rate to population growth rate” (indicator 11.3.1) was proposed for the monitoring of urban development. The present study proposes the analysis of the built-up space evolution in relation to the demographic growth in the main metropolitan areas of Romania using the 11.3.1 indicator. Land consumption rate and population growth rate (LCRPGR) is used to assess the sustainability of urban growth, which takes into account both the change in the built-up area and in the population. LCRPGR is calculated as the ratio of land consumption rate (LCR) and the population growth rate (PGR). The analysis was conducted at the metropolitan area level for the 2006–2009, 2009–2015 and 2015–2020 periods. LCR and PGR proved to be very useful indicators for the monitoring of the intensity of built-up changes in the eight metropolitan areas both in time and in space and are useful for the local and central administrations, in both the context of achieving the sustainable development targets and goals and in conducting urban design and planning

Dendroclimatic Reconstruction of Summer Temperatures in Irik Valley, Mount Elbrus (Greater Caucasus)

Recent evidence suggests an acceleration of glacier retreat in Greater Caucasus after 1980. For the same period a significant summer temperature warming trend and little or no change in precipitation variation have been observed. In this paper we seek to find similar past climatic conditions using a dendroclimatic reconstruction of summer temperatures from upper treeline sites after the Little Ice Age (LIA). Dendroclimatological sampling of Scots pine (Pinus sylvestris) has been made in Irik Valley, near Elbrus glacier, and a tree-ring width (TRW) chronology has been used to reconstruct May – August (MJJA) temperatures back to 1830. Three warm periods were identified in the MJJA temperatures reconstructed data (1830 - 1900), but we cannot appreciate if they had the same intensity as the recent warm perio

Dendroclimatic reconstruction of summer temperatures in Southern Carpathians

A significant summer temperature warming trend and little or no change in precipitation variation have been observed in the southern part of the Carpathians after 1980. In this paper we seek to find similar past climatic conditions using a dendroclimatic reconstruction of summer temperatures. Regional dendroclimatic reconstruction has been conducted in four different massifs (Bucegi, Piatra Craiului, Făgăraş and Parâng Massifs) belonging to the Southern Carpathians. The four sampling sites are located nearby the upper timberline, the forest stands being here dominated by Norway spruce trees (Picea abies (L) Karst). A tree-ring width (TRW) chronology of P. abies has been used here to reconstruct summer temperatures back to the end of 19th century. Results indicate that during the considered period, the decadal periods characterized by cold summers alternate with those with warm summer temperature

Change detection in the cluj forest district using remote sensing and gis application

International audienceThis paper focuses on the testing and comparison of the sensitivity of vegetation indices to determine the changes occurred in forest areas of the Cluj Forest District during the post-socialist period, between 1986 and 2009. Concurrently, the paper pursues to assess the way in which the socioeconomic and social changes have caused alterations of the forest areas. These have been significantly affected by the changes occurred over the past decades, as well as by the increase of the anthropization degree of the natural areas. Remote sensing applications are very efficient tools in detecting and assessing the changes both in space and over time. Two vegetation indices were used-NDVI and SAVI. The results show the spatio-temporal dynamics of the vegetation cover for approximately one third of the area, as the used indices presented decreasing values of up to 35% (NDVI 27%, SAVI 32%). The accuracy of classifying indices in decreasing, increasing and no-change areas is 88.20%, while the Kappa coefficient is 0.82. In addition, user's and producer's accuracy was calculated for each class

VIIRS Nighttime Light Data for Income Estimation at Local Level

The aim of the paper is to develop a model for the real-time estimation of local level income data by combining machine learning, Earth Observation, and Geographic Information System. More exactly, we estimated the income per capita by help of a machine learning model for 46 cities with more than 50,000 inhabitants, based on the National Polar-orbiting Partnership–Visible Infrared Imaging Radiometer Suite (NPP-VIIRS) nighttime satellite images from 2012–2018. For the automation of calculation, a new ModelBuilder type tool was developed within the ArcGIS software called EO-Incity (Earth Observation–Income city). The sum of light (SOL) data extracted by means of the EO-Incity tool and the observed income data were integrated in an algorithm within the MATLAB software in order to calculate a transfer equation and the average error. The results achieved were subsequently reintegrated in EO-Incity and used for the estimation of the income value at local level. The regression analyses highlighted a stable and strong relationship between SOL and income for the analyzed cities. The EO-Incity tool and the machine learning model proved to be efficient in the real-time estimation of the income at local level. When integrated in the information systems specific for smart cities, they can serve as a support for decision-making in order to fight poverty and reduce social inequalities

Snow avalanche history in Parâng Mountains (Southern Carpathians) revealed by dendrogeomorphic analyses

Parâng Mountains belong to Southern Carpathians, having the maximum altitude in Parângul Mare Peak (2519 m a.s.l.). The geology is dominated by crystalline schists, due to whom the relief is characterized by steep slopes. Between 1400 – 1700 m the average annual temperature is around 2-3ᴼC and the total precipitation about 1000-1200 mm/year. Coniferous belt extends roughly at the mentioned altitudes, being dominated by Norway spruce (Picea abies) forests. Above 1800 m the average annual temperature drops below 2ᴼC and the average rainfalls reach 1200 mm/year, allowing the development of alpine shrubs and alpine grassland (Oancea et al., 1987). Crests and steep slopes in these subalpine areas are prone to snow accumulation and avalanche release. Despite the favorable conditions for avalanche trigger in this area, only one avalanche event is historically recorded, with severe impact on forest areas, but no destructive impact on infrastructure or fatalities.</p

Ratio of Land Consumption Rate to Population Growth Rate in the Major Metropolitan Areas of Romania

In 2015, the 2030 Agenda for Sustainable Development was adopted by all United Nations Member States and includes a set of 17 Sustainable Development Goals. The indicator, “Ratio of land consumption rate to population growth rate” (indicator 11.3.1) was proposed for the monitoring of urban development. The present study proposes the analysis of the built-up space evolution in relation to the demographic growth in the main metropolitan areas of Romania using the 11.3.1 indicator. Land consumption rate and population growth rate (LCRPGR) is used to assess the sustainability of urban growth, which takes into account both the change in the built-up area and in the population. LCRPGR is calculated as the ratio of land consumption rate (LCR) and the population growth rate (PGR). The analysis was conducted at the metropolitan area level for the 2006–2009, 2009–2015 and 2015–2020 periods. LCR and PGR proved to be very useful indicators for the monitoring of the intensity of built-up changes in the eight metropolitan areas both in time and in space and are useful for the local and central administrations, in both the context of achieving the sustainable development targets and goals and in conducting urban design and planning