The risk of the desertification of a part of Romania is increasingly evident, constituting a serious problem for the environment and the society. This article attempts to assess and monitor the risk of desertification in Dobrogea using Landsat Thematic Mapper (TM) satellite images acquired in 1987, 1994, 2000, 2007 and 2011. In order to assess the risk of desertification, we used as indicators the Modified Soil Adjustment Vegetation Index 1 (MSAVI1), the Moving Standard Deviation Index (MSDI) and the albedo, indices relating to the vegetation conditions, the landscape pattern and micrometeorology. The decision tree classifier (DTC) was also used on the basis of pre-established rules, and maps displaying six grades of desertification risk were obtained: non, very low, low, medium, high and severe. Land surface temperature (LST) was also used for the analysis. The results indicate that, according to pre-established rules for the period of 1987-2011, there are two grades of desertification risk that have an ascending trend in Dobrogea, namely very low and medium desertification. An investigation into the causes of the desertification risk revealed that high temperature is the main factor, accompanied by the destruction of forest shelterbelts and of the irrigation system and, to a smaller extent, by the fragmentation of agricultural land and the deforestation in the study area.
Protected areas of Romania have enjoyed particular importance after 1989, but, at the same time, they were subject to different anthropogenic and natural pressures which resulted in the occurrence of land cover changes. These changes have generally led to landscape degradation inside and at the borders of the protected areas. In this article, 12 landscape metrics were used in order to quantify landscape pattern and assess land cover changes in two protected areas, Piatra Craiului National Park (PCNP) and Bucegi Natural Park (BNP). The landscape metrics were obtained from land cover maps derived from Landsat Thematic Mapper (TM) and Landsat Enhanced Thematic Mapper Plus (ETM+) images from 1987, 1993, 2000, 2009 and 2010. Three land cover classes were analysed in PCNP and five land cover map classes in BNP. The results show a landscape fragmentation trend for both parks, affecting different types of land covers. Between 1987 and 2010, in PCNP fragmentation was, in principle, the result not only of anthropogenic activities such as forest cuttings and illegal logging but also of natural causes. In BNP, between 1987 and 2009, the fragmentation affected the pasture which resulted in the occurrence of bare land and rocky areas because of the erosion on the Bucegi Plateau.
During the communist regime, Romania's planned economy focused exclusively on production neglecting the environment protection. The lack of less polluting production technologies and of environmental protection measures led to excessive pollution in certain industrialized areas. This is the case of the town of Copsa Mica in Sibiu County, which in 1987 was considered one of the most polluted towns in Europe. The present study assesses the change vector analysis (CVA) technique using a Landsat Thematic Mapper (TM) image time series to monitor land cover changes caused by carbon black and heavy metal pollution. CVA was applied to the tasseled cap greenness (TCG) and tasseled cap brightness (TCB) indices, as well as to the Normalized Difference Vegetation Index (NDVI) and bare soil index (BI). Various maps were generated for the periods 1985-1994, 1994-2003, 2003-2011, and 1985-2011, and threshold values were determined for the detection of land cover change/no change. The change direction and magnitude values were cross-tabulated and classified. The technique was assessed based on the change versus no-change error matrix. The results show that in the area of Copsa Mica, land cover changes occurred because of a considerable decrease in the area affected by carbon black and heavy metal pollution. The CVA technique proved efficient in monitoring the land cover changes caused by pollution and especially by carbon black pollution. Soil pollution by heavy metals is reflected in the bare soil surfaces present in the imagery.
Reducing students’ dropout rate is a major challenge for universities. Based on a quantitative approach, this study aims to analyze and explain students’ dropout intention at the largest forestry school in Romania by collecting data in their first two months of the academic year prior to failing any courses. The study participants are undergraduate freshmen, male and female students, and the tools are psychological instruments commonly used or specifically developed for this study. Our findings partly confirm previous results, such as the higher intention of dropping out among male students compared to females, and also among students with admission GPA lower or equal to seven, on a GPA scale from 1 to 10, and among students from families with low income. Dropout intention can be explained by the academic performance expectancy, gender, family, socio-economic status, and perceived barriers to completion of studies. There were no differences regarding whether students were from urban or rural areas, proximity of university to home, and high school academic program. Our results may help to implement efficient measures for increasing student retention.
The desertification risk affects around 40% of the agricultural land in various regions of Romania. The purpose of this study is to analyse the risk of desertification in the south-west of Romania in the period 1984-2011 using the change vector analysis (CVA) technique and Landsat thematic mapper (TM) satellite images. CVA was applied to combinations of normalised difference vegetation index (NDVI)-albedo, NDVI-bare soil index (BI) and tasselled cap greenness (TCG)-tasselled cap brightness (TCB). The combination NDVI-albedo proved to be the best in assessing the desertification risk, with an overall accuracy of 87.67%, identifying a desertification risk on 25.16% of the studied period. The classification of the maps was performed for the following classes: desertification risk, re-growing and persistence. Four degrees of desertification risk and re-growing were used: low, medium, high and extreme. Using the combination NDVI-albedo, 0.53% of the analysed surface was assessed as having an extreme degree of desertification risk, 3.93% a high degree, 8.72% a medium degree and 11.98% a low degree. The driving forces behind the risk of desertification are both anthropogenic and climatic causes. The anthropogenic causes include the destruction of the irrigation system, deforestation, the destruction of the forest shelterbelts, the fragmentation of agricultural land and its inefficient management. Climatic causes refer to increase of temperatures, frequent and prolonged droughts and decline of the amount of precipitation.
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