In the environmental risk assessment of oil fields, a detailed knowledge of the heterogeneity of groundwater surfaces is absolutely indispensable. Based on theoretical considerations, in order to analyse small-scale heterogeneities, we decided that the Sequential Gaussian Simulation (SGS) approach seemed to be the most appropriate one. This method gives preference to the reproduction of small-scale heterogeneities at the expense of local accuracy. To test whether this kind of heterogeneity of the groundwater level corresponds to sedimentological variability, a point bar of the River Tisza (South-Hungary) was chosen. In variograms, the longest range was derived from the large-scale sedimentological heterogeneity of the point-bar, the medium range was in accordance with the radius of the meander and its direction coincided with the depositional strike of the meander, while the shortest range corresponded to the lateral heterogeneity of the deposits where the ground water level was measured. The similarities and differences of the realizations of SGS express the uncertainty of the map representation of the ground water surface. The E-type estimates of 100 equiprobable realizations resulted in a very detailed surface. The hydraulic gradient map obtained from the E-type estimates can provide us with a better understanding of the local flow characteristics.
The aim of this study the authors measured and analyzed the effect of the exterior daily temperature change on the interior temperature in a dripstone cave visited by cavers exclusively. The measurement was carried out in the Hajnóczy Cave located in the southern part of Bükk Mountains in Hungary. Although only one entrance is known, there are more evidences for the strong effect of exterior conditions on the interior processes like temperature fluctuation and dripstone development. Using high resolution wireless digital thermometer sensor network the air temperature and air humidity were measured in 32 points in every 10 minutes for long time but now the data of a 8-days period were analyzed. Based on these data different zones of the cave could be separated and during summer conditions the climatic variability of the entrance transitional and deep cave zone was described. Based on statistical analysis of spatial information significant correlation was found between the exterior temperature fluctuation and that of such a cave chamber, which is relatively far from the cave entrance. This fact proves that existence of a fissure system which is permeable for air but not passable for cavers. During the measurement the human effect was also analyzed and 0.3-0.6 °C temperature rising was recognized for a short time. Because of the surface vicinity the effects of the environmental change can have sensible impact on the cave and its natural phenomena. Among others temperature rising, air humidity decreasing were detected in present study.
Hyperspectral remote sensing combined with advanced image processing techniques is an efficient tool for the identification of agricultural crops. In our study we pursued spectral analysis on a relatively small sample area using low number of training points to examine the potential of high resolution imagery. Spectral separability measurements were applied to reveal spectral overlapping between 4 crop species and for the discrimination we also used statistical comparisons such as plotting the PC values and calculating standard deviation of single band reflectance values on our classes. These statistical results were proven to be good indicators of spectral similarity and potential confusion of data samples. The classification of Spectral Angle Mapper (SAM) had an overall accuracy of 72% for the four species where the poorest results were obtained from the test points of garlic and sugar beet. Comparing the statistical analyses we concluded that spectral homogeneity does not necessarily have influence on the accuracy of mapping, whereas separability scores strongly correlate with classification results, implying also that preliminary statistical assessments can improve the efficiency of training site selection and provide useful information to specify some technical requirements of airborne hyperspectral surveys.
Land cover change and deforestation are important global ecosystem hazards. As for Syria, the current conflict and the subsequent absence of the forest preservation are main reasons for land cover change. This study aims to investigate the temporal and spatial aspects and trends of the land cover alterations in the southern Syrian coastal basins. In this study, land cover maps were made from surface reflectance images of Landsat-5(TM), Landsat-7(ETM+) and Landsat-8(OLI) during May (period of maximum vegetation cover) in 1987, 2002 and 2017. The images were classified into four different thematic classes using the maximum likelihood supervised classification method. The classification results were validated using 160 validation points in 2017, where overall accuracy was 83.75%. Spatial analysis was applied to investigate the land cover change during the period of 30 years for each basin and the whole study area. The results show 262.40 km2 reduction of forest and natural vegetation area during (1987-2017) period, and 72.5% of this reduction occurred during (2002-2017) period due to over-cutting of forest trees as a source of heating by local people, especially during the conflict period. This reduction was particularly high in the Alabrash and Hseen basins with 76.13 and 79.49 km2 respectively, and was accompanied by major increase of agriculture lands area which is attributed to dam construction in these basins which allowed people to cultivate rural lands for subsistence or to enhance their economic situation. The results of this study must draw the relevant authorities’ attention to preserve the remaining forest area.