In the North-East of the Moldavian Platform, the upper Badenian is composed of three lithologic units, on top of which there is Limestones and Marls with Lithothamnium Formation. At the level of this formation, the ge...In the North-East of the Moldavian Platform, the upper Badenian is composed of three lithologic units, on top of which there is Limestones and Marls with Lithothamnium Formation. At the level of this formation, the geological research conducted in four localities near the Prut Valley demonstrated, based on two new foraminifera genera identified in this area--Oolina and Velapertina-favorable conditions for the development of the stenohaline fauna, a marine shelf environment with warm water, as well as the certitude regarding the age of the late Badenian for these. These results were not previously reported in this area.展开更多
Soil morphological, physical and chemical properties are described at four locations along an elevational transect in the northeastern part of the Moldavian Plateau (Romania). These data contribute to the knowledge of...Soil morphological, physical and chemical properties are described at four locations along an elevational transect in the northeastern part of the Moldavian Plateau (Romania). These data contribute to the knowledge of the soils of this area and to their classification according to the USDA-Soil Taxonomy, FAOWRB and the SRTS-Romanian System. The soils were classified as Inceptisols, Alfisols and Mollisols, according to the USDA-Soil Taxonomy;Gleysol, Chernozem and Luvisol, according to the FAO-WRB and Gleiosol, Cernoziom, Preluvosol, Luvosol, according to the SRTS-Romanian System. The selected soils have a range of properties that represent the soilscape of the Moldavian subcarpathian plateau, characterised by a natural forest with oak as the dominant species. The selected soil parameters decreased with increasing elevation;calcium carbonate and clay leaching and accumulation are the main soil formation processes.展开更多
A correct assessment of the landslide susceptibility component is extremely useful for the diminution of associated potential risks to local economic development, particularly in regard to land use planning and soil c...A correct assessment of the landslide susceptibility component is extremely useful for the diminution of associated potential risks to local economic development, particularly in regard to land use planning and soil conservation. The purpose of the present study was to compare the usefulness of two methods, i.e., binary logistic regression(BLR) and analytical hierarchy process(AHP), for the assessment of landslide susceptibility over a 130-km^2 area in the Moldavian Plateau(eastern Romania) region, where landslides affect large areas and render them unsuitable for agriculture. A large scale inventory mapping of all types of landslides(covering 13.7% of the total area) was performed using orthophoto images, topographical maps, and field surveys. A geographic information system database was created, comprising the nine potential factors considered as most relevant for the landsliding process. Five factors(altitude, slope angle, slope aspect, surface lithology, and land use) were further selected for analysis through the application of a tolerance test and the stepwise filtering procedure of BLR. For each predictor, a corresponding raster layer was built and a dense grid of equally spaced points was generated, with an approximately equal number of points inside and outside the landslide area, in order to extract the values of the predictors from raster layers. Approximately half of the total number of points was used for model computation, while the other half was used for validation. Analytical hierarchy process was employed to derive factor weights, with several pair-wise comparison matrices being tested for this purpose. The class weights, on a scale of 0 to 1, were taken as normalized landslide densities. A comparison of results achieved through these two approaches showed that BLR was better suited for mapping landslide susceptibility, with 82.8% of the landslide area falling into the high and very high susceptibility classes. The susceptibility class separation using standard deviation was superior to either the equal interval or the natural break method. Results from the study area suggest that the statistical model achieved by BLR could be successfully extrapolated to the entire area of the Moldavian Plateau.展开更多
文摘In the North-East of the Moldavian Platform, the upper Badenian is composed of three lithologic units, on top of which there is Limestones and Marls with Lithothamnium Formation. At the level of this formation, the geological research conducted in four localities near the Prut Valley demonstrated, based on two new foraminifera genera identified in this area--Oolina and Velapertina-favorable conditions for the development of the stenohaline fauna, a marine shelf environment with warm water, as well as the certitude regarding the age of the late Badenian for these. These results were not previously reported in this area.
文摘Soil morphological, physical and chemical properties are described at four locations along an elevational transect in the northeastern part of the Moldavian Plateau (Romania). These data contribute to the knowledge of the soils of this area and to their classification according to the USDA-Soil Taxonomy, FAOWRB and the SRTS-Romanian System. The soils were classified as Inceptisols, Alfisols and Mollisols, according to the USDA-Soil Taxonomy;Gleysol, Chernozem and Luvisol, according to the FAO-WRB and Gleiosol, Cernoziom, Preluvosol, Luvosol, according to the SRTS-Romanian System. The selected soils have a range of properties that represent the soilscape of the Moldavian subcarpathian plateau, characterised by a natural forest with oak as the dominant species. The selected soil parameters decreased with increasing elevation;calcium carbonate and clay leaching and accumulation are the main soil formation processes.
文摘A correct assessment of the landslide susceptibility component is extremely useful for the diminution of associated potential risks to local economic development, particularly in regard to land use planning and soil conservation. The purpose of the present study was to compare the usefulness of two methods, i.e., binary logistic regression(BLR) and analytical hierarchy process(AHP), for the assessment of landslide susceptibility over a 130-km^2 area in the Moldavian Plateau(eastern Romania) region, where landslides affect large areas and render them unsuitable for agriculture. A large scale inventory mapping of all types of landslides(covering 13.7% of the total area) was performed using orthophoto images, topographical maps, and field surveys. A geographic information system database was created, comprising the nine potential factors considered as most relevant for the landsliding process. Five factors(altitude, slope angle, slope aspect, surface lithology, and land use) were further selected for analysis through the application of a tolerance test and the stepwise filtering procedure of BLR. For each predictor, a corresponding raster layer was built and a dense grid of equally spaced points was generated, with an approximately equal number of points inside and outside the landslide area, in order to extract the values of the predictors from raster layers. Approximately half of the total number of points was used for model computation, while the other half was used for validation. Analytical hierarchy process was employed to derive factor weights, with several pair-wise comparison matrices being tested for this purpose. The class weights, on a scale of 0 to 1, were taken as normalized landslide densities. A comparison of results achieved through these two approaches showed that BLR was better suited for mapping landslide susceptibility, with 82.8% of the landslide area falling into the high and very high susceptibility classes. The susceptibility class separation using standard deviation was superior to either the equal interval or the natural break method. Results from the study area suggest that the statistical model achieved by BLR could be successfully extrapolated to the entire area of the Moldavian Plateau.
