Space planning in Prahova Subcarpathians, Romania. Landslides - land cover relationship analysis

Space planning in Prahova Subcarpathians, Romania. Landslides - land cover relationship analysis. There is a strong relationship between the anthropogenic influence and the geomorphological processes, resulting limitations for settlements expansion, but also changes of the relief caused by human activities. The aim of this study is to identify a model for the analysis of the relationship between society and environment under a geomorphological concern, with a case study from a representative Romanian-Subcarpathian hills region. The analysis consisted in combining two methods, one for the landslide susceptibility evaluation and another for the evaluation of the human component from the study area, taking into account the elements at risk, the infrastructure, the settlement growth etc. The results show the existence of important areas with high and very high levels of the landslide susceptibility overlapped with settlements built-up areas and other anthropogenic elements. In some areas the geomorphic risk problem stopped the expansion of the built-up area, while in other cases these problems were ignored. All these lead to the conclusion that these complex maps should be used when conducting a development plan for a settlement, thus ensuring the avoidance of a catastrophic event, otherwise difficult to predict

Land cover classification in Romanian Carpathians and Subcarpathians using multi-date Sentinel-2 remote sensing imagery

In this article, we processed Sentinel-2 images in order to obtain high accuracy land cover maps for two complementary study areas. The first is represented by the Romanian Subcarpathians, a hilly highly fragmented area with heterogeneous land cover pattern and the second by Romanian Carpathians, a mountain area with homogenous structure of vegetation cover. The aim of this article is to evaluate the potential of a singledate in comparison with multi-date images for which a complete calibration and an iterative process of supervised classification using Maximum Likelihood (ML) and Support Vector Machine (SVM) algorithms were applied for the both study areas. The results show that in the case of Subcarpathian area, the SVM classification on multi-date images has better accuracy due to high complexity of the land cover pattern and spectral similarities between classes, while in the Carpathians, the ML returns good accuracy, consequence of high spectral separabilities between compact features. The validation process based on ground reference data shows good accuracies, about 92.41% for the Subcarpathians and 98.65% for the Carpathians. It is clearly noticed that the land cover pattern determines the use of different algorithms and the multi-date images enhance the overall accuracy of the classification

Urban landscape change in Carpathian Mountain Resorts

<p>Mapping of urban landscape change in detail scale is a difficult task when analysis is focused on a longer period with little data available. This is also the case of Romanian resort towns, where the latest development replaces former urban structures characterized by lower densities and larger green areas with a new pattern, consisting of more compact districts. The paper focuses on mapping urban change in one of the most popular mountain resorts in Romanian Carpathians, the town of Bușteni (820–980 m), located along the Upper Prahova Valley, at the bottom of Bucegi Massif. This research integrates data from historical aerial photos, photogrammetrically processed (1969) as well as digital orthophotos (2012). For an adequate representation, we created a database containing two vector datasets (buildings), corresponding to both historical moments, in order to calculate the Built-up Index (BI). The <i>change map</i> features, in detail scale, the difference in urban patterns, concerning their spatial distribution and intensity. This type of analysis is a very useful instrument in urban planning, protected area designing and touristic resort development.</p