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Mining activities represent one of the main causes leading to subsidence in the natural and urban environment. Sustainable urban planning and detection of potential hazards in mining areas involve the use of adequate instruments such as the continuous monitoring of land subsidence. The complexity of urban environment demands the utilization of new methods for monitoring and quantifying the effects of the mining processes. In the last decades, considering the technological developments from the remote sensing domain, the Synthetic Aperture Radar Interferometry (InSAR) techniques offer the opportunity for early detection and continuous monitoring of subsidence in mining areas, including urban centers. Considering various parameters of mining subsidence monitoring, a review of several tens of studies realized in different mining sites, based on InSAR techniques, is presented. As mining subsidence in urban areas has a direct impact on the quality of life, the review is completed with demographic indicators assessment, followed by a study case on the dynamics of the population in an urban mining area from Romania, Ocnele Mari. [ABSTRACT FROM AUTHOR]

This paper presents the results of a study to determine the potential of radar imaging to detect classes of built-up areas defined in the Urban Atlas (UA) spatial database. The classes are distinguished by function and building density. In addition to the reflectance value itself, characteristics such as building density or spatial layout can improve the identification of these classes. In order to increase the classification possibilities and better exploit the potential of radar imagery, a grey-level co-occurrence matrix (GLCM) was generated to analyse the texture of built-up classes. Two types of synthetic-aperture radar (SAR) images from different sensors were used as test data: Sentinel-1 and ICEYE, which were selected for their different setup configurations and parameters. Classification was carried out using the Random Forests (RF) and Minimum Distance (MD) methods. The use of the MD classifier resulted in an overall accuracy of 64% and 51% for Sentinel-1 and ICEYE, respectively. In ICEYE, individual objects (e.g. buildings) are better recognised than classes defined by their function or density, as in UA classes. Sentinel-1 performed better than ICEYE, with its texture images better complementing the features of urban area classes. This remains a significant challenge due to the complexity of urban areas in defining and characterising urban area classes. Automatic acquisition of training fields directly from UA is problematic and it is therefore advisable to independently obtain reference data for built-up area categories. [ABSTRACT FROM AUTHOR]

Before 18:00 UTC a high precipitation supercell storm structure was observed and the storm was located over western Mazovia - a strong, locally destructive wind gust and hail were reported. Graph: Figure 8 Synoptic weather charts: 4 September 2016, 12:00 UTC and 5 September 2016, 00:00 UTCSource: National Weather Service (IMWM - NRI) Meteorological conditions in Warsaw Warsaw was under the influence of a warm, polar air mass with a maximum air temperature of 28.6°C. Graph: Figure 11 PPI 0.5° and cross-section images of supercell storm before approaching Warsaw: 4 September 2016, 18:53 UTCSource: National Weather Service (IMWM - NRI) The damage path was parallel to the movement of the supercell core (fig. 12). Keywords: Thunderstorm; supercell; synoptic conditions; damages; urban area; Warsaw EN Thunderstorm supercell synoptic conditions damages urban area Warsaw 63 74 12 03/11/22 20220101 NES 220101 Introduction One of the consequences of contemporary climate change is the growth in intensity of extreme weather phenomena that can cause widespread damages ([15], [7]). [Extracted from the article]

The study is part of humanity's current concerns of tempering climate change for sustainable development, in the context where the construction sector is responsible for a significant percentage of greenhouse gas emissions. In the present work, through a rigorous documentation, the authors synthesize several existing green and sustainable building certification systems. Extending the study from buildings to green neighbourhoods, to university campuses and even to green cities, models of their sustainable development are highlighted. The authors summarize the results of the various "green" ratings, initiating "Top 10 Greenest Universities in the world", demonstrating the interest of certification and classification. The paper presents the case study of the University of Oradea. From this perspective, participation in a rating of green campuses, as well as certification of buildings, are stimulating elements for approaching a sustainable development strategy. Thus, with the registration in the UI GreenMetric World University Rankings, the University of Oradea is set to rise in the ranking, which actually led to the improvement of the green criteria and implicitly to an orientation towards a sustainable development of the university campus. At the same time, the paper demonstrates that the energy certification of old buildings engaged in the "wave of renovations" is a tool for the sustainable development of university campuses. [ABSTRACT FROM AUTHOR]

The accelerated and uncontrolled urbanisation in the coastal zone of Mostaganem is exclusively at the expense of agricultural and natural areas and is reflected in the aggravation of their degradation. The study area is a 62-km-long littoral to the west of Mostaganem and includes 11 municipalities. The Corine Land Cover nomenclature was used by exploiting data from Landsat satellite images over a 30-year period. The exploitation of statistics related to agricultural and forestry areas reveals a worrying dynamics. All spaces are under pressure mainly due to urbanisation. The phenomena of urbanization and coastalisation and the development of seaside tourism have increased the pressures on natural heritage to the point of compromising it. The analysis identified seven thematic object classes for the study area. An assessment of the dynamics of urban, forest and agricultural areas is an informative indicator of the sustainability of natural areas in the coastline of Mostaganem. The cultivated areas measured from 42,356 ha in 1985 to 38,301 ha in 2015,forest formations from 8207 ha to 9298 ha and urbanised areas from 2604 ha to 5049 ha. The dramatic land use change stimulated by rapid urbanisation in the study areas has resulted in a fundamental change in the landscape pattern. The thematic maps and the results obtained through different periods show that the predominant agricultural landscape has been gradually converted into urban areas. [ABSTRACT FROM AUTHOR]

Urbanization has a far-reaching impact on the environment, economy, political and social processes. Therefore, understanding the spatial distribution and evolution of human settlements is a key element in planning strategies that ensure the sustainable development of urban and rural settlements. Accordingly, it is very important to map human settlements and to monitor the development of cities and villages. Therefore, the problem of settlements has found its reflection in the creation of global databases of urban areas. Global settlement data have extraordinary value. These data allow us to carry out the quantitative and qualitative analyses as well as to compare the settlement network at a regional, national and global scale. However, the possibility of conducting both spatial and attribute analyses of these data would be even more valuable. The article describes how to prepare raster data so that they can be implemented into a vector database. It answers the questions whether it is possible to combine these data with databases available in Poland and what benefits it brings. It presents the methods of data generalization and the optimization of time and disk space. As a result of the study, two vector databases with GUF data were developed. The first database resolution is similar to the original (~12 m resolution) database, the second database contains less detailed (~20 m resolution) data, generalized using mathematical morphology. Both databases have been enriched with descriptive data obtained from the National Geodetic and Cartographic Resource. [ABSTRACT FROM AUTHOR]

Urban changes occur as a result of new constructions or destructions of buildings, extensions, excavation works and earth fill arising from urbanization or disasters. The fast and efficient detection of urban changes enables us to update geo-databases and allows effective planning and disaster management. This study concerns the visualization and analysis of urban changes using multi-period point clouds from aerial images. The urban changes in the city centre of the Konya Metropolitan area within arbitrary periods between the years 1951, 1975, 1998 and 2010 were estimated after comparing the point clouds by using the iterative closest point (ICP) algorithm. The changes were detected with the point-to-surface distances between the point clouds. The degrees of the changes were expressed with the RMSEs of these point-to-surface distances. In addition, the change size and proportion during the historical periods were analysed. The proposed multi-period change visualization and analysis method ensures strict management against unauthorized building or excavation and more operative urban planning. [ABSTRACT FROM AUTHOR]