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This research reports the use of a new method of geomorphological mapping in GIS environments, using a full-coverage, object-based method, following the guidelines of the new geomorphological legend proposed by ISPRA–AIGEO–CNG. This methodology is applied to a tributary valley of the Germanasca Valley, shaped into calcschist and greenschist, of the Piedmont Zone (Penninic Domain, Western Alps). The investigated sector is extensively affected by dep-seated gravitational slope deformation (DSGSD) that strongly influences the geological setting and the geomorphological features of the area. The mapping of these gravitational landforms in a traditional way creates some difficulties, essentially connected to the high density of information in the same site and the impossibility of specifying the relationships between different elements. The use of the full-coverage, object-based method instead is advantageous in mapping gravitational evidence. In detail, it allows for the representation of various landforms in the same sector, and their relationships, specifying the size of landforms, and with the possibility of multiscale representation in the GIS environment; and, it can progressively be update with the development of knowledge. This research confirms that the use of the full-coverage, object-based method allows for better mapping of the geomorphological features of DSGSD evidence compared to classical representation.

Abstract Regarding climate change, the world’s most discussed issue for the last few decades, countries like Bangladesh are always noteworthy due to its susceptibility resulting from its geography, hazard proneness, and socioeconomic condition. Thus, this aimed to justify the hypothesis that Bangladesh has spatial diversity in sectors of Climate Change Vulnerability (CCV) by identifying the sectors of vulnerability and visualizing the spatial distribution of vulnerability through multivariate geospatial analysis in the GIS environment. For an integrated assessment of CCV, 38 indicators (socio-economic and biophysical) have been incorporated in the IPCC framework in raster form. Test statistics have shown Kiser-Meyer-Olkin (KMO) value is 0.73 and the p-value of Bartlett’s sphericity is 0. The principal component analysis resulted in 6 principal components with 73.52% total explained variance. Sectors of CCV are the Climatic extreme event vulnerability (PC1), Meteorological shift vulnerability (PC2), Infrastructure and demographic vulnerability (PC3), Ecological vulnerability (PC4), Flood vulnerability (PC5), and Economic vulnerability (PC6) with Cronbach’s alpha 0.90, 0.81, 0.88, 0.72, 0.72, and 0.66 respectively. Among 3 clusters (Jenk’s Natural break) of weighted averaged indices, the highly vulnerable cluster has shown that the PC1 has the highest magnitude with a score of 0.53–0.87, while the PC5 has the highest spatial coverage with 24 districts. The present study however is a new edition in climate vulnerability assessment in Bangladesh since it encompasses multivariate spatial analysis to demonstrate countrywide CCV. This study should be an important tool for setting adaptation and mitigation strategies from the root level to policymaking platforms of Bangladesh.

Abstract In the Campo region, groundwater is critical for human consumption and social activity. Groundwater potential is influenced by a region's geological, geophysical, and hydrogeological factors. The major goals of this research are to determine which regions are ideal for productive groundwater drilling and to assess the source of salinity in the study area's coastal aquifers. The groundwater potential map was created using Geographic Information Systems (GIS) and the Hierarchical Analysis Process (AHP). The process of groundwater mineralization was studied using principal component analysis (PCA). Six variables were taken into account, and weights were assigned to them based on their impact on groundwater recharge. In a GIS environment, spatial integration and a combination of theme layers were conducted. Campo's groundwater potential map was divided into four zones: low 14.4% (389.6 km²), moderate 53.3% (1484.5 km²), high 28.3% (783.3 km²), and extremely high 4.1% (110.9 km²). The results of the PCA reveal a mechanism of water-rock interaction, as a result of geological alteration and a salinization process caused by the intrusion of seawater and human activity The source of salinity in groundwater is manmade (agricultural and residential activities) rather than seawater intrusion. Seawater infiltration is not greatly aided by the low lineament density found near the beaches.

Abstract. Coastal lagoons are highly dynamic and physically complicated systems. They are environmentally productive and socio-economically valuable. Contemporary global development and management pressures require a better understanding of their dynamics and sustainability. The present study focuses on the problem of water confinement in the Oualidia lagoon (Atlantic coast of Morocco). This lagoon is characterized by an asymmetric tidal propagation, with a shorter duration of the flood (rising tide) than the ebb (falling tide). In the long term, this contributes to the reduction of depths and the confinement of water upstream. After extensive studies, a sediment trap was created in 2011 to trap the finest sediment in the upstream part of the lagoon. This study aims to analyze the morphodynamical and sedimentological changes in the lagoon of Oualidia, after the sediment trap dredging. For this purpose, bathymetric surveys covering 6 years between 2006 and 2012 were analyzed, providing sufficient data to identify the morphological changes that the lagoon has undergone during this period. The data analysis was followed by a study of the lagoon bed dynamics using profile lines extracted from the bathymetric data in a GIS environment. As a result, the findings partly show that over 6 years, an average height of +0.65 m was gained by the lagoon, while the average change in the eroded areas was estimated to be −0.42 m. In addition, the eroded area in the lagoon was estimated to be about 1,513,800 m2 with an erosion volume of 633,383 m3, while the accumulated area found was about 2,699,396 m2 with an accumulation volume of 1,765,866 m3. These changes can be related to the large input of marine sediment, mainly caused by tidal currents and waves, but also to the creation of a sediment trap in the upstream area of the lagoon.

Os grandes aglomerados urbanos desencadeiam profundas problemáticas de natureza hidroclimática, resultantes principalmente das formas de uso e ocupação do solo. Os padrões hídricos, tais como escoamento e acúmulo de fluxo, são afetados diretamente pelo efeito de impermeabilização do solo decorrente das construções humanas e quando esta estrutura urbana é somada aos eventos climáticos extremos, culminam na ocorrência periódica de inundações. Diante deste contexto, o presente estudo tem como objetivo compreender e identificar os danos hidrológicos decorrentes da concentração urbana, sobre a dinâmica natural do escoamento, a fim de investigar os fatores que provocam estas inundações nas determinadas regiões. A área de estudo do presente trabalho é representada por folhas de amostragem do sensor LiDAR das Regiões político administrativas IV e VI do município do Recife, Pernambuco. Para subsidiar a análise proposta, os modelos digitais de elevação do projeto Pernambuco 3D, provenientes do sensor LiDAR, foram processados em ambiente SIG, e a partir destes dados de alta resolução espacial foi possível analisar detalhadamente as variáveis que propiciam o escoamento superficial e acúmulo de fluxo nas áreas em estudo. Os resultados obtidos para as áreas de amostragem, foram analisados e comparados com as políticas públicas de drenagem urbana e planejamento territorial vigentes, avaliando a relação entre as redes de macro e microdrenagem, com a ocorrência de inundações no meio urbano. The use of lidar data for the understanding of water flow and accumulation dynamics in the Recife – PEA B S T R A C TLarge urban agglomerations result in huge problems of hydroclimatic nature, resulting mainly from the forms of land use and occupation. Water patterns, such as runoff and flow accumulation, are directly affected by the waterproofing effect from human constructions, and when added to the extreme weather events, they culminate in a periodic occurrence of urban floods. The study area of the present work is represented by the LiDAR sensor sampling sheets from the administrative political Regions IV and VI of the municipality of Recife, in Pernambuco. Given this context, the present study aims to understand and identify the hydrological damage caused by the urban concentration on the natural dynamics of runoff, to investigate the factors that cause these floods in that specific region. To subsidize the proposed analysis, the digital elevation models of the Pernambuco 3D project, from the LiDAR sensor, were processed in a GIS environment, and from these high spatial resolution data it was possible to analyze in detail the variables that propitiate surface runoff and flow accumulation in the areas under study. The results obtained for the sampling areas were analyzed and compared with the urban drainage and territorial planning public policies in force, evaluating the relationship between the macro and micro drainage networks, with the occurrence of floods in the urban environment. Keywords: Geoprocessing. remote sensing. urbanization. urban flood. surface runoff.

The study of the phenomenon of flooding in an urban environment requires the integration of the city in its physical context, in this case the entire impluvium. Thus, the consideration of all the hydrological, morphometric and physical characteristics (topography, lithology, land cover...). In order to put in place appropriate measures to improve urban resilience and protect the population and their property in the capital of Algeria (City of Algiers), a hydrological modeling must be carried out upstream to evaluate the hydrological response of the watershed. This modeling was done using the auxiliary tool HEC-GEO HMS, an extension that works in a GIS environment (ArcGIS).

Desertification is a serious threat to human survival and to ecosystems, especially to inland desert oases. An assessment of desertification severity is essential to ensure national sustainable development for agricultural and land expansion processes in this region. In this study, Index of Land Susceptibility to Wind Erosion (ILSWE) was integrated with a Modified Mediterranean Desertification and Land Use (MEDALUS) method and factor analysis (FA) to develop a GIS-based model for mapping desertification severity. The model was then applied to 987.77 km2 in the El- Farafra Oasis, located in the Western Desert of Egypt, as a case study. Climate and field survey data together with remote sensing images were used to generate five quality indices (soil, climate, vegetation, land management and wind erosion). Based on the FA, a weighted value was assigned to each index. Five thematic layers representing the indices were created within the GIS environment and overlaid using the weighted sum model. The developed model showed that 59% of the total area was identified as high-critical and 38% as medium-critical. The results of an environmentally sensitive area index suggested by the original MEDALUS model indicated similar results: 18.37% of the total area was classified as high-critical and 78.73% as medium-critical. However, the sensitivity analysis indicated that weights derived from FA resulted in better performance of the developed spatial model than that derived from the original MEDALUS method. The proposed model would be a suitable tool for monitoring vulnerable zones, and could be a starting point for sustainable agricultural development in inland oases.

The main purpose of the paper is to explore the relationship between the CORINE Land Cover (CLC) classification and the MAES typology in order to develop a basis for mapping of ecosystems at national level in Bulgaria, which could ensure a spatial framework for mapping and assessment of the ecosystem services provided by the natural heritage. Identifying the necessary data for our purposes, we found that, in spatial terms, CLC data is the only appropriate data source. The subtypes of ecosystems at Level 3 of the classification of ecosystems in Bulgaria (based on the European MAES classification) are identified as mapping units. Firstly, we decided to analyze the links between the CLC and the MAES BG classes through five categories of correspondence: 1) full correspondence – one CLC class corresponds to one MAES BG subtype; 2) multi-directional links – one or more CLC classes correspond to one MAES BG subtype; 3) discrepancies that necessitate further analyses; 4) CLC classes that are not found in Bulgaria; 5) MAES BG subtypes that have no correspondence to a CLC class. Secondly, we prepared a comparison table to determine the correspondence between the CLC classes and ecosystem subtypes, which we integrated into the GIS environment. Thirdly, we developed an algorithm for modifications of the spatial distribution of ecosystem subtypes. The algorithm was applied particularly to grasslands, where at Level 3 of CLC there are two classes of "grassland”, whereas at Level 3 of the classification of ecosystems in Bulgaria, the subtypes are five. This algorithm was applied to the 2018 CLC spatial data so as to develop a GIS database providing the basis for subsequent analyzes related to ecosystems. The database was used to delineate and map the ecosystems at national level in Bulgaria. Furthermore, a map of the potential of the natural heritage to provide ecosystem services was produced.