Geomorphological Mapping Global Trends and Applications

Quesada-Román, Adolfo; Peralta-Reyes, Manuel

doi:10.3390/geographies3030032

Cited by 19 publications

(4 citation statements)

References 37 publications

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“…Although detailed landscape and geomorphological mapping are useful tools for land use and disaster risk planning, such efforts in Central America are very scarce [40][41][42][43][44][45]. Therefore, geomorphological mapping presents a very important part of this study, which gives insight into the geomorphological characteristics of the studied karstic area.…”

Section: Geomorphological Mappingmentioning

confidence: 99%

Past and Present Drivers of Karst Formation of Ciénega de El Mangle, Panama

Rivera-Solís,

Quesada-Román,

Domazetović

2023

Quaternary

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Tropical coastal karst areas represent dynamic, fragile, and biodiverse environments. Central America’s karst regions have been scarcely studied, with most of the research focused on the northern part of the region and on several larger cave systems. The coastal carbonate zones of the Central American region represent a unique karstic landscape, which, so far, has been insufficiently studied. Therefore, in this paper, we aim to describe the (i) landscape geomorphology and (ii) chemical conditions that define Ciénega de El Mangle in Panama as a distinctive karstic site. Carried geomorphological mapping and the characterization of karstic features have resulted in the identification of the different karstic forms and processes that are present within this unique karstic area. Considering that the chosen karstic study area is located in a marine–coastal fringe on the periphery of a lagoon, it is affected by a combination of several factors and processes, including seawater intrusion (through sinkholes), the formation of conchiferous limestone (CaCO3), and NaCl precipitation related to efflorescence. Due to the seasonally humid tropical climate, the chemical weathering processes are intense, thus forming alkaline soils that are hindering the development of mangrove vegetation. The geomorphology of the area results from intense evaporation combined with an influx of brackish groundwater, due to which a landscape has evolved in the marine–coastal strips, of seasonal tropical climates, that exhibit saline beaches, known as a littoral shott. In total, 24 karstic microdolines have evolved within the shott, of which six represent domical geoforms formed by gradual evaporitic precipitation, while seven other geoforms represent active karstic sinkholes filled with brackish water. These results are key for understanding the past and present climate interactions and conditions that have led to the formation of tropical karst environments.

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Section: Geomorphological Mappingmentioning

confidence: 99%

Past and Present Drivers of Karst Formation of Ciénega de El Mangle, Panama

Rivera-Solís,

Quesada-Román,

Domazetović

2023

Quaternary

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“…Recent studies have emphasized the importance of mapping urban geomorphological forms and features as well as geoheritage, revealing the intricate interplay between natural processes, human actions, and urban growth [9,[25][26][27][28]. Geomorphological mapping utilizes various techniques to capture the dynamic interplay among geological forces, climatic factors, and surface processes [29].…”

Section: Introductionmentioning

confidence: 99%

Nature-Based Solution Integration to Enhance Urban Geomorphological Mapping: A Methodological Approach

Hamidova,

Bosino,

Franceschi

et al. 2024

Land

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This study conducted an extensive literature review spanning from 1950 to 2023, exploring the methodologies in urban geomorphology and urban geoheritage assessment, and the possibility of applying Nature-Based Solutions (NbSs) in order to enhance geomorphological maps. The methodology proposed here is based on a two-step approach: (i) a bibliographic review and methodological investigation and (ii) methodological proposal in order to enhance the traditional geomorphological and geoheritage maps with NbS to reduce the geomorphological risk in urban areas. This paper aims to introduce a methodological framework and illustrated its practical application to provide researchers and practitioners with a clear understanding of its implementation in real-world scenarios. The proposed methodology was applied in the north and northeastern parts of Milan, Italy. The implementation of the proposed methodology demonstrated its effectiveness in urban contexts and its potential for further modification and extension to various urban environments in the future.

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“…However, in the study of climate-human-environment interactions [6], they play a crucial role in researching climate change, investigating hydrological resources, and issuing snow disaster warnings [7]. Due to the close radiation temperatures and similar properties in the optical wavelengths of snow and clouds, distinguishing between the two during detection tasks is challenging [8].…”

Section: Introductionmentioning

confidence: 99%

Multi-Level Attention Interactive Network for Cloud and Snow Detection Segmentation

Ding,

Xia,

Lin

et al. 2023

Remote Sensing

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The ground is typically hidden by cloud and snow in satellite images, which have a similar visible spectrum and complex spatial distribution characteristics. The detection of cloud and snow is important for increasing image availability and studying climate change. To address the issues of the low classification accuracy and poor generalization effect by the traditional threshold method, as well as the problems of the misdetection of overlapping regions, rough segmentation results, and a loss of boundary details in existing algorithms, this paper designed a Multi-level Attention Interaction Network (MAINet). The MAINet uses a modified ResNet50 to extract features and introduces a Detail Feature Extraction module to extract multi-level information and reduce the loss of details. In the last down-sampling, the Deep Multi-head Information Enhancement module combines a CNN and a Transformer structure to make deep semantic features more distinct and reduce redundant information. Then, the Feature Interactive and Fusion Up-sampling module enhances the information extraction of deep and shallow information and, then, guides and aggregates each to make the learned semantic features more comprehensive, which can better recover remote sensing images and increase the prediction accuracy. The MAINet model we propose performed satisfactorily in handling cloud and snow detection and segmentation tasks in multiple scenarios. Experiments on related data sets also showed that the MAINet algorithm exhibited the best performance.

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Geomorphological Mapping Global Trends and Applications

Cited by 19 publications

References 37 publications

Past and Present Drivers of Karst Formation of Ciénega de El Mangle, Panama

Past and Present Drivers of Karst Formation of Ciénega de El Mangle, Panama

Nature-Based Solution Integration to Enhance Urban Geomorphological Mapping: A Methodological Approach

Multi-Level Attention Interactive Network for Cloud and Snow Detection Segmentation

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