Landslide increasingly affect urban areas and transport infrastructure, due to rapid urbanization, climate change, and complex hydrogeological conditions. Anthropogenic activity associated with construction of housing, roads, and drainage systems modify surface water runoff and subsurface hydrology, strongly affecting slope stability [1]. Rapid urban development, especially in developing countries, results in unregulated buildings and poor or non-existing water drainage and water leakages, which cause in widespread slope instability under intense rainfall [2].
Landslide susceptibility maps based on statistical models may be ineffective at the urban scale. Physically based approaches may be suitable for including local anthropic changes and predicting slope stability in urban areas and along transportation routes [3]. They are specialized to landslide type, including reach distance and runoff, and take into account time-dependent triggering conditions [4, 5].
Numerical models can combine rain infiltration with measured rainfall, soil moisture and soil suction, local anthropic changes on the terrain, and may lead to effective early warning systems in urban areas [3, 6]. These considerations apply both to urban areas and transport routes, characterized by local and continued anthropic changes.
We invite contributions that explore:
(1) application of physically based models to landslides affecting urban areas and transport infrastructure, including but not limited to soil mechanics, hydrology, and geotechnical engineering;
(2) detection and monitoring of ground movements specialized for urban areas and transport routes, including the use of remote sensing technologies as well as ground-based techniques, and their integration with GIS and data analytics to provide real-time monitoring and early warning systems.
(3) effects of urban sprawl for slope stability, including interdisciplinary approaches, novel methodologies, and practical implementations in rapidly growing urban areas.
References
[1] Dille et al., Nature Geosci. (2022). DOI: 10.1038/s41561-022-01073-3
[2] Ozturk et al., Nature (2022). DOI: 10.1038/d41586-022-02141-9
[3] Bozzolan et al., Sci. Tot. Env. (2023). DOI: 10.1016/j.scitotenv.2022.159412
[4] Alvioli et al., Eng. Geol. (2021). DOI: 10.1016/j.enggeo.2021.106301
[5] Marchesini et al., Eng. Geol. (2024). DOI: 10.1016/j.enggeo.2024.107474
[6] Mendes et al., Geotech. Geol. Eng. (2017). DOI: 10.1007/s10706-017-0303-z
Landslide susceptibility maps based on statistical models may be ineffective at the urban scale. Physically based approaches may be suitable for including local anthropic changes and predicting slope stability in urban areas and along transportation routes [3]. They are specialized to landslide type, including reach distance and runoff, and take into account time-dependent triggering conditions [4, 5].
Numerical models can combine rain infiltration with measured rainfall, soil moisture and soil suction, local anthropic changes on the terrain, and may lead to effective early warning systems in urban areas [3, 6]. These considerations apply both to urban areas and transport routes, characterized by local and continued anthropic changes.
We invite contributions that explore:
(1) application of physically based models to landslides affecting urban areas and transport infrastructure, including but not limited to soil mechanics, hydrology, and geotechnical engineering;
(2) detection and monitoring of ground movements specialized for urban areas and transport routes, including the use of remote sensing technologies as well as ground-based techniques, and their integration with GIS and data analytics to provide real-time monitoring and early warning systems.
(3) effects of urban sprawl for slope stability, including interdisciplinary approaches, novel methodologies, and practical implementations in rapidly growing urban areas.
References
[1] Dille et al., Nature Geosci. (2022). DOI: 10.1038/s41561-022-01073-3
[2] Ozturk et al., Nature (2022). DOI: 10.1038/d41586-022-02141-9
[3] Bozzolan et al., Sci. Tot. Env. (2023). DOI: 10.1016/j.scitotenv.2022.159412
[4] Alvioli et al., Eng. Geol. (2021). DOI: 10.1016/j.enggeo.2021.106301
[5] Marchesini et al., Eng. Geol. (2024). DOI: 10.1016/j.enggeo.2024.107474
[6] Mendes et al., Geotech. Geol. Eng. (2017). DOI: 10.1007/s10706-017-0303-z