Urbanization has been linked to destructive geo-hazards that can cause loss of life, destruction of property, and environmental damage. On August 14, 2017, a devastating geo-hazard chain—a debris slide, debris flow, and sediment-laden flood—in Freetown, Sierra Leone resulted in at least 500 deaths and over 600 missing persons and the destruction of hundreds of houses. This study uses 10 years of high-resolution satellite images to conduct a remote sensing analysis of the disaster. Although rainfall was the trigger, rapid and haphazard urbanization acted to increase both hazard and vulnerability. Specifically, poor urban planning with inadequate consideration of risk led to housing construction in dangerous areas; clearance of hillside vegetation increased erosion potential; very low cost buildings using frail construction material and methods lacked resilience; and insufficient risk management led to weak emergency response.

Understanding disaster risk perception is vital for community-based disaster risk reduction (DRR). This study was set to investigate the correlations between disaster risk perception and the population at risk. To address this research question, the current study conducted an interdisciplinary approach: a household survey for measuring variables and constructed an Agent-based model for simulating the population at risk. Therefore, two correlations were defined, (1) between risk perception and willingness to evacuate, and (2) between willingness to evacuate and the population at risk. The willingness to evacuate was adopted as a mediator to determine the relationship between risk perception and the population at risk. The results show that the residents generally have a higher risk perception and willingness to evacuate because the study area frequently suffered from debris flow and flash floods. A positive correlation was found between risk perception and willingness to evacuate, and a negative correlation to the population at risk. However, a marginal effect was observed when raising public risk perception to reduce the number of the population at risk. This study provides an interdisciplinary approach to measuring disaster risk perception at the community level and helps policymakers select the most effective ways to reduce the population at risk.

Against the backdrop of intensifying global climate change, the impact of land use pattern changes on ecosystem vulnerability has garnered increasing attention. However, systematic studies concerning the ecological vulnerability of mountainous regions remains inadequate, with relevant policies primarily remaining at the macro-regulation level and lacking specific guidance measures. Taking Heishui County in southwest China as a case study, this research innovatively combines landscape pattern with the sensitivity–pressure–resilience (SPR) model to systematically analyze land use spatiotemporal evolution characteristics, ecological vulnerability and spatial differentiation patterns, and their driving mechanisms across multiple scales, including county, township, and land use types. The findings reveal that the region’s ecological vulnerability exhibits a spatial distribution pattern of “high in the southeast and low in the northwest”, with a radiating decrease from the centers of Longba and Weigu towns. The high degree of farmland landscape fragmentation is identified as a crucial factor contributing to its heightened ecological vulnerability. Geological disasters, human activities, meteorological conditions, and topographical features are the primary driving factors affecting ecological vulnerability intensity. Furthermore, land use pattern changes, characterized by landscape patch fragmentation, lack of dominant patch types, and decreased landscape diversity have further intensified regional ecological vulnerability. This research holds significant theoretical and practical implications for guiding ecological environmental governance in mountainous regions, enhancing ecological resilience, and promoting regional sustainable development.

Earthquakes–induced landslides generally provide abundant loose materials at hillslopes, possibly triggering morphological reshaping processes at river channels and riverbeds during the large flash flood hydrograph and bringing huge risk downstream. Therefore, in a Wenchuan earthquake-affected catchment, the collected hydro-meteorological data and high-precision small Unmanned Aerial Vehicle (sUAV) data were used to quantitatively analyze channel evolution by a large flash flood event on 25 and 26 June 2018. It was found that the stable riverbed structure formed by the armour layer appeared in the tenth year after the Wenchuan earthquake. In a confined channel, the layer can protect the channel and resist the drastic change after the flash flood event with only a small bed elevation from 0.2 m to 2 m. Without the protection of the armour, the change could reach 6 m in the unconfined channel. Meanwhile, more materials with a deposition volume of about 7450 m³ from tributaries were generally taken to the main channel, and more intense erosion with a volume of 10⁵ m³ mostly occurred downstream of tributaries. It was noted that, in the cross-section, the increased channel width could lead to a significant change with the large volume of 35 m³. Additionally, a conceptual diagram of the generalized channel response to large flash floods was provided during multi-stage periods after the Wenchuan earthquake. It determined the rebalance processes of channel evolution in the tenth year after the earthquake. This study will contribute to understanding the post-earthquake long-term channel evolutions and could provide decision-makers of assessing the mitigation strategies for higher-magnitude flood disasters triggered by channel change in earthquake-affected watersheds.