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.

A rainfall-induced compound disaster happened in Mocoa in the pre-dawn hours of 1 April 2017. More than 300 people were killed, and a large number of houses and roads were destroyed in the worst catastrophe in the history of Mocoa. To investigate this disaster, a detailed interpretation was carried out using high-resolution images. Analysis of disaster characteristics based on satellite image revealed that the disaster could be identified as a consequence of compound mountain hazards including landslides, debris flows, and mountain torrents. The mountain hazards converged in the mountain watershed, which amplified the disaster’s effects. Analysis considers that this disaster is the result of heavy rainfalls. Moreover, in-depth interpretation of rainfall data and satellite images spanning over 16 years reveals that the previous El Niño event (2014–2016) also played an important role, which caused reduced rainfall and vegetation coverage. The long period of drought brought by El Niño affected the growth of vegetation and reduced the ability of vegetation to cope with heavy rainfalls. The results reveal that both antecedent rainfalls and climate impact need to be taken into consideration for mountain hazard analysis.

To solve the decline of rural development, an effective development mode is indispensable. Rural tourism is a key approach in poverty alleviation and rural revitalization in China. The comparative analysis of the 50 most beautiful villages as awarded by the Ministry of Agriculture of China shows that the rural tourism development mode with the integration of production, village and scenery realizes the sustainable development of rural areas. To examine this further, this study takes Qinggangshu Village as a case study and constructs a systematic rural tourism-based sustainable development model called Aims, Measures, Demands (AMD). The results show that Qinggangshu Village has changed from a single farming village to a mature tourism village due to the Beautiful Village Project’s support. In this process, the production, village and scenery have made great change by promoting rural tourism development. Land consolidation and land asset activation is at the core of rural transformation and development, which can drive the reorganization and flow of labor and capital and can also make rebuilt villages more comfortable living spaces. Furthermore, a good landscape environment can stimulate development and competition. This study could be used as an example of attaining sustainable development for other rural areas.

A catastrophic tailings dam failure disaster occurred in Brumadinho, Brazil on 25 January 2019, which resulted in over 270 casualties, 24,000 residents evacuated, and a huge economic loss. Environmental concerns were raised for the potential pollution of water due to tailings waste entering the Paraopeba River. In this paper, a detailed analysis has been carried out to investigate the disaster conditions of the Brumadinho dam failure using satellite images with different spatial resolutions. Our in-depth analysis reveals that the hazard chain caused by this failure contained three stages, namely dam failure, mudflow, and the hyperconcentrated flow in the Paraopeba River. The variation characteristics of turbidity of the Rio Paraopeba River after the disaster have also been investigated using high-resolution remote sensing images, followed by a qualitative analysis of the impacts on the downstream reservoir of the Retiro Baixo Plant that was over 300 km away from the dam failure origin. It is believed that, on the one hand, the lack of dam stability management at the maintenance stage was the main cause of this disaster. On the other hand, the abundant antecedent precipitation caused by extreme weather events should be a critical triggering factor. Furthermore, the spatiotemporal pattern mining of global tailings dam failures revealed that the Brumadinho dam disaster belonged to a Consecutive Hot Spot area, suggesting that the regular drainage inspection, risk assessment, monitoring, and early warning of tailings dam in Consecutive Hot Spot areas still need to be strengthened for disaster mitigation.

Debris flows in a burned area, post-fire debris flows, are considered as one of the most dangerous geo-hazards due to their high velocity, long run-out distance, and huge destruction to infrastructures. The rainfall threshold to trigger such hazards is often reduced compared with normal debris flow because ashes generated by mountain fires reduce the permeability of the top soil layer, thus increasing surface runoff. At the same time, burnt material and residual debris have very poor geo-mechanical characteristics, e.g., their internal friction angle and cohesion are typically low, and thus an intense rainfall can easily trigger some debris flows. Studying post-fire debris flow enables us to get a deeper understanding of disaster management. In this paper, the debris flow that occurred in Montecito, California, USA, and was affected by the Thomas Fire was used as a case study. Five major watersheds were extracted based on the digital elevation model (DEM). Remote sensing images were used to analyze the wildfire process, the extent of the burned areas, and the burn severity. The hypsometric integral (HI) and short-duration rainfall records of the watersheds around Montecito when the post-fire debris flows occurred were analyzed. Steep terrain, loose and abundant deposits, and sufficient water supply are the important conditions affecting the formation of debris flows. Taking watersheds as the research objects, HI was used to describe the geomorphic and topographic features, open-access rainfall data was used to represent the water supply, and burn severity represented the abundance of material sources. An occurrence probability model of post-fire debris flow based on HI, short-duration heavy rainfall, and burn severity was developed by using a logistic regression model in post-fire areas. By using this model, the occurrence probability of the post-fire debris flow in different watersheds around Montecito was analyzed based on the precipitation with time. Especially, the change characteristics of occurrence probability of debris flows over time based on the model bring a new perspective to observe the obvious change of the danger of post-fire debris flows and it is very useful for early warning of post-fire debris flows.

The study of land use/land cover (LULC) changes plays an important guiding role in regional ecological protection and sustainable development policy formulation. Especially, the simulation study of the future scenarios may provide a hypothetical prospect which could help to determine the rationality of current and future development policies. In order to support the ecological protection and high-quality development strategy of the Yellow River Basin proposed by the Chinese government, the Great Yellow River Region (GYRR) is taken as the research area. The multi-period land cover data are used to carry out the analysis of land cover changes. The MOLUSCE (Modules for Land Use Change Simulations) plugin of QGIS software is used to carry out a land cover simulation and prediction study for 2030 on a large regional scale. Finally, the land cover status in the mountainous areas of the GYRR is analyzed thoroughly. The results show a decrease in agricultural land and increase in forest land during the past 25 years from 1995 to 2020, and that this trend would continue to 2030. The landscape pattern index analysis indicates that the land cover in the GYRR has become more and more abundant, and the degree of fragmentation has become higher and higher, while landscape patches were more evenly distributed in the GYRR until 2020. On the other hand, the landscape pattern would tend to achieve a certain degree of stability in 2030. The decrease in farmland and the increase in forest land illustrate the efforts made by the GYRR residents and governments in improving the ecological environment under the policy of returning farmland to forests and grasslands. On the other hand, although the residential areas in the mountainous areas are far away from the mountain hazard historical points because of consideration during construction with the help of the development of disaster prevention and mitigation over the years, there could be problem of rapid and haphazard urbanization. It is worth mentioning here that the harmonious and sustainable development of people and land in the GYRR mountainous areas still requires a large amount of effort.