The deformation characteristics and instability patterns of rotational landslides are complicated. Such landslides are large and occur continuously, seriously threatening people’s lives. We used interferometry synthetic aperture radar (InSAR), digital elevation models of difference (DODs), numerical simulations, and other techniques for analyzing the topographic changes, surface deformation and movement process before, during and after a landslide. Based on the high-resolution terrain data before and after the landslide, the topographic changes were analyzed, and the active zone of the landslide was identified. The areas of the topographic changes were mainly located on the main scarp, toe and secondary landslides. The topographic changes were influenced by rainfall and rill erosion. The geomorphologically-guided InSAR interpretation method was applied to explore the displacement pattern. The deformation area in the middle of the landslide coincided with the secondary landslides. A time-series InSAR analysis revealed the dynamic evolution of the deformation before and after the landslide. Based on its evolution, the simulated landslide process included the main landslide and three secondary landslides. Based on the displacement of the longitudinal ground surface profiles, the displacement characteristics and kinematic behavior were summarized and compared with those of a single rotational landslide and multiple rotational landslides. The single rotational landslide had obvious secondary and progressive characteristics, developing into multiple rotational landslides triggered by conditions such as rainfall.

Landslide processes are a consequence of the interactions between their triggers and the surrounding environment. Understanding the differences in landslide movement processes and characteristics can provide new insights for landslide prevention and mitigation. Three adjacent landslides characterized by different movement processes were triggered from August to September in 2018 in Hualong County, China. A combination of surface and subsurface characteristics illustrated that Xiongwa (XW) landslides 1 and 2 have deformed several times and exhibit significant heterogeneity, whereas the Xiashitang (XST) landslide is a typical retrogressive landslide, and its material has moved downslope along a shear surface. Time-series Interferometric Synthetic Aperture Radar (InSAR) and Differential InSAR (DInSAR) techniques were used to detect the displacement processes of these three landslides. The pre-failure displacement signals of a slow-moving landslide (the XST landslide) can be clearly revealed by using time-series InSAR. However, these sudden landslides, which are a typical catastrophic natural hazard across the globe, are easily ignored by time-series InSAR. We confirmed that effective antecedent precipitation played an important role in the three landslides’ occurrence. The deformation of an existing landslide itself can also trigger new adjacent landslides in this study. These findings indicate that landslide early warnings are still a challenge since landslide processes and mechanisms are complicated. We need to learn to live with natural disasters, and more relevant detection and field investigations should be conducted for landslide risk mitigation.

This study investigates the antecedents of environmentally responsible behaviour by creating a theoretical model of relationships between service quality, place attachment and environmentally responsible behaviour. A questionnaire survey was conducted among tourists who visited six famous tourist attractions in Shaanxi, China. The results of the research demonstrate that service quality exerts influence on environmentally responsible behaviour and place attachment in a positive manner. Additionally, the findings suggest that place attachment affects environmentally responsible behaviour in a direct and positive manner. Moreover, it is also found that service quality strengthens its effect on environmentally responsible behaviour through place attachment, indicating the mediating role of place attachment in the link between service quality and environmentally responsible behaviour. The current research contributes to tourism literature in that it helps to better understand the tourists’ environmentally responsible behaviour and provides management with evidence of the significance for improving the service quality at tourist attractions.

Vegetation indicators and spatial distribution characteristics are the core and basis to study the complex human-natural coupled system. In this paper, with Landsat 5 and Landsat 8 remote sensing data, we quantitatively estimated vegetation coverage in Henan Province, China. According to the urbanization rate, altitude, slope degree, and slope exposure, we analyzed spatial and temporal variation laws of vegetation coverage under the action of different factors to provide a reference for the improvement of the ecological environment and the quality assessment of Chinese granary. From 2000 to 2013, the vegetation coverage in Henan Province declined by 30.49% and the ecological environment deteriorated. The spatial change of vegetation coverage was evenly distributed in Henan Province. The vegetation coverage was increased in the west, south, and southwest parts of Henan Province and slightly decreased in the central, east, and the eastern part of Taihang Mountain. Vegetation coverage in a city was related to its population urbanization rate. The population urbanization rate was often negatively correlated with the vegetation coverage. According to the results of terrain factors based analysis, the low-altitude areas were in a good vegetation cover condition with the high vegetation coverage grade; the areas with a smaller slope degree had the large vegetation coverage and the coverage decreased with the increase in the slope degree; the coverage showed no significant difference between sunny and shady slopes and was less limited by light, temperature, and humidity.

Stellera chamaejasme L. (S. chamaejasme) is one of the primary toxic grass species (poisonous plants) distributed in the alpine meadows of Qinghai Province, China. In this study, according to the distinctive phenological characteristics of S. chamaejasme, the spectral differences between S. chamaejasme in the full-bloom stage and other pasture grasses were analyzed and the red, blue, and near-infrared bands of IKONOS image were determined as the diagnostic bands of S. chamaejasme recognition. Feature indexes related to S. chamaejasme were established using the diagnostic bands, and \(NDVI_{blue} = (\rho_{nir} − \rho_{blue})/(\rho_{nir} + \rho_{blue})\) obtained as S. chamaejasme sensitive index based on the linear regression analysis between the indexes derived from field spectra and the actual cover fraction of S. chamaejasme communities. The distribution area of S. chamaejasme was extracted by using the index \(NDVI_{blue}\) derived from IKONOS multispectral image in Qilian County of Qinghai Province, China and the verified result reached an overall accuracy of 90.71%. The study indicated that high resolution multispectral satellite images (such as IKONOS images) had significant potential in remote sensing recognition of toxic grass species.