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As the core area of human activities and economic development in the Xinjiang Autonomous Region, the hilly oasis zone of Xinjiang directly affects the regional sustainable development and stability of the ecosystem. Understanding the effects of different geomorphic types on vegetation distribution is crucial for maintaining vegetation growth and development, especially the improvement in the terrestrial ecological environment in arid areas under the background of climate change. However, there are few studies on the effect of spatial differences in detailed geomorphic types on vegetation distribution patterns. Therefore, this paper divides the Xinjiang hilly oasis zone into six geomorphologic level zones and innovatively investigates the influence of detailed geomorphologic types on the spatial distribution of vegetation and vegetation cover. Further, the area proportion of detailed landform types corresponding to different vegetation coverage in each geomorphic area was quantitatively calculated. Finally, the Geodetector method was used to detect the drivers of interactions between vegetation and the environment. The findings are shown as follows: (1) In the same climate zone, the spatial differentiation of landforms has a great influence on the vegetation distribution, manifesting as the significantly different vegetation distribution in different landform types. Grassland is the main vegetation type in the erosion and denudation of Nakayama; cultivated vegetation and meadows have a larger coverage in the alluvial flood plain and alluvial plain; and the distribution of vegetation in the Tianshan economic zone is characterized by obvious vertical zoning with the geomorphology. (2) The landform type and morphological types are the strongest driving factors for vegetation coverage with q values of 0.433 and 0.295, respectively, which effectually fill the gap caused by only using two terrain indicators, slope and elevation, to study the relationship between landforms and vegetation. (3) In addition, the improved nonlinear interaction resulting from the double factor of landform type and slope is 0.486, which has a stronger control on vegetation coverage than the single factor of landform type. These findings are conducive to enhancing the supply services of vegetation to the ecosystem in arid areas as well as providing important scientific guidance for the construction of ecological civilization and sustainable development in Xinjiang. [ABSTRACT FROM AUTHOR]

In rockfall hazard management, the investigation and detection of potential rockfall source areas on rock cliffs by remote-sensing-based susceptibility analysis are of primary importance. However, when the rockfall analysis results are used as feedback to the fieldwork, the irregular slope surface morphology makes it difficult to objectively locate the risk zones of hazard maps on the real slopes, and the problem of straightforward on-site visualization of rockfall susceptibility remains a research gap. This paper presents some of the pioneering studies on the augmented reality (AR) mapping of geospatial information from cyberspace within 2D screens to the physical world for on-site visualization, which directly recognizes the rock mass and superimposes corresponding rock discontinuities and rockfall susceptibility onto the real slopes. A novel method of edge-based tracking of the rock mass target for mobile AR is proposed, where the model edges extracted from unmanned aerial vehicle (UAV) structure-from-motion (SfM) 3D reconstructions are aligned with the corresponding actual rock mass to estimate the camera pose accurately. Specifically, the visually prominent edges of dominant structural planes were first explored and discovered to be a robust visual feature of rock mass for AR tracking. The novel approaches of visual-geometric synthetic image (VGSI) and prominent structural plane (Pro-SP) were developed to extract structural planes with identified prominent edges as 3D template models which could provide a pose estimation reference. An experiment verified that the proposed Pro-SP template model could effectively improve the edge tracking performance and quality, and this approach was relatively robust to the changes of sunlight conditions. A case study was carried out on a typical roadcut cliff in the Mentougou District of Beijing, China. The results validate the scalability of the proposed mobile AR strategy, which is applicable and suitable for cliff-scale fieldwork. The results also demonstrate the feasibility, efficiency, and significance of the geoinformation AR mapping methodology for on-site zoning and locating of potential rockfalls, and providing relevant guidance for subsequent detailed site investigation. [ABSTRACT FROM AUTHOR]