Sediment transport rate, as an important indicator for studying Earth surface processes and for planning soil and water conservation, is a spatial variable. However, traditional monitoring methods can only obtain the global sediment transport rate in a certain area and are unable to map the spatial distribution of sediment transport rate. In this study, unmanned aerial vehicle (UAV) photogrammetry was used to obtain a two-phase digital elevation model (DEM) and calculate the amount of topographic change. In accordance with the principle of mass conservation and using a multi-flow direction algorithm, a spatial sediment transport model was established, by which the spatial sediment transport rate from a loess watershed was obtained. The results show that this method can effectively simulate the transportation of sediment in space. The area where the mass is not conserved is less than 4%, and the non-conserved areas are mostly those that are affected by human activities. The effects of DEM choice and the level of topographic change detection on the proposed model are also discussed. When DEM in the first phase is used to calculate the sediment transportation path, the area where the mass is not conserved is significantly reduced. The results of the spatial sediment transport model are more robust when a precision map is used to detect topographic changes, whereas the results from topographic changes detected by root mean square error (RMSE) greatly varied under different confidence levels. The proposed model can conveniently and quickly provide a detailed spatial distribution of sediment transport rate through UAV-based topographic change detection, which provides new perspectives for research of Earth surface processes.

With the rapid development of civilian unmanned aerial vehicle (UAV) technology, UAV aerial photography has become an important data source for urban image perception research. Based on the photos, text introduction, shooting location, and related data of UAVs photos of Xi'an City obtained from the social media platform SkyPixel, this study used computer vision analysis, computer text emotion analysis, social network analysis, and GIS spatial analysis to explore the city image of Xi'an from the perspective of UAV. The research results show that: 1) UAV aerial photography photos are mainly concentrated in the main urban areas, and there are fewer aerial data points in the suburb. The spatial distribution of photos presents a pattern of dense inside and sparse outside, with the highest density area in the center of the city at the junction zone of the three districts, showing a dumbbell-type distribution extending from the north to south. 2) The visual images are mostly of modern urban landscape description, of which the content of human landscape is dominant. 3) Emotion evaluation presents an overall positive feeling, and the polarization of the popular tourist attractions is obvious in the main urban area. Finally, this study explored the mechanism of city image formation and promotion from the perspective of UAV, and provided recommendations for the optimization of Xi'an city image construction and UAV use policy.

Unmanned aerial vehicle (UAV) is a flexible and efficient platform to accurately obtain high-resolution and multi-source remote sensing data in low altitude airspace. It can provide important information for industrial applications and management decisions. With the arrival of the big-data era, both the hardware and software for acquiring and processing UAV remote sensing data stepped into a fast lane. The enormous amount of data has brought unprecedented opportunities and challenges for UAV remote sensing and industrial applications. In this article, we introduced the history and advances in UAV remote sensing hardware development. The UAVs mounted with lightweight, high-precision, standardized, and integrated sensors would be the future direction of UAV remote sensing hardware development. Then, we summarized the current status of applications in agriculture, forestry and prataculture, surveying, geological hazard monitoring and disaster management, electricity sector, and atmospheric monitoring using UAV remote sensing. The integrated UAV remote sensing platforms equipped with multi-sensors are one of the keys for such applications. Finally, we discussed the intelligent UAV hardware, network operation potential, massive data processing capability, automatic information extraction technique, and future directions in UAV remote sensing. The popularization and standardization of UAV remote sensing application in various industries will largely improve and accelerate national and regional social and economic development.

The glaciers of the Meili Snow Mountain are now rapidly retreating and thinning, owing to climate change. The main aim of this study was to monitor the dynamics of the Mingyong Glacier in the Meili Snow Mountain based on unmanned aerial vehicle (UAV) survey and UBase. The result of the digital surface model (DSM) in the Mingyong Glacier terminus shows that the surface morphology has a significant difference between the upper and lower sections. The lower section was covered by a large amount of debris, and a few crevasses developed along the direction of glacier flow. Little debris was found in the upper section, and a lot of transverse crevasses developed there. A mean ice thinning of 1.67 m was observed in the terminus of the Mingyong Glacier from November 2018 to November 2019, and surface lowering was heterogeneous. There were positive and negative alternations in surface lowering in the upper section, surface thinning was observed in the middle section, while a significant thickening was observed in the lower section. Compared with glacier changes in other areas in the High Asia Mountains, the Meili Snow Mountain was the region with the most significant glacier surface elevation change.

In recent years, unmanned aerial vehicle (UAV) technology has experienced a great improvement. Due to its flexibility and super-high resolution, UAV has a great development potential in the field of glacier change monitoring. In this study, three UAV surveys were conducted, for the first time above 5400 m altitude, at the Xiao Dongkemadi Glacier, which is located in the Tanggula Mountains on the central Tibetan Plateau. Three UAV products were co-registered based on the reference points of bedrocks around the glacier. Then, we analyzed the ablation pattern of the glacier in a year of balance and ablation season, and further explored the application of UAV in glacier change monitoring and discussed the problems we met, as well as advantages of UAV, to provide some guidance for future research. Our results show that the UAV technology is suitable for the change monitoring in a single and small glacier. It can be used to monitor glacier changes in terminal, area, surface elevation, and detail glacier features.