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The satellite image data has some shortcomings such as poor timeless, incomplete disaster information and so on in the typhoon disaster analysis. Compared with the satellite image data, unmanned aerial vehicle (UAV) remote sensing technology has the characteristics of flexibility, convenience, high resolution and so on. It plays a great role in the aspect of obtaining the images and systematically analyze the disaster data. This research based on UAV technology to obtain the high resolution image data and complied the disaster thematic maps after interpretation, as well as determining the data model. Subsequently, determining the system used Html, Javascript and CSS to build the system framework. Combining with Postgre SQL database, Leaflet map module and Echarts diagram and other technologies to perform the feasibility analysis and the detailed design of the integrated system. Finally, it could accurately and comprehensively obtain the system’s disaster monitoring, the typhoon track display, the diagram statistics and visual analysis of the data processing, as well it could deeply analysis and management for the disaster information and assessment. The application shows that this system could provide the information support for future emergency rescue, which is of great significance for the monitoring and preventing the occurrence natural disasters in the future.

With the speeding up of urbanization process, ecological problems, such as unsustainable land use and environmental pollution,have emerged one after another in cites. Nowadays, green development and ecological priority are the important concepts and trends of the current new urban planning in China. In this study, Pingtan County, a coastal city in Fujian Province, China, was taken as the research area. Based on two Landsat 8 remote sensing images (2016, 2017), and two Sentinel-2A remote sensing images (2016, 2017), we first adopt the modified normalized water body index (MNDWI) to mask the water body. Four indicators, including greenness, humidity, dryness and heat were extracted to synthesize the remote sensing ecological index (RSEI), which were obtained by principal component analysis method. Based on the RSEI values acquired from Landsat 8 and Sentinel-2A images, the ecological environment change trend in Pingtan County was evaluated .The experimental results show that: 1) The RSEI indicators based on Landsat 8 and sentinel data all show a downward trend, but due to due to the influence of image spatial resolution and PCA weighting coefficient, the RSEI index has different degrees of decline. 2) The main reason for the decline in RSEI is the increase in NDSI indicators. Compared with July 2016, the bare ground increased in April 2017. Although the NDVI has increased, the overall trend is still declining. Therefore, it is necessary to ecologically return farmland and improve vegetation coverage in the future development process. 3) In recent years, the ecological quality of new construction land near drinking water sources has declined, so it is necessary to strengthen monitoring of changes in the region.

The power patrol has been completed by manual field investigation, which is inefficient, costly and unsafe. In order to extract the height of the power line and its surrounding ground objects more quickly and conveniently, and better service for power line patrol. This paper uses remote sensing data of unmanned aerial vehicle to carry out aerial triangulation, stereo model establishment and binocular stereo vision height extraction base on MapMatrix software, then obtains the power line height analysis chart. Then LiDAR point cloud data is used to verify the accuracy of the power line height analysis chart. The results show that this method not only meets the standard of power line patrol, but also improves the efficiency and quality of power line patrol.

The traditional electrical power line inspection method has the disadvantages of high labor intensity, low efficiency and long cycle of re-inspection. Airborne LiDAR can quickly obtain the high-precision three-dimensional spatial information of transmission line, and the data which collected by it can make it possible to accurately detect the dangerous points.It is proposed to use the grid method to divide the data into multiple regions for the elevation histogram statistical method to obtain the power line point cloud at the complex mountainous terrain. In the non-ground point data, part of the vegetation point cloud is separated according to the point cloud dimension feature, and then the power line point and the pole point are distinguished according to the density characteristics of the point cloud so as to realize the point cloud classification of the transmission line corridor. On this basis, the power line safety distance detection is carried out on the power line points and vegetation points extracted by the classification, and the early warning analysis of the dangerous points of the transmission line tree barrier is completed. The experimental results show that the method can classify the acquired power line corridor point cloud and extract the complete power line, which effectively eliminates the hidden dangers and has certain practical significance.

With the rapid development of the economy, the number of vehicles in China has increased rapidly, which has also brought about frequent ills in traffic accidents. How to improve the efficiency of on-site treatment of traffic accidents, and quickly and accurately conduct accident investigation and analysis is imminent. This paper was based on the point cloud to draw the accident scene DLG, and then used the local elevation difference method to automatically extract the point cloud data of the accident vehicle, and analyzes the vehicle speed calculation, the damage area measurement and the road surface flatness, as well as constructs the overall 3D scene of the accident scene. By analyzing the DLG of accident scene, the point cloud data and the constructed 3D model, which could quickly improve the efficiency of traffic accident investigation. The application results show that the method of information collection and rapid exploration of the accident site what based on the laser point cloud not only provides a basis for traffic accident treatment, but also effectively shortens the exploration time of accident site. At the same time, it cloud relieve the traffic congestion in a certain extent with the obvious results.

With the advent of the 5G era of digital smart city, “UAV + Application” is booming, and there is more and more demand for UAV remote sensing technology. How to cultivate high-tech application talents of UAV has become the primary problem to be solved in the development process of UAV. Based on WebGL technology, this paper combines virtual reality and panoramic technology, and adopts lightweight B/S architecture to develop an open platform for virtual simulation teaching that integrates online display, teaching, practical training, assessment, communication and management of UAV. The platform realizes the “three-dimensional teaching material, teaching platform, virtual exhibition hall” of the trinity teaching mode. Students can log in through the account to carry out theoretical learning, flight control operation learning and other interfaces, which can meet the training needs of high-tech application talents of UAV and strengthen students' understanding of theory and practice, simulation training has the advantages of repeated practice, without being limited by the space and time, and solve the problems of low interest, poor scalability and high cost of traditional UAV training.

Iron deficiency chlorosis occurs frequently in calcareous soils. The transformation of plants with ferric chelate reductase genes (FROs) provides a potential strategy to alleviate plant chlorosis under iron deficiency. A CjFRO2 gene isolated from Citrus junos Sieb. ex Tanaka was introduced into Poncirus trifoliata (L.) Raf via Agrobacterium-mediated transformation. The transgene integration and expression were confirmed by PCR, Southern blot, and real-time PCR analyses. Hydroponic- and soil-grown transgenic plants were tested for their tolerance to iron deficiency. Compared with nontransgenic (NT) P. trifoliata plants, a rhizosphere acidification capacity in the transgenic lines increased, and a ferric chelate reductase activity in roots was up to 3.39- and 2.93-fold higher in a hydroponic solution and soil, respectively. A transgenic line TO-8, which reacted similarly in hydroponics and soil, appeared tolerant to the iron deficiency. Its leaf chlorophyll and ferrous ion content was significantly higher than in NT. These results indicate that tolerance to the iron deficiency in P. trifoliata could be improved through the genetic engineering.