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| 1 | Iterative construction of low-altitude UAV air route network in urban areas:Case planning and assessment显示文摘With the rapid increase of Unmanned Aircraft Vehicle(UAV) numbers,the contradiction between extensive flight demands and limited low-altitude airspace resources has become increasingly prominent.To ensure the safety and efficiency of low-altitude UAV operations,the low-altitude UAV public air route creatively proposed by the Chinese Academy of Sciences(CAS) and supported by the Civil Aviation Administration of China(CAAC) has been gradually recognized.However,present planning research on UAV low-altitude air route is not enough to explore how to use the ground transportation infrastructure,how to closely combine the surface pattern characteristics,and how to form the mechanism of 'network'.Based on the solution proposed in the early stage and related researches,this paper further deepens the exploration of the low-altitude public air route network and the implementation of key technologies and steps with an actual case study in Tianjin,China.Firstly,a path-planning environment consisting of favorable spaces,obstacle spaces,and mobile communication spaces for UAV flights was pre-constructed.Subsequently,air routes were planned by using the conflict detection and path re-planning algorithm.Our study also assessed the network by computing the population exposure risk index(PERI) and found that the index value was greatly reduced after the construction of the network,indicating that the network can effectively reduce the operational risk.In this study,a low-altitude UAV air route network in an actual region was constructed using multidisciplinary approaches such as remote sensing,geographic information,aviation,and transportation;it indirectly verified the rationality of the outcomes.This can provide practical solutions to low-altitude traffic problems in urban areas. | XU Chenchen LIAO Xiaohan YE Huping YUE Huanyin | 2020 | Journal of Geographical Sciences2020，30，9： | 2 |
| 2 | Launching an unmanned aerial vehicle remote sensing data carrier:concept,key components and prospects显示文摘Unmanned aerial vehicles(UAV)based remote sensing is an emerging and important data source.Recently,the use of UAVs for remote sensing applications has been rapidly growing owing to their greater availability and the miniaturization of sensors.UAVs are surpassing satellites and aircraft in remote sensing data supply for many local requirements.In comparison with satellite remote sensing data,most UAV remote sensing data is characterized by high resolution,small coverage area,and heterogeneous multi-sources.However,UAVs lack a unified space–time framework and standardized data process.This paper describes a UAV remote sensing data carrier that can be used as an e-commerce platform for data sharing among registered members and a mission planner for new data acquisition.To the best of our knowledge,the data carriers described herein,are the first of their kind.Through seamless docking with UAVs,the data carrier will form a national UAV network,capable of dynamically obtaining very-high-resolution UAV remote sensing images.In practice,a pilot retrieval system of UAV meta data has been developed to provide a catalogue of data product services. | Xiaohan Liao Huanyin Yue Ronggao Liu Xiangyong Luo Bin Luo Ming Lu Barbara Ryan Huping Ye | 2020 | International Journal of Digital Earth2020，13，10： | 2 |
| 3 | Gaussian decomposition and component pigment spectral analysis of phytoplankton absorption spectra显示文摘The absorption spectrum of phytoplankton is an important bio-optical parameter for ocean color hyperspectral remote sensing;its magnitude and shape can be aff ected considerably by pigment composition and concentration. We conducted Gaussian decomposition to the absorption spectra of phytoplankton pigment and studied the spectral components of the phytoplankton, in which the package effect was investigated using pigment concentration data and phytoplankton absorption spectra. The decomposition results were compared with the corresponding concentrations of the five main pigment groups (chlorophylls a , b , and c , photo-synthetic carotenoids (PSC), and photo-protective carotenoids (PPC)). The results indicate that the majority of residual errors in the Gaussian decomposition are <0.001 m^-1 , and R 2 of the power regression between characteristic bands and HPLC pigment concentrations (except for chlorophyll b) was 0.65 or greater for surface water samples at autumn cruise. In addition, we determined a strong predictive capability for chlorophylls a , c , PPC, and PSC. We also tested the estimation of pigment concentrations from the empirical specific absorption coeffi cient of pigment composition. The empirical decomposition showed that the Ficek model was the closest to the original spectra with the smallest residual errors.The pigment decomposition results and HPLC measurements of pigment concentration are in a high consistency as the scatter plots are distributed largely near the 1:1 line in spite of prominent seasonal variations. The Wozniak model showed a better fit than the Ficek model for Ch1 a , and the median relative error was small. The pigment component information estimated from the phytoplankton absorption spectra can help better remote sensing of hyperspectral ocean color that related to the changes in phytoplankton communities and varieties. | YE Huping ZHANG Bing LIAO Xiaohan LI Tongji SHEN Qian ZHANG Fangfang ZHU Jianhua LI Junsheng | 2019 | Journal of Oceanology and Limnology2019，37，5： | 1 |
| 4 | Catalytic domains of matrix metalloproteinases:a molecular biology approach to drug discovery显示文摘 | Ye QZ Hupe D Johnson L | 1996 | Current Medicinal Chemistry1996，3，： | 1 |
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