Spatial and Temporal Distribution Characteristics of Snowstorm in Ulanqab City in Recent 30 Years

Based on the data of daily snowfall and weather phenomena of 11 national meteorological stations in Ulanqab City from 1991 to 2020,the spatial and temporal distribution characteristics of snowstorm were analyzed.The results show that the snowstorm in Ulanqab had obvious seasonal distribution characteristics,mainly happening in spring(March-May)and autumn(September-November).It also had obvious regional distribution in space,and the snowstorm center appeared in Chahar Right Wing Middle Banner and Jining District,namely the east side of the Yinshan Mountain.In the past 30 years,the amount of snowstorm in the whole year in Ulanqab showed a certain fluctuation trend,and the number of snowstorm days had shown an obvious upward trend since 2011.

Spatial and Temporal Distribution Characteristics of Flower-viewing Tourism and Its Influencing Factors in China

Despite the rapid development of flower-viewing tourism in China in recent years,there is almost no systematic research on it.Therefore,this study analyzes the spatial and temporal distribution characteristics of flower-viewing tourism and its influencing factors in China using the spatial statistical analysis methods and the geographic detector method.The study uses the Point-of-Interest data of flower-viewing tourist attractions from networks such as Qunar and Ctrip,the flower observation data from China Phenological Observation Network,Chinese network news,and Weibo,and the statistical data from yearbooks.The results are as follows:1)The spatial attribution type of flower-viewing tourism in China is aggregated into areas,including two high-density aggregated areas,three medium-density aggregated areas,and one general-density aggregated area.Furthermore,five major types of flower-viewing tourist attractions have formed several aggregated areas.2)The time of flower viewing in China starts from about February and lasts about eight months till October each year.Florescence and flowering time of different ornamental flowers in different regions are different.3)The spatial and temporal distribution characteristics of flower-viewing tourism in China are mainly affected by ornamental flower phenology,spatial distribution characteristics of flower-viewing resources,regional permanent population size,youth population size,female population size,regional GDP,and added value of the tertiary sector.These conclusions clarify the spatial and temporal distribution characteristics of flower-viewing tourism and its influencing factors in China.They could provide a scientific basis and useful reference for the coordination and sustainable development of regional flower-viewing tourism in China.

Recognition Algorithm and Risk Assessment of Airport Hotspots

The hotspot recognition algorithm is proposed based on a potential collision in order to study the aircraft taxi conflicts in large airports.The spatial and temporal distribution characteristics of hotspots are analyzed based on the risk assessment model of hotspot constructed in this paper.Firstly,approaches for monitoring of the aerodrome movement were compared.The hotspot recognition algorithm taken into account of whether aircrafts'taxi track has spatial and temporal overlap based on the aerodrome surveillance radar(ASR)data was presented,by identifying the hotspots through analyzing whether the aircrafts'time of entering and exiting the same taxiway is overlap or not,and the heading difference and distance of the two aircrafts satisfy the specified threshold constraint condition.Then,the ASR data were divided into several parts,and then airport hotspots were recognized and the spatial and temporal distribution characteristics were analyzed.The risk assessment model of airport safety hotspots was constructed which is taken into account of the conflict probability and its severity consequence.Finally,based on the risk grade assessment criteria and hotspots'risk value,the risk grade ranking of hotspot in one airport of China was evaluated and designated.According to the result,the spatial and temporal distribution characteristics of airport hotspots were varied with the variation of airport traffic flow and operational mode of runway,which shows that the hotspots have the characteristics of dynamic periodicity and diurnal variation.And the risk assessment results were consistent with experts'opinions and actual operation condition,which verified the rationality of the hotspot recognition algorithm,risk assessment model as well as the risk grade ranking criteria.