In this era of big data transfer and use, the extraction of disaster event information from huge quantities of network data is important to facilitate research on disaster prevention and reduction. In comparison with traditional disaster information, disaster information based on Web text is dynamic, heterogeneous, and massive, has space-time aspects, and accesses multiple sources. How to extract and visualize the spatio temporal and attribute information of disaster events from Web text, and track dynamic change patterns and trends of such events over space and time, is a growing area of research in geographic and disaster information systems. This study reviews the progress of relevant researchs including network data mining technology frameworks, disaster theme web page crawling, the extraction of disaster event information, the visualization and spatial distribution characteristics analysis of disaster events and the application system for disaster prevention and reduction. By examining the trend of disaster information acquisition for disaster prevention and reduction from the internet, this study analyzed and summarized the appropriate technologies of information extraction from Web text and discussed the development trends in the following three aspects: (1) Focusing on global disaster information acquisition and analysis. The fundamental trend is to realize the automatic acquisition, analysis, and visualization of global disaster event information to ensure disaster prevention and reduction. (2) To realize the United Nations' 2030 Agenda for Sustainable Development and China's "the Belt and Road" strategy, strengthening of the disaster event information analysis research and its application to typical regions is one of the research hotspots in the field of Web disaster information acquisition and application. (3) Establishing a new disaster prevention and reduction knowledge service system supported by big data mining and analysis technologies according to the application level of data, information, and knowledge will be one of the future research trends.
Vector data, as an important part of Geographic Information System (GIS), plays a significant role in three-dimensional(3D) GIS to indicate geographic objects, explain spatial relationships and enrich map information. However, in the study of 2D vector rendering onto 3D terrain surface, vector lines drawn by traditional algorithms are relatively simple and monotonous, mainly shown as monochromatic lines or multicolor parallel lines, which cannot meet the growing demands for visualization. With the rapid development of graphics hardware acceleration and the widespread application of Virtual Geographical Environment (VGE), in order to draw the complicated linear map symbol in 3D map effectively and efficiently, this paper proposes a screen-based method that renders the linear symbol onto the 3D terrain surface with the use of OpenGL Shader Language (GLSL). We transfer the vector data from the procedure to Graphics Processing Unit (GPU) by encoding the vector data into the texture data. The mapping relationships between terrain units and vector lines are stored in the index texture, and the mapping is used for looking up the related line segments in real-time. In addition, the node texture stores the attribute of vector lines. We calculate the position relationship between screen fragments and related line segments, and find out the area where the current fragment belongs to. If the current screen fragment has associated line segments, then we get the attributes of the related line segments from the node texture and set the fragment color. It is worth mentioning that we provide a variety of symbolic functions, which can render different types of vector line segments, including gradient lines, periodic lines, etc. In order to achieve better visual effects, we apply a series of detail optimization operations to related line segments, including anti-aliasing and corner optimization. Finally, we take the Purple Mountain as an example and render vector lines onto it using the proposed method. The experiments demonstrated that vector lines rendered by our method show great visual effect and our method can render some complicated and typical line symbols with high performance while keeping rendering efficiency at real time level.
In the development of virtual geographic environment (VGE), natural and efficient human-computer interactions have always been one of the core contents of its research. However, users still communicate with VGE based on the traditional human-computer interaction interface in many current VGE application cases. This leads to two problems: (1) the immersive feeling of the users is poor; (2) the requirements for multi-users to interact in VGE cannot be effectively satisfied. It is crucial to take advantage of the latest achievements of human-computer interaction technology in order to solve these problems to meet the immersive multi-user collaborative interaction requirements in VGE. In this paper, the status of research and application of the human-computer interaction technology in VGE was reviewed. The development process and basic principle of motion capture technology and its advantages in improving the interactive immersion of VGE users were briefly described. Next, focusing on the design of immersive multi-user collaborative interaction system in VGE, the immersive multi-user collaborative interaction model based on motion capture technology and the corresponding interactive semantics of its interactive actions were analyzed. A multi-user collaborative conflict control mechanism was proposed. The structure and function of the immersive multi-user collaborative interaction system in VGE were introduced emphatically. Moreover, the Virtual Yanyuan Auxiliary Planning Prototype System (VYAPPS) adopting Peking University campus as a case study was developed by using Javascript and Python language. The experiments based on VYAPPS were carried out. Questionnaire statistical results show that the interactive effects of the immersive multi-user collaborative interaction technology in VGE are recognized by users. The results also showed that the advantages of the immersive multi-user collaborative interaction technology in improving multi-user immersion make it have a good application prospect. For example, it can be applied to geography education, urban planning, emergency rescue, military command fields and so on.
Population growth, climate change, institutional change and urbanization etc. would cause the change of land use / land cover, which in turn would further affect the hydrological process (e.g. infiltration, surface runoff, evapotranspiration and lateral flow) and water balance. Currently, because of the difficulties in obtaining the yearly land use / land cover data and the problems in calculating process in hydrological models, the simulation of hydrological process under the impact of land use / land cover change is conducted on one period each time and the impacts of multiple periods (e.g. multiple years) of land use / land cover change cannot be simulated continuously. That is the models could not call land use / land cover data year by year seamlessly. SWAT （Soil and Water Assessment Tools）is a distributed hydrological model. During its simulation period, it could not call land use / land cover data year by year and neglects the land use / land cover change in time scale. This would impact its applications in regions with severe land use / land cover changes (e.g. the Middle Reaches of the Heihe River). Heihe River Basin is the second largest and a typical endorheic river basin in China. The middle reach consumes a major portion of the water in the Heihe River. For the weakness of SWAT model, this research developed a model called LU-SWAT that could simulate the impacts of multiple years of land use / land cover change continuously. Furthermore, we applied SWAT and LU-SWAT to simulating streamflow in the Middle Reaches of the Heihe River, and compared their efficiency. The results showed that the LU-SWAT model, which could call land use / land cover data year by year is more suitable to simulate the streamflow in the Middle Reaches of the Heihe River.
Analysis on the road network is the basis for implementing the connectivity projects during the Initiative for the Belt and Road. The Belt and Road conforms to the trend of global economic globalization, integration, multi-polarization, and informatization. It implicates a thriving Asia-Pacific and developed European economic circles and drives the economic development of the intermediate countries. Under the new circumstances of the Belt and Road, it is of great practical significance to promote regional cooperation and economic development through the construction of transportation infrastructure along the Silk Road economic belt. In this study, based on the Volunteered Geographic Information (VGI), namely, OpenStreetMap (OSM) road network data of the Eurasian continental, the road network density and weighted road network density were calculated by Geographic Information System (GIS) spatial analysis techniques, and the spatial patterns of urban accessibility for the six economic corridors were studied. Following results have been obtained: there was an imbalance in the development of Land Transportation over the Belt and Road. The road network density and traffic capacity were higher in coastal areas than that in the inland areas. Central Asia, West Asia and Indo-china Peninsula are lagging areas that have restricted the integration of the resources and the smooth flow of trade in the Silk Road Economic Belt. It is suggested that at the same time as the construction of a new transnational road and railway, the existing old roads should be widened, reinforced, and upgraded. The grade levels of the roads across the region are in unreasonable coordination. The spatial distribution of urban accessibility in the six economic corridors showed an obvious interval pattern, and the accessibility of 83% of regions are within 10 h. This study showed that the undeveloped area of road in the Belt and Road, providing a fundamental dataset and support for the study on traffic infrastructure construction of the Belt and Road.
The study of urban development suitability is used for understanding the advantageous conditions of urban development, provides evidence for determining the expansion direction of town development project. Research in the arctic and the sub-arctic is of great significance for China's international cooperation in urbanization, major infrastructure and corridor construction. This article using multi-source data, on the basis of samplingpoints, 5 significant indicators were selected after filtering variables with the idea of stepwise method, the final logistic model was used to assess the suitability of urban development. Finally, the classified map of suitability of urban development was got. Finally, we get the classified map of suitability of urban development in study area. The result show that the ranking of significant indicators is, temperature (forward), traffic network density (forward), altitude (reverse), population density (forward), distance to nearest port (reverse). The above factors increase by 1 unit, the probability of urban development increased by 38.4%, 16.7%, 9%, 0.4%, and 0.1% respectively; The overall suitability of urban development shows a trend of decreasing with increasing latitude and it shows a trend of increasing with increasing longitude. The climatic and geographical conditions suitable for urban development are cool summer humid continental climates zone (Dfb, abbreviation in Koppen Climate Classification)and temperate oceanic climates zone (Cfb) with plains and lowland regions; The suitability of urban development in the study area sorted from the largest to the smallest is 0.08 in northwestern Russia, 0.07 in Sweden, 0.06 in Finland and 0.03 in Norway. The overall suitability of urban development in northwestern Russia is low in northern area and high in southern area. Sweden presents a trend that is low suitability in northwest area along with high suitability in southeast area, and suitability of coast is greater than that of inland. The suitability of Norway presents a spatial layout that is higher in the western coast, highest in the southern coast and low in other regions.
Extreme rainfall events caused terrible mountain torrents, urban floods and other disasters, and brought great losses to the ecological environment, social and economic development, people's lives and properties. Investigating the spatial pattern and difference of the occurrence of extreme rainfalls, especially for short time-duration, is important for the floods prevention and control. Based on the annual maximum rainfall data at the time resolutions of 60 min, 6 h and 24 h, we generated the series data with 2000 samples following the Pearson-III probabilistic distribution, and then calculated the information entropy values by discrete information entropy theory. Investigation was focused on the spatial distribution and difference of stochastic characteristics of extreme rainfall with different time-durations. Results show that the entropy value of annual extreme rainfall in the southeastern region is greater than that in the northwestern region, indicating more obviously stochastic characteristics of extreme rainfall in the latter. However, the spatial distribution of stochastic characteristics of extreme rainfall, which is comprehensively determined by monsoon, typhoon, local weather system and human activities, vary with time resolutions, especially the entropy value in the Eastern Tibet, Haihe River Basin and the Huaihe River Basin express obvious difference. In addition, the entropy value mainly accounts for the relatively discrete degree of extreme rainfall value, rather than absolutely discrete degree, so the entropy value is determined by the kurtosis value of extreme rainfall and the two variables show a significant negative correlation. Moreover, the paper indicates that the evident relationship between the entropy value and coefficient of variation does not mean causality, which is resulted from the relationship of kurtosis and entropy value. It is concluded that the spatial distribution of entropy values of extreme rainfall in different time-durations can reflect the spatial distribution of its stochastic characteristics, thus the results can be a helpful scientific basis for the flood prevention and control, agriculture and economic-social developments.
The coastal wetlands of the Yellow River Delta is the most integral, broadest and youngest wetland ecosystem in the warm temperate zone of China. Also, it has unique ecological landscape as well as important ecological service functions. With the increase in population and the intensification of high-intensity development and construction activities, the sensitivity/fragility of the area is highlighted, which poses a great threat to the sustainable development of coastal areas. Aiming at the unique geographic location and resource characteristics of the Yellow River Delta, based on RS and GIS, the hemeroby model as well as the man-made ditches density were used in this study to intuitively reveal the temporal and spatial characteristics of human disturbance intensity in 1995, 2004 and 2015 at the regional and local scales. The response of the wetland landscape pattern to human interference activities was explored as well. A grid analysis method was used to calculate the hemeroby index and man-made ditches density. The data source included the following: Landsat TM、ETM+ and OLI Remote Sensing Data (30 m resolution) in 1995、2004、2015, SPOT image of 2004(5m resolution) , GF-1 image of 2015 (2 m resolution) and topographic map. This study aims to provide decision support for ecological regulation and spatial control on human activities in coastal wetlands of the Yellow River Delta. The results showed that: (1) From 1995 to 2015, both the hemeroby index and the density of artificial ditches in the Yellow River Delta had increased significantly, and its spatial distribution showed a trend of expansion from the southwest to the east and north, and from inland to coastal areas; (2) With the increase of human activities, the area of natural wetlands in the study area have been decreased from 3232.11km2 in 1995 to 2165.48km2 in 2015, the landscape diversity and spatial heterogeneity increased, ecological connectivity weakened, the plaque shape tended to be regular and simplistic. (3) The response of landscape pattern to hemeroby index varies regionally and temporally. In the Kenli Agricultural Area, Hekou Agricultural Area and Shengli Oil Field Area, where the intensity of human interference activities had been relatively high, the intensity increased significantly, and the regional landscape pattern changed obviously in different phases. In the Yiqianer Management Station and the Yellow River Estuary Management Station area, where the intensity of human interference activities had been relatively low, due to the increase in the density of artificial ditches, the landscape pattern had presented a decreasing trend in landscape diversity, patch complexity and ecological connectivity from 2004 to 2015. (4) The indices of hemeroby and the density of man-made ditches supplement each other and confirm each other, which can reflect the degree of human disturbance activities in the Yellow River Delta more comprehensively and objectively.
Urban medical services have a great impact on the quality of life of urban residents and play an extremely important role in the field of public services. In recent years, with the rapid development of China's urbanization, large amounts of large data have been produced in the daily life of urban residents. Based on these massive data, the analysis of residents' medical travel characteristics is of great significance to optimize and improve the layout of urban medical resources. With the help of spatial location data of Beijing's main medical institutions and data of the taxi GPS movement trajectory, the space-time statistical analysis method is used to study the spatial and temporal characteristics of residents' medical travel by the taxi. The results show that using the OD (Origin-Destination) network structure characteristics of the hospital, the service scope of different hospitals and the spatial and temporal distribution pattern of the audience can be identified. The medical network of the hospitals in the urban area, especially within the forth ring, is dense and compact, and the medical density is high, while outside the forth ring and about suburbs, the medical network is sparse and scattered. The result in some degree shows that the geographical location of medical resources affects the residents' medical tendency. This study used the floating car GPS data to carry out the research on the spatial and temporal behavior patterns of residents' medical treatment, which can provide decision-making support for the supply and demand analysis and optimal allocation of urban medical resources.
Sharing bicycles is an important tool for solving the "last mile" travel problem in a city. However, the imbalance between supply and demand of sharing bicycles occurred frequently, which leads to significant spare of bicycles and obvious inconvenience for users. The key to solve this problem is to understand the spatial and temporal distribution characteristics of sharing bicycles’ supply and demand. In this case, this study defines the intensive "source" and intensive "sink" points of sharing bicycles, and uses Mobikes cycling data and land use type data to analyze the distribution characteristics of the intensive source and intensive sink points during the workdays and weekends, as well as the morning and evening peaks. Combined with the land type information, we further analyze the characteristics of sharing bicycles' usage under different land use types and propose a local scheduling model based on spatial neighborhood. Results show that under different land use coverage, the distribution of intensive source and intensive sink points of sharing bicycles show significant spatial and temporal heterogeneous patterns: (1) The usage of sharing bicycles during work days is obviously higher than weekends, and the distribution of the intensive source and intensive sink is obviously different among different land use types. For example, the net inflow and outflow density in areas such as residential, commercial, financial lands are greater than those of green areas; (2) In the morning and evening peak periods, the source and sink attributes of the same area are always showing a converse pattern. For instance, areas with offices such as education and scientific research lands and commercial and financial lands will have the characteristics of "morning sinks and evening sources", while the residential lands will be "morning sources and evening sinks"; (3) During the morning and evening peak periods of weekdays and weekends, there are also differences in characteristics of the sources and sinks of the same type of land use. For instance, the proportion of the intensive sources and intensive sinks will obviously decline in the office area on weekends. Based on the results above, this paper proposes a local optimized scheduling model. It is found that the model can effectively reduce the imbalance of bicycles' space allocation and increase the resource's utilization and the convenience of people's travelling.
Urban residential rent space differentiation has always been one of the core contents of urban geography and urban economics. The residential rent has the inherent regularity in the spatial distribution, and explores this law information and its influence mechanism, which helps the government to formulate reasonable price regulation and land use policy. Taking Nanjing "one main city and three subsidiary cities" residential quarters as research unit, this paper simulates and estimates the spatial distribution of "one main city and three subsidiary cities" residential rents by using fishnet analysis and Exploratory Spatial Data Analysis (ESDA) , and explores the influence mechanism of residential rent space difference from three aspects of residential area's location feature, architectural feature and neighborhood feature by using the geographical detector model. The results show that: (1) Residential rent in Nanjing generally shows an upward trend, showing a peripheral pattern of decentering from the main city to the vice city in space, and the spatial structure of residential rent gradually develops from single nuclear to dual nuclear with significant spatial heterogeneity in residential rent. (2) The residential rent shows obvious positive spatial correlation and regional agglomeration. The hot spots tend to weaken from the inner core to the vice cities, and the hot and cold spot spatial patterns are in a circle. (3) The traffic trend and central tendency are the factors that explain the rent of one house and three houses the most, and the second one is the explanation power of commercial facilities, financial facilities and residential houses. The influence intensity of the characteristic factors on the rents of the main city and vice-cities varies. Therefore, research on urban residential rental space distribution can promote the differentiation of space and an important driving mechanism, and can predict the basic trend in the future time city residential rental space distribution pattern evolution, can provide a forward-looking perspective and analysis tools to the study of urban social space.
A novel change detection method is proposed based on BOW (Bag of Words) features of the image objects, aiming at the drawbacks of traditional change detection methods and the poor interpretation capacity of basic features. First of all, a simultaneous segmentation method which took both spectral features and geometric information into consideration was applied to two images that were previously preprocessed and layer-stacked to acquire corresponding image objects; then mathematical mean and variance of every image band, and six textures from its panchromatic image were extracted as basic features. Moreover, the BOW representation of each image object was constructed by regarding objects as documents and basic features of pixels as words. Finally, similarity measurement was used to compare BOW features to define changed and no-changed areas. In this paper, experimental results on two sets of WorldView-2 images showed that the proposed method demonstrated superiority in completeness of detection result and outperformed the methods for comparison in accuracy assessment. In all, the proposed method can basically meet the needs of change detection work and provide an effective way for data mining and analysis of high resolution remote sensing images.
Rapid urbanization has led to land cover pattern changes which alter the surface net radiation and eventually influence surface energy balance. This process has been accompanied by a series of ecological and environmental problems, one of which is the urban heat island effect. Therefore, research on the seasonal variations of urban surface net radiation and its relationship to land cover pattern can provide important insights for exploring the formation and evolution mechanism of urban heat island. Taking Xiamen city as a study area, this research retrieved surface net radiation using Landsat-5 TM remote sensing images and meteorological data of the four seasons. Then the seasonal variation characteristics of surface net radiation were further analyzed. Landscape metrics were used to characterize and describe the spatial composition and allocation of land cover pattern. The correlation analysis, partial correlation analysis, stepwise regression analysis and variance partitioning were applied to explore the relationship between surface net radiation and land cover pattern from multi-seasonal perspective. The results suggest that: (1) the highest mean value of surface net radiation was found in summer, followed by spring, fall and winter. Surface net radiation is higher for the land cover types of water and forestland, while lower for built-up land and bare land. (2) The spatial allocation of land cover pattern has no significant influence on surface net radiation. (3) The spatial composition of land cover pattern shows significant influence on surface net radiation. The proportions of bare land and the proportion of forest land are effective and important factors which affect the changes of surface net radiation all the year round. And the proportion of forest land is the most important and continuously effective factor which affects and explains the cross-seasonal differences of surface net radiation. This research expands our scientific understanding of the effects of land cover pattern on surface net radiation. And it is helpful in exploring the formation and evolution mechanism of urban heat island. In addition, it may provide theoretical hints and realistic guidance for urban planning and sustainable development.
A number of researches have shown that the occurrence of earthquakes is often accompanied by abnormal warming of infrared radiation data, which is hidden in the Outgoing Long-Wave Radiation (OLR) data, which has been captured by the NOAA remote sensing satellite. These abnormal signals are embedded in a large amount of normal information and cannot be recognized by human eyes or some common methods. Many scholars utilized different means to analyze the anomaly of infrared remote sensing data. However, there were still lack of any effective processing techniques and algorithms, and most of the thermal infrared satellite remote sensing data weren't fully utilized. In this work, we propose a data mining algorithm, which is based on the anomaly features of the martingale theory. The algorithm first calculates the distance between a sample point and the cluster, and then determines whether the measured point is abnormal according to a comprehensive operation of the number of abnormal points nearest to each point, and calculates the whole event sequence data changing trend based on the martingale theory. The martingale value (i.e. CD value) corresponding to each original point is obtained, so that the original data is stripped out, the noise and the normal data are obtained, and the anomaly is analyzed before the earthquake. The OLR data sources used in the experiments on this algorithm were from three earthquakes happened in Nepal between September 2014 and July 2015 (including the Ms7.8 earthquake in April 25, 2015). We found that the CD value of the OLR data about the epicenter region began to have significant temporal correlation characteristics of anomalous data changes as early as 2 or 3 months before the earthquake. The results of this research were similar to the comparison of the OLR original and CD values of the Wenchuan and Lushan earthquakes. In this paper, we analyzed the anomaly of the three earthquakes one month before and some two weeks after the earthquakes. The experimental results show that when the earthquake is larger, and the anomaly CD value occurs earlier. In conclusion, the more obvious the anomaly is, the closer the region is to the epicenter or fault zone, the farther from the epicenter, the weaker and appeared later the abnormal signal.
The thesis paper is based on AMSR-E passive microwave brightness temperature data, chosen three soil surface freeze-thaw discrimination algorithms and compares the soil freeze-thaw status classification accuracy of the ground surface on Tibetan plateau area seperatly. Three algorithms are consisted of Dual Index Algorithm, Decision Tree Algorithm and Discriminant Function Algorithm. This thesis collects the soil surface temperature data from three soil temperature and humidity observational networks on Tibetan plateau that includes Naqu, Maqu and Ngari district, and combines with AMSR-E passive microwave brightness temperature data, then separately compares and evaluates the classification accuracy of the mentioned algorithms in the previous three observational areas. The results illustrate that whether during daytime or nighttime, in arid area like Ngari network district the microwave signal comes from deep layer soil, on the one hand, it’s kind of hard to probe in aid area and get an accurate detection as well, on the other hand, for all three discriminat algorithms that leads to the low discriminant accuracy in arid area at the same time. On the contrary each algorithm has relatively high discriminant accuracy in semi-arid area like Naqu network and subhumid area like Maqu network on Tibetan plateau; Dual Index Algorithm, compared with two other algorithm, has the highest classification accuracy among three discriminat algorithms, and has the best entirety classification accuracy in three observational networks on Tibetan plateau as well. The classificition accuracy at nighttime is higher than the dayttime due to the spatial heterogeneity of the air temperature between day and night; Except that the actual measured data also has the problem of incomprehensive representativeness, which means the inadequacy of information from all sites in the networks, and this is what needs to pay attention in the follow-up work to improve the algorithm classification accuracy.
In the study of spatial and temporal changes of the turbidity, traditional methods largely depend on field survey, which needs considerable manpower and materials. And these models are limited in different regions and time periods. With the help of self-organizing map (SOM) clustering, typical turbidity patterns can be extracted from plenty of remote sensing imageries covering long time periods. It can also facilitate the analysis of intra-annual and inter-annual variations. Taking the Yellow River estuary as our study area, six turbidity patterns were revealed from 2000-2015 MODIS data. Two main turbid areas appeared on the turbidity feature maps, located in the western and southern Bohai Bay, and outside the estuary in north-western Laizhou Bay. Four patterns appeared annually, of which the turbid level in winter and spring is higher than that in autumn and summer. And during the last fifteen years, turbidity patterns have gradually changed from middle turbidity to Clean, showing a declining trend of the overall turbid level. The hydrological data from Yellow River, meteorological observation data of wind and wave on the sea surface and ocean dynamics in the estuary were combined to detect the contributing factors of turbidity patterns. Spatial distribution was mainly influenced by wind waves and ocean dynamics, such as tide and circulating current. And intra-annual changes of dominant turbidity pattern were mainly caused by wind and wave on the sea surface, while the influence of sediment transportation from Yellow River is only limited around the estuary. SOM clustering results were evaluated from two perspectives: calculation of statistic parameters for quantitative analysis and inversion of the concentration of total suspended matter in the study area in 2007 for comparison with empirical model. It showed that there were significant differences between SOM patterns, and this method could reveal similar turbid features as the empirical models do. Thus, SOM is an effective and indispensable method to identify turbidity patterns and can directly extract typical features from long time series remote sensing imageries. This method significantly facilitates the study on spatial and temporal variation of water turbidity in coastal areas, which is of great practical value for research on sediment transport and water utilization in complex water bodies.
The China Meteorological Administration (CMA) has constructed a radar network of China next generation weather radar (CINRAD) to detect precipitation. In order to investigate the coverage condition of weather radar network, high-resolution digital elevation data of SRTM3 were used to analyze the terrain-blockage of 12 weather radars deployed in Guangdong Province. The beam blockage by mountain was calculated with the following method. Firstly, if the first tilt radar beam is blocked up to 50%, then it is considered that the radar beam does not scatter in the forward direction and the radar beam will jump to the next tilt at the blocked area, the obstructed slant range will be replaced by the second elevation. Secondly, if the mountain peaks are still higher than the radar beam and the radar beam is blocked up to 50%, the third tilt will be adopted. Results show that Shaoguan, Lianzhou and Zhaoqing radars suffer from serious beam blockage at the lowest elevation (0.5°). Additionally, Shenzhen, Yangjiang, Meizhou and Shanwei radars have large blocked areas at 0.5° elevation scan while the rest of radars have a very good coverage. With the raise of radar elevation, the beam blockage will be weaked or the more beams will clear the surface. At 3.4° elevation, all of 12 radars do not suffer from beam blockage. The 12 radars can completely cover Guangdong Province within the height of 5 km above mean sea level (MSL), and there are four adjacent radars in most areas. Radar coverage maps at the height of 3 km above ground level (AGL) and 3 km above MSL show that only a few regions in northern and northwestern Guangdong Province have no radar coverage, while most areas generally have more than 2 radars coverage, and there are 4-6 radars overlapping in the Pearl River Delta area. Within the height of 2 km AGL, the CINRAD network can effectively cover most regions of Guangdong province. Only within the height of 1 km, radar coverage in the northern and northwestern Guangdong Province is a little poor. Generally, the CINRAD network can monitor almost the entire Guangdong Province at height of 2 -3 km AGL and 3-5 km above MSL, thus, the distribution of radar is relatively good in Guangdong Province.
