STATISTICAL ANALYSIS ON THE INFLUENCE OF THE LANDFALLING STRONG TROPICAL CYCLONES IN THE CATASTROPHIC MIGRATIONS OF NILAPARVATA LUGENS(STL) IN CHINA

In order to clarify the statistical pattern by which landfalling strong tropical cyclones(LSTCs)influenced the catastrophic migrations of rice brown planthopper(BPH),Nilaparvata lugens(stl)in China,the data of the LSTCs in China and the lighting catches of BPH that covered the main Chinese rice-growing regions from 1979 to 2008 were collected and analyzed in this work with the assistance of ArcGIS9.3,a software of geographic information system.The results were as follows:(1)In China,there were 220 strong tropical cyclones that passed the main rice-growing regions and 466 great events of BPH’s immigration in the 30 years from 1979 to 2008.73 of them resulted in the occurrence of BPH’s catastrphic migration(CM)events directly and 147 of them produced indirect effect on the migrations.(2)The number of the LSTCs was variable in different years during 1979 to 2008 and their influence was not the same in the BPH’s northward and southward migrations in the years.In the 30 years,the LSTCs brought more obvious influence on the migrations in 1980,1981,2005,2006 and 2007.The influence was the most obvious in2007 and all of the 7 LSTCs produced remarkable impact on the CMs of BPH’s populations.The effect of the LSTCs on the northward immigration of BPH’s populations was the most serious in 2006 and the influence on the southward immigration was the most remarkable in 2005.(3)In these years,the most of LSTCs occurred in July,August and September and great events of BPH's immigration occurred most frequently in the same months.The LSTCs played a more important role on the CM of BPH’s populations in the three months than in other months.(4)The analysis on the spatial distribution of the LSTCs and BPH’s immigration events for the different provinces showed that the BPH’s migrations in the main rice-growing regions of the Southeastern China were influenced by the LSTCs and the impact was different with the change of their spatial probability distribution during their passages.The most serious influence of the LSTCs on the BPH’s migrations occurred in Guangdong and Fujian provinces.(5)The statistical results indicated that a suitable insect source is an indispensable condition of the CMs of BPH when a LSTC influenced a rice-growing region.     

导管架式海上风力发电支撑结构振型扩阶方法

提出1种适用于海上风力发电支撑结构的模态振型扩阶方法。该方法无需借助转换矩阵实现振型扩阶,而是依靠实测模态并通过修正有限元模型对应振型在未测试自由度的振型值而获得空间完备的模态振型,并且所发展的方法在一定程度上可以忽略有限元模型存在的建模误差,是1种直接的估算方法,计算效率相对较高。文中采用三桩导管架式海上风力发电支撑结构验证提出方法的正确性以及在低阶模态振型扩阶上的优越性。数值结果表明,该方法对传感器位置、数量依赖程度低,尤其对于海上风电结构,仅在结构的水深较浅部位布置少数传感器即可比较精确的实现低阶模态振型扩阶,具有良好的工程应用前景。     

Modeling of spatial distributions of farmland density and its temporal change using geographically weighted regression model

This study used spatial autoregression（SAR） model and geographically weighted regression（GWR） model to model the spatial patterns of farmland density and its temporal change in Gucheng County,Hubei Province,China in 1999 and 2009,and discussed the difference between global and local spatial autocorrelations in terms of spatial heterogeneity and non-stationarity. Results showed that strong spatial positive correlations existed in the spatial distributions of farmland density,its temporal change and the driving factors,and the coefficients of spatial autocorrelations decreased as the spatial lag distance increased. SAR models revealed the global spatial relations between dependent and independent variables,while the GWR model showed the spatially varying fitting degree and local weighting coefficients of driving factors and farmland indices（i.e.,farmland density and temporal change）. The GWR model has smooth process when constructing the farmland spatial model. The coefficients of GWR model can show the accurate influence degrees of different driving factors on the farmland at different geographical locations. The performance indices of GWR model showed that GWR model produced more accurate simulation results than other models at different times,and the improvement precision of GWR model was obvious. The global and local farmland models used in this study showed different characteristics in the spatial distributions of farmland indices at different scales,which may provide the theoretical basis for farmland protection from the influence of different driving factors.     

Effects of corridor networks on plant species composition and diversity in an intensive agriculture landscape

The development of modern agriculture has resulted in much homogenization of the landscape consisting of large patches of farmland,so small remnant non-crop habitats especially linear corridors play an important role in the conservation of species and the maintenance of ecosystem functions.However,little attention has been paid to the effects of corridors structural characteristics on the plant species restricted to such habitats.In this study,we selected three types of corridors including ditch,hedgerow and road,and ana-lyzed their structural characteristics.The plant species presented in these corridors were investigated,and the species diversity,abun-dance and frequency were estimated.Moreover,spatial arrangements of corridors were classified into different types to discuss whether there were significant effects of corridor network on plant distribution.The results show that three types of corridors have different ef-fects on plant species composition and diversity.The one-one combined corridor networks and total network associated by three corri-dors have more complex structural features than each single type of corridor.However,there is no strong correlation between the corri-dor networks with their plant species.We suggest that carrying out a pointed vegetation survey at corridor intersections to further test the relationships between structural features of corridor and plants is necessary.     

Evolution and spatial patterns of spheres of urban influence in China

This article presents the findings of a study of the spheres of urban influence with regard to all cities in China（not including Hong Kong,Macau and Taiwan Province of China）in the years 1990,2000 and 2009.An optimized gravity model with comprehensive time distance was used to carry out a detailed analysis of the spatial patterns of Chinese spheres of urban influence and the spatial characteristics of urban agglomerations.Such urban agglomerations are characterized by high density population and a developed economy,which are also considered as the national competition unit.This paper initially identifies four spatial patterns of urban agglomerations based on the spatial layout of city groups during their evolution.Some basic characteristics of urban agglomerations are outlined,including the number of cities,the size of cities and the functions of urban centers.These characteristics are examined by using statistical methods and Geographic Information System（GIS）.The main findings from this research are that the development stages and structures of urban agglomerations in China vary significantly.It is also clear that the stages and evolution of spatial patterns are strongly affected and dominated by both policy and location factors.     

Spatial structure of central places in Jilin Central Urban Agglomeration,Jilin Province,China

Using the radius of gyration from fractal theory, this paper describes the calculation of fractal dimensions for the four tiers of central places in the Jilin Central Urban Agglomeration(JCUA), Jilin Province, China and the structural characteristics of each tier: 1) the 1st tier central place, Changchun Proper(not including Shuangyang District), provides the most service functions and has the most stable primate position; 2) the 2nd tier central places, Jilin Proper, Siping Proper, Liaoyuan Proper and Songyuan Proper have unclear statuses and do not provide certain functions; 3) the 3rd tier central places comprise 23 county-level cities, counties and urban districts(including Shuangyang District of Changchun), exhibiting a dense spatial structure that agrees with theory; 4) the 4th tier contains the largest number of central places(248 designated towns), but they are loosely distributed. In this study, a spatial image of the JCUA was created, based on vectorized data of the urban settlement distribution, which was then modified and abstracted to create a hexagonal network covering the JCUA. Compared to the traditional central place model, the modified spatial image conforms to the K = 3 principle. In reality, however, the growth of some 3rd tier central places should be increased with the cities being upgraded to the 2nd tier so as to overcome that tier′s functional deficiency. The loose distribution in the 4th tier should also be changed. This apparent anomaly can be explained by the fact that the classic hexagon model used to describe the way market areas layout does not exist in the real world. However, this should not be viewed as an obstacle to using central place theory. If its assumptions are properly applied, it can still assist research into the spatial structure of regions.     

Characterizing landscape spatial heterogeneity in multisensor images with variogram models

Most evaluation of the consistency of multisensor images have focused on Normalized Difference Vegetation Index （NDVI） products for natural landscapes, often neglecting less vegetated urban landscapes. This gap has been filled through quantifying and evaluating spatial heterogeneity of urban and natural landscapes from QuickBird, Satellite pour l＇observation de la Terre （SPOT）, Ad- vanced Spacebome Thermal Emission and Reflection Radiometer （ASTER） and Landsat Thematic Mapper （TM） images with variogram analysis. Instead of a logarithmic relationship with pixel size observed in the corresponding aggregated images, the spatial variability decayed and the spatial structures decomposed more slowly and complexly with spatial resolution for real multisensor im- ages. As the spatial resolution increased, the proportion of spatial variability of the smaller spatial structure decreased quickly and only a larger spatial structure was observed at very coarse scales. Compared with visible band, greater spatial variability was observed in near infrared band for both densely and less densely vegetated landscapes. The influence of image size on spatial heterogeneity was highly dependent on whether the empirical sernivariogram reached its sill within the original image size. When the empirical semivariogram did not reach its sill at the original observation scale, spatial variability and mean characteristic length scale would increase with image size; otherwise they might decrease. This study could provide new insights into the knowledge of spatial heterogeneity in real multisen- sor images with consideration of their nominal spatial resolution, image size and spectral bands.     

基于拓扑与形态特征的城市道路交通状态空间自相关分析

城市道路交通状态具有空间自相关特征。某一道路交通状态的变化会对其周边道路产生影响,故把握道路交通状态的空间自相关性是提高交通规划、交通预测水平的基础。然而,城市道路交通状态又具有空间异质性,即道路交通状态的影响扩散并非各向同性,其使得道路交通状态空间自相关性的度量更为复杂,因此仅从地理空间下道路之间的邻近关系出发进行分析有失偏颇。同时,城市道路具有拓扑结构特征和几何形态特征,二者对于交通状态自相关性的影响和制约,却未引起足够重视。本文从城市道路的拓扑结构特征和几何形态特征出发,提出了一种新的交通状态空间自相关路段识别规则,即基于交通状态变化的路段空间识别规则,通过拓扑社区发现方法刻画路段在空间上的聚集特征,同时,基于Stroke跟踪的几何形态概化来描述道路交通状态变化影响的空间异质性。结果表明,利用本文提出的识别规则产生的交通状态自相关路段集合,较仅考虑地理空间邻近或拓扑结构的识别规则更为合理,更好地揭示了城市道路交通状态的空间自相关特征。     

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