城市电子地图多尺度自动缩编方法

随着智慧城市、地理信息公共服务及地理国情数据等政务信息逐步公开,作为各类政务信息发布基础的城市电子地图在多尺度展现时,只能通过关闭、选取要素来实现,这种未进行制图综合的做法导致要素在逐级放大过程中,会出现跳跃性丢失和细节破碎的现象,既不符合地图表达要求也难以满足用户视觉体验。本文提出了一源数据多尺度自动缩编的技术方法,构建了最优化的"统一源头、一致派生、无级表达"技术体系,实现了城市电子地图联动更新和多尺度展现,节省了大量人力和物力,为最大限度地发挥测绘地理信息集成与服务能力提供保障。     

河西走廊沙尘暴及其影响因子的多尺度研究

沙尘暴活跃期具有周期性,这与影响因子的周期变化有关,尝试利用具有多时间尺度和多分辨率特性的小波分析技术对其进行研究。利用Morlet小波对甘肃河西走廊18个气象站多年平均的沙尘暴日数进行分析,发现沙尘暴变化的时间序列具有多尺度振荡的特点,存在7 a、13 a、以及23 a左右的特征时间尺度（周期变化）。通过对大风日数、干旱指数、降水、气温等沙尘暴的影响因子分析,表明沙尘暴的活跃度与大气环流的年际变化和突变有关,特别是与大风日数在时间尺度和主周期等方面具有明显的一致性,7 a左右的年际变化是它们的主周期;干旱指数、降水和气温具有同步的时间序列,13～25 a的年代际变化是它们的主周期,因此,它们对沙尘暴的影响主要体现在大时间尺度上。     

Curvelet变换及其在地震波场分离中的应用

小波多尺度分析可以有效处理一维信号的点奇异特征,但对于二维信号的线奇异特征,小波变换显得无能为力。Curvelet多尺度变换可以对时空信号进行最稀疏表达,能够获得最优的非线性逼近。通过分析地震信号在Curvelet域三维空间的特征,认为时空信号的不同波组成分在Curvelet域存在明显的差异,可以从频率、角度和空间位置实现有效反射波和干扰波的分离。理论模型与实际单炮记录处理结果表明,Curvelet域方法在分离干扰波、突出反射波的同时,可以较好地保持有效波信息,保真度好。      

TRANSVERSE STRUCTURES FEATURES OF DIFFERENT DEPTHS DERIVED FROM BOUGUER GRAVITY ANOMALIES IN THE SOUTHERN SEGMENT OF TAN-LU FAULT ZONE

To research the faults distribution and deep structures in the southern segment of Tan-Lu fault zone(TLFZ) and its adjacent area, this paper collects the Bouguer gravity data and makes separation by the multi-scale wavelet analysis method to analyze the crustal transverse structure of different depths. Meanwhile Moho interface is inversed by Parker variable density model. Research indicates that the southern segment of TLFZ behaves as a NNE-directed large-scale regional field gravity gradient zone, which separates the west North China-Dabie orogen block and the east Yangtze block, cutting the whole crust and lithosphere mantle. There are quite differences of density structures and tectonic features between both sides of this gradient belt. The sedimentary and upper crustal density structure is complex. The two east branches of TLFZ behave as linear gravity anomalous belt throughout the region, whereas the two west branches of TLFZ continue to extend after truncating the EW-trending gravity anomaly body. The lower crustal density structure is relatively simple. TLFZ behaves as a broad and gentle low abnormal belt, which reflects the Cretaceous-Paleogene extension environment caused graben structure. The two west branches of TLFZ, running through Hefei city, extend southward along the west margin of Feidong depression and pinch out in Shucheng area due to the high density trap occlusions in the south of Shucheng. The Feizhong Fault, Liu'an-Hefei Fault, and Feixi-Hanbaidu Fault intersect the two west branch faults of TLFZ without extending to the east. Recent epicenters are mainly located in conversion zones between the high-density and the low-density anomaly, especially in TLFZ and the junction of the faults, where earthquakes frequently occurred in the upper and middle crust. As strong earthquakes rarely occur in the southern segment of TLFZ, considering its deep feature of abrupt change of the Moho and intersections with many EW-trending faults, the hazard of strong earthquake cannot be ignored.     

基于层次分析法的多尺度点群目标相似度计算

计算不同尺度下空间目标的相似性是GIS研究的热点问题之一。点群是地理空间群组目标的一种,研究其相似性可对空间群组目标的计算机制图结果进行评价。以往的理论研究主要从影响点群目标的单一因子出发,对影响点群目标的简单因子进行分析,并以此提出相应计算模型。为了研究点群目标在不同尺度下的相似性问题,本文在前人研究的基础上,整合了影响点群目标相似性的主要因子（包括拓扑关系、方向关系、距离关系、分布范围和分布密度）,并分别提出拓扑相似度、方向相似度、分布范围相似度、距离相似度分布和密度相似度的计算模型,从整体上把握计算点群目标的相似性。通过层次分析法,赋予5种因子相应的权重,最后集成不同尺度下点群目标相似度的总体计算模型。经过计算验证,该方法能较准确地计算不同尺度下点群目标的相似程度,为制图综合质量做出评价。     

区域碳收支能力估算的面向对象遥感分类方法

全球气候变暖问题是人类面临的最艰巨的挑战之一,通过先进的面向对象分类方法可以提高碳排放与碳汇能力的研究水平,对于控制区域气候变化具有推动作用。本文利用面向对象分类方法,以广西百色市右江区为研究区域,选取Landsat 8 OLI和Google Earth影像数据提取区域地物信息,并针对研究区地势复杂的特点,采用设置多种尺度参数的方法,选取最优尺度进行影像分割。同时,引入隶属度函数法、最邻近分类法和CART决策树分类器3种方法,基于影像光谱差异、几何形状、对象纹理等特征,逐层逐级地实施面向对象分类,随后加以针对性的精度评价分析并检验分类结果。通过总结分析前人的地物碳系数转换关系并结合高精度面向对象分类结果,构建了基于土地覆被类型的碳收支能力估算模型,并根据已有的基于CASA模型的碳收支能力估算方法加以精度校验,最终估算出右江区碳收支能力为-399.64万t。此外,本文结合右江区行政区划、人口分布、DEM等相关数据对区域碳收支能力进行了专题性剖析。结果表明,面向对象分类方法是研究小区域碳收支能力的有效途径,在区域碳循环评估中具有更好的准确性和预见性,有效促进碳收支平衡研究领域的发展。     

城市道路网的多尺度连续变换方法

本文提出了一种多比例尺道路网的连续变换方法,旨在解决在信息化大地图环境下城市道路网的多尺度连续表达需求。该方法首先对2种比例尺的道路网数据进行拓扑重建预处理,然后利用概率松弛匹配方法识别二者的要素对应关系。根据要素对应表,将2种比例尺道路要素分为1:1对应线状要素、1:0单独线状要素和M:N复杂线状要素3种情况：（1）对于1:1对应线状要素,本文采用简单线性Morphing变换方法;(2)对于1:0单独线状要素,首先对道路要素的直角特征进行识别,并定义直角及其前后一定范围内的线段为直角子线段,在此基础上,利用Douglas-Peucker算法将分割后的道路要素进一步分割,然后将直角子线段的起点和终点作为断点切割原道路要素,以顶点连续移位的方式实现连续综合变换;(3)对于M:N复杂线状要素,采用渲染颜色逐渐淡出的方法进行连续表达。最后,将3种情况的连续变换结果进行叠加组合。实验结果表明,本文方法能够获得良好的多尺度连续表达效果。     

多空间数据库位置匹配方法及其应用

同一地区由于不同的要求和目的而建立了多种数据库 ,包括不同比例尺的基础地理信息数据库或空间专题属性数据库。在实际应用中经常需要将这些数据库中的数据联系起来 ,相互利用。在实践中通常可以利用存在位置属性这一特点将这些数据库关联 ,达到充分利用数据、挖掘数据潜在信息的目的。本文以国家基础地理信息数据库中全国 1∶2 5万和全国 1∶1 0 0万数据的公路和河流要素为实例 ,阐述利用空间位置这一特性来建立数据库联系的思路方法     

Modeling the scale dependences of topological relations between lines and regions induced by reduction of attributes

The scale dependences of topological relations are caused by the changes of spatial objects at different scales, which are induced by the reduction of attributes. Generally, the detailed partitions and multi-scale attributes are stored in spatial databases, while the coarse partitions are not. Consequently, the detailed topological relations can be computed and regarded as known information, while the coarse relations stay unknown. However, many applications (e.g., multi-scale spatial data query) need to deal with the topological relations at multiple scales. In this study new methods are proposed to model and derive the scale dependences of topological relations between lines and multi-scale region partitions. The scale dependences of topological relations are modeled and used to derive the relations between lines and coarse partitions from the relations about the detailed partitions. The derivation can be performed in two steps. At the first step, the topological dependences between a line and two meeting, covered and contained regions are computed and stored into composition tables, respectively. At the second step, a graph is used to represent the neighboring relations among the regions in a detailed partition. The scale dependences and detailed relations are then used to derive topological relations at the coarse level. Our methods can also be extended to handle the scale dependences of relations about disconnected regions, or the combinations of connected and disconnected regions. Because our methods use the scale dependences to derive relations at the coarse level, rather than generating coarse partition and computing the relations with geometric information, they are more efficient to support scale-dependent applications.