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首页> 外文期刊>ISPRS International Journal of Geo-Information >A Combinatorial Reasoning Mechanism with Topological and Metric Relations for Change Detection in River Planforms: An Application to GlobeLand30’s Water Bodies
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A Combinatorial Reasoning Mechanism with Topological and Metric Relations for Change Detection in River Planforms: An Application to GlobeLand30’s Water Bodies

机译:具有拓扑和度量关系的组合推理机制,用于河床平面变化检测:在GlobeLand30的水体中的应用

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Changes in river plane shapes are called river planform changes (RPCs). Such changes can impact sustainable human development (e.g., human habitations, industrial and agricultural development, and national border security). RPCs can be identified through field surveys—a method that is highly precise but time-consuming, or through remote sensing (RS) and geographic information system (GIS), which are less precise but more efficient. Previous studies that have addressed RPCs often used RS, GIS, or digital elevation models (DEMs) and focused on only one or a few rivers in specific areas with the goal of identifying the reasons underlying these changes. In contrast, in this paper, we developed a combinatorial reasoning mechanism based on topological and metric relations that can be used to classify RPCs. This approach does not require DEMs and can eliminate most false-change information caused by varying river water levels. First, we present GIS models of river planforms based on their natural properties and, then, modify these models into simple GIS river planform models (SGRPMs) using straight lines rather than common lines to facilitate computational and human understanding. Second, we used double straight line 4-intersection models (DSL4IMs) and intersection and difference models (IDMs) of the regions to represent the topological relations between the SGRPMs and used double-start-point 8-distance models (DS8DMs) to express the metric relations between the SGRPMs. Then, we combined topological and metric relations to analyse the changes in the SGRPMs. Finally, to compensate for the complexity of common river planforms in nature, we proposed three segmentation rules to turn common river planforms into SGRPMs and used combinatorial reasoning mechanism tables (CRMTs) to describe the spatial relations among different river planforms. Based on our method, users can describe common river planforms and their changes in detail and confidently reject false changes. Future work should develop a method to automatically or semi-automatically adjust the segmentation rules and the combinatorial reasoning mechanism.
机译:河平面形状的变化称为河平面形状变化(RPC)。这种变化会影响人类的可持续发展(例如,人类居住,工农业发展以及国家边境安全)。可以通过实地调查来识别RPC,这是一种高度精确但费时的方法,也可以通过精度较低但效率更高的遥感(RS)和地理信息系统(GIS)来识别。先前针对RPC的研究通常使用RS,GIS或数字高程模型(DEM),并且只关注特定区域中的一条或几条河流,目的是找出造成这些变化的原因。相反,在本文中,我们基于拓扑和度量关系开发了一种组合推理机制,可用于对RPC进行分类。这种方法不需要DEM,并且可以消除由于河水水位变化而引起的大多数错误变化信息。首先,我们根据河流自然形态的自然特性提出GIS模型,然后使用直线而不是普通线将这些模型修改为简单的GIS河流自然形态模型(SGRPM),以促进计算和人类理解。其次,我们使用区域的双直线4交叉模型(DSL4IM)和交叉和差异模型(IDM)来表示SGRPM之间的拓扑关系,并使用双起点8距离模型(DS8DM)来表示SGRPM之间的度量关系。然后,我们结合拓扑和度量关系来分析SGRPM中的变化。最后,为了弥补自然界中常见河道平面图的复杂性,我们提出了三种分割规则,将共同河道平面图转化为SGRPM,并使用组合推理机制表(CRMT)来描述不同河道平面图之间的空间关系。根据我们的方法,用户可以详细描述常见的河流平面图及其变化,并自信地拒绝错误的变化。未来的工作应该开发一种自动或半自动调整分割规则和组合推理机制的方法。

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