Abstract
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.
Highlights
Rivers are critical for human survival and sustainable development and provide indispensable human resources, such as domestic water, agricultural water, industrial water, shipping, and alluvial plains
Using geographic information system (GIS), people can rapidly display, process, and analyse the high volumes of geographic data acquired through remote sensing (RS)
To better analyse river planform changes” (RPCs), some auxiliary information such as digital elevation models (DEMs), landscapes, and geometries have been applied to the analysis of river planforms
Summary
Rivers are critical for human survival and sustainable development and provide indispensable human resources, such as domestic water, agricultural water, industrial water, shipping, and alluvial plains. Dynamic river planforms are temporary and should not be considered as true river planforms; in other words, changes caused by non-normal river levels should be considered as false RPCs. The common approach for detecting RPCs and distinguishing false RPCs is to use a LiDAR-based high-precision DEM at different times; this approach is costly on a global scale [31,32,33,34,35,36]. In this paper, considering river planform properties, we develop a reasoning mechanism that combines topological and metric relations to detect and analyse massive amounts of RPCs and distinguish false RPCs. The remainder of this paper is organised as follows: In Section 2, we discuss related works on the spatial relations of lines or regions.
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