###### Abstract
The original watermarks can still be effectively detected when the cover data containing the watermarks are embedded in another watermark. The question therefore remains as to how to effectively implement the whole process of multi-user tracking; this issue cannot be solved using a single watermarking algorithm. Multiple watermarking technology represents a good method for solving the above problems. The term \"multiple watermarking technology\" refers to the embedding of multiple distinct watermarks within the same cover data. This technology serves the purpose of safeguarding copyright and facilitating the tracking of \"multi-user\" usage during data distribution and transmission processes. However, the existing multiple watermarking technology places more focus on the algorithms for digital images that have the following three main types. The first is the combination of different types of watermarking, such as robust watermarking, fragile watermarking, zero watermarking, or reversible watermarking [12; 13]. The second is embedding watermarks in different locations that constitute spatial and frequency domains [14; 15; 16; 17; 18; 19; 20], as well as different blocks of the spatial domain [21; 22; 23; 24]. The last involves consolidating the multiple watermarks into a single watermark, which is subsequently embedded into the cover data using a normal single watermarking algorithm [25; 26; 27]. Vector geographic data are different from digital images because they are organized by coordinate vertices. Therefore, the above methods cannot be directly applied to the multiple watermarking algorithm for vector geographic data. For vector geographic data, adding, deleting, and randomly changing coordinate vertices are common operations; meanwhile, embedding sufficient watermarks is a challenge for vector geographic data containing fewer vertices. However, the concepts used to solve the problem for digital images can be used as a reference. To the best of our knowledge, limited research has been conducted on vector geographic data, and the algorithms that are used to embed multiple watermarks learn from those intended for digital images. For instance, in [28], robust watermarks and fragile watermarks were embedded into the feature and non-feature vertices of cover data. In [29], combined with the Arnold algorithm, a zero watermark was constructed according to feature vertices' information, and a non-destructive fragile watermark was used to authenticate the data content via spatial sorting and zero-bit dynamic expansion. In [30], two types of watermarks, namely, a zero watermark and a reversible watermark, were employed. The density center vertices were selected to embed the zero watermark, while the feature vertices located within a relative distance to the density center were utilized to embed the reversible watermark. The above three algorithms all combine general watermarking and zero watermarking or reversible watermarking to embed two watermarks, and the watermark capacity is limited. In [31; 32], two watermarks were embedded in the spatial domain and the frequency domain. In [33], four kinds of multiple watermarking algorithms were designed. One embedded two watermarks in the DFT (Discrete Fourier Transform) and DCT (Discrete Cosine Transformation) domains, while another embedded three watermarks in the low-, intermediate-, and high-frequency domains. The number of embedding watermarks in the above studies is limited by the type of watermarking algorithm. These algorithms embed two watermarks into different frequency domains. The number of frequency domains is limited, which limits the number of embedded watermarks. Consequently, as frequency domain watermarking algorithms, they have weaknesses in terms of resisting addition and deletion attacks. In [34; 35; 36], the cover data were divided into many blocks or vertices sets, in which multiple different watermarks were embedded. Enough coordinate vertices need to be provided so that multiple watermarks are not overwritten.