摘要：
土壤注记是土壤图制图表达的重要内容,对于理解土壤的发生、分布具有重要意义.在基于全国第二次土壤普查资料进行大比例尺土壤图分幅制图过程中,若对拥有海量土壤空间信息的多分幅大比例尺土壤图实现注记表达,不可能再依赖于传统的制图方式生成注记.为了实现注记上图的自动化和以交互方式解决多个步骤判断问题,构建了土壤图注记自动配置系统.该系统采用图廓边界注记压盖检测与处理技术,解决了注记压盖图廓边界的问题;采用图层、分级码、要素对象的三级控制方法,实现了注记在图层级别上进行整个图层以及背景层注记的设置,在分级码级别上结合统计结果,实现了注记的条件判别与阈值过滤,在要素级别上实现了特殊要素注记的生成.基于数据库驱动技术并以人机交互的方式进行土壤图注记的自动化配置,实现了批量土壤图分幅注记的快速生成,不仅具有较强的灵活性,可适用于不同比例尺土壤图及其他类型地图的注记表达,而且大大提高了数据生产的效率和自动化处理程度.该研究为今后不同比例尺土壤图制图实现注记的自动化配置提供参考.%[Objective]Soil map annotation is an essential component of soil mapping to have a better understanding of soil genesis and distribution. During the Second National Soil Survey sponsored by the Ministry of Agriculture of the People Republic of China in the 1980s, large volumes of soil maps at the county level were plotted in paper using the traditional mapping and annotating method, which is no longer efficient enough for plotting and annotating large-scaled multi-framed soil maps (more than 20 000 standard frames, 1: 50 000 in scale) that contains such huge volumes of soil spatial information. In order to realize automatic and interactive annotation and solution of a series of problems of step judgment in soil mapping, a soil map annotation auto configuration system was built up. [Method] The system was developed on ArcEngine 10.1 platform with C# programming language based on database-driven technology. The system solved the problem of annotation overlapping outer-boundaries of soil patches in the map with the help of the over boundary annotation detection method, and realized annotation of the entire map layer and the background layer on the map layer level, using the three-level control method, i.e. layer, grade code and feature object; condition judgment and threshold screening by combining statistics in grade coding and annotations of special features on the feature level. [Result]In order to evaluate performance of the Soil Map Annotation Auto-configuration System, a standard frame of soil map, F49E010012, of Xinyi, Guangdong, was chosen as an example for adoption of the system, with the 1:50 000 national basic geographic data and the 1:50 000 soil spatial and attribute data of the region as input. The basic geographic information to be annotated in the map includes residential settlements, linear water systems, surface water systems and administrative boundaries, whereas the soil spatial data do soil types and soil profile sites. The spatial data and attribute data were converted into Geodatabase. Analysis of the output volume of annotations shows that a total of 615 annotations were formed out of 2 618 items of feature data, including 2 067 items that already contains annotation names, and that the annotations formed covered only about 30% of all the annotatable feature data. The water systems and soil profile sites rarely annotated were reserved in the annotating process. On the soil map layer, most of the soil codes were reserved as annotation. Residential settlements were too densely clustered to keep the name of each settlement in annotation and only names of the settlements over the township level appeared. In the light of the conditions of the grading code screening module and avoidance analysis module, the volume of annotation was greatly reduced, particularly, the number of residential settlements to avoid overcrowding of the annotations of residential settlements on the map and relief the load of annotation, so as to maintain balance of the map in appearance. Comparison of the two maps shows that the original map had annotations overlapping map boundaries, while the map having processed with the Soil Map Annotation Auto-configuration System did not have such problems. [Conclusion]Based on the database-driven technique and human-computer interaction, the Soil Map Annotation Auto-configuration System is adopted to rapidly annotate an enormous volume of standard frame soil maps. The system is not only highly flexible, and adoptable to soil maps and other maps varying in scale, but also greatly improving the efficiency and automation degree of data production. All the findings in the study may serve as reference for realizing annotation automatic configuration in soil mapping varying in scale in future.
