This paper presents a new approach and procedure for directly processing vector-based data sets to generalise maps depicting real-world phenomena. It shows how map generalisation and seamless matching of the edges of adjacent area features can be achieved. With this approach, the combined use of selected methods has led to a ground-breaking novel procedure for vector-based map generalisation guaranteeing outputting with neither self-intersection nor cross-intersection. The approach employs turning points and convex hull points as a set of characteristic points. These points define the shape and characteristics of real-world geographical features with delineating lines, which have complex rendering layouts, many turnings and inherent sub-features. The set of characteristic points are used as splitting points to partition lines into monotonic chains. Line simplification with an intuitive point reduction technique using the Douglas-Peucker algorithm is confined within monotonic chains to guarantee no self-intersection. In addition, the paper describes the most suitable and intuitive means to deal with gaps and overlaps potentially resulting from cross-intersections without adding or deleting any anchoring point. Distinctively different from the approaches of previous studies, the research was undertaken through an iterative process of exploratory programming, experimentation, validation and testing of results produced. This process was repeated until an integrated total solution was reached. It sheds new light on the fields of geocomputation, geographic information systems (GIS) and digital cartography.