*4.1. Rural Settlements Identification*

Figure 5 shows the resulting rural settlements of our study area. Tables 2 and 3 present confusion matrices on test sets. The proposed method achieved the OA of 98.31% with a Kappa coefficient of 0.9724 on the point test set, and the UA and PA of two settlements classes reached about 98%. The classification accuracy on polygon-based testing samples was different, the accuracies of low-density class (UA of 88.00% and PA of 84.97%) were higher than those of high-density class (UA of 85.22% and PA of 84.68%). In terms of overall classification, the Kappa coefficient of 0.8591 in the polygon-based testing method were lower than that of the point-based test set. This was because the polygon-based test method had strict requirements on the object boundary. Visual interpretation indicates that the proposed method can effectively distinguish rural residential areas from other man-made structures (white circle in Figure 5). It was observed that the footprints of HDS were more smoothed than the LDS, where the latter ones were inclined to be obscured by the surroundings, e.g., tress and shadows. The introduction of multi-scale context made it easier for HDS with relatively uniform scales to be detected, which was reflected by the PA. In addition, a few LDS houses on the edge of HDS were misclassified into isolated houses within HDS. This was caused by a similar roofs and ambient vegetation (red circle in Figure 5). It further suggests that the polygon-based testing method is necessary. Previous studies considered recognition accuracy, but sometimes did not include area accuracy of rural settlements.

**Figure 5.** Classification result of the polygon test area.




**Table 3.** Confusion matrix of polygon test set (m2).
