•A new remote sensing detection equipment, airborne streak tube imaging laser radar.•A building zone extraction method from airborne streak tube imaging laser radar data.•A building zone extraction method only using single data source, laser radar data.•Extracting suburban residential building zone. In this paper, we proposed a novel method for extracting suburban residential building zone (SRBZ) from airborne streak tube imaging LiDAR (STIL) data. This method is implemented using a single data source, which avoids the collections of multi-source data and shortens the production cycle of LiDAR data products. The framework of the method is mainly composed of a prediction module, and a correction module. In the correction module, two correction algorithms were proposed, that is, k-nearest neighbor majority voting correction algorithm (k-NNMV) and Gaussian weight based k-nearest neighbor voting correction algorithm (GWk-NNV). Experiment tests show that the framework based on the GWk-NNV has a better SRBZ extraction effect than that of the k-NNMV. The F1 coefficient of the GWk-NNV-based framework reached 80.10%. That proves that the proposed method for extracting SRBZ from airborne STIL data is feasible.