Sequential drone imagery of building façades under controlled acquisition configurations for rectified façade orthophotos

<b>Dataset overview:</b> Reliable façade inspection requires image datasets that support photogrammetric reconstruction and the generation of rectified façade products under clearly documented acquisition conditions. This dataset presents sequential drone imagery collected from three residential apartment buildings under three representative acquisition configurations per building, resulting in nine building–configuration dataset units. The release contains raw JPEG images captured using a DJI Mavic 3 Enterprise platform, with mission planning and automated flight execution conducted in UGCS. The acquisition framework was designed for crack-oriented façade inspection under practical field constraints, with imaging conditions intended to support the visibility of cracks wider than approximately 3 mm in the raw images. Within each building–configuration unit, images are organized by façade elevation, including front, rear, left-side, and right-side façades. The number of images varies across façades due to differences in façade geometry, accessible viewpoints, corridor conditions, and other operational constraints. The dataset is intended to support repeated offline evaluation of photogrammetric processing settings, including image alignment, reconstruction, and orthophoto generation.<b>File download and extraction instructions:</b> This dataset is distributed as a split ZIP archive because of its large total size. The archive consists of 11 files: Data.zip and Data.z01 to Data.z10. To extract the dataset correctly, users must download all 11 files and place them in the same folder. The dataset can then be extracted by opening Data.zip with a standard extraction tool such as 7-Zip, WinZip, or another compatible archive utility, which will automatically reassemble the full archive. If the dataset is downloaded using Figshare’s “Download all” function, users must first extract the outer ZIP file generated by Figshare, and then open Data.zip from the extracted folder to reconstruct the full dataset. Because of the large dataset size, downloading and extraction may require additional time and storage space.