*2.3. Data Processing*

The agricultural multispectral processing module in Pix4Dmapper 4.4 was used to automatically generate multispectral imagery and DSM. The fundamental working flow includes (1) radiometric calibration, (2) structure-from-motion (SFM) processing, (3) spatial correction, and (4) orthoimage and DSM generation. By employing radiometric calibration images and reflectance values, radiometric calibration can be performed for every image. Using the overlapping images, SFM processing recreates their positions and orientations in a densified point cloud by using automatic aerial triangulation. Based on four ground control points (manually collected before image acquisition), the three-dimensional point cloud was corrected during the stitching process and subsequently used to construct orthoimages and DSM.

Based on the multispectral imagery, the study area was divided into 119 blocks using the created fishnet function provided by ArcGIS 10.2. Then, 89 blocks were selected as the modeling areas and 30 as the verification areas. In the modeling areas, 643 maize lodging samples and 654 nonlodging samples were collected, marked as "1" and "0," respectively. These maize samples were subjected to binary logistic regression classification (BLRC), texture information extraction and feature screening. We also selected 50 samples each of lodging and nonlodging maize from the verification areas to calculate the precision of all the lodging identification results in this study.
