# Recognizing Urban Functional Zones by GF-7 Satellite Stereo Imagery and POI Data
## 2 Study Area and Data
### Data  
The GF-7 is China's first civil optical stereo mapping satellite with a sub-meter resolution. It was successfully launched in November 2019 with an orbital altitude of about 506 km and has a return cycle period of fewer than 60 days. It can effectively acquire 20 km wide front-view panchromatic stereoscopic images with a 0.8 m resolution, rear-view panchromatic stereoscopic images with a 0.65 m resolution, and multi-spectral images with a 2.6 m resolution. The specific parameters of the GF-7 dual-line array stereo camera are shown in Table 1.  
In this study, two adjacent GF-7 images were selected on 16 October 2020 with less clouds, a clear texture, and geometric structure, which effectively covered most of the area within the Beijing Fourth Ring Road. The 0.65 m multi-spectral image underwent preprocessing steps, such as orthorectification, image sharpening, and mosaicking, using PCI Geomatica 2021 SP4. Subsequently, the multi-spectral images were resampled to a resolution of 1.3 m as required. DSM data are generated by utilizing both the GF-7 front-view panchromatic image and rear-view panchromatic image. Initially, the rational function model was created, and then the ground control point (GCP) and tie point (TP) were collected to improve the mathematical model and ensure that the stereo pairs were aligned with each other. Finally, the semi-global matching (SGM) algorithm was used to derive 1 m DSM data [46]. Meanwhile, we take blocks and some buildings as spatial units, and a series of filtering algorithms available in PCI Geomatica were carefully filtered the DSM to obtain Digital Elevation Model (DEM). Then, DSM minus DEM to obtain nDSM, which is used to describe the relative height of ground objects. Furthermore, due to water surface clutter and the building being occluded, the nDSM value of the water surface is wrong and some building height information is missing. We utilized the surrounding ground object height and building floor data as references to correct the nDSM data to obtain the finalized nDSM data. Figure 2 shows the finalized nDSM data. POI data are a kind of spatial point data, which are an abstract expression of geographic entities in the real world. Any geographic entity can be represented by POIs, such as shopping malls, universities, residences, and parks, and typically include attributes, such as names, categories, and geographic coordinates. In this study, the POI data were obtained using the Gaode map API, and the data were downloaded on 10 July 2021. The Gaode map has three levels of classification for POIs, including 23 first-level classifications, 267 s-level classifications, and 869 third-level classifications. Some POI types in the first-level classifications contain different functional types, and POI types in the third-level classifications are too elaborate and not conducive to data processing. Therefore, we opted to utilize the second-level classification as our standard for classification and removed some POI categories that are easy to interfere with the identification of UFZs, such as shared equipment, ATMs, parking lots, and ticket offices. Consequently, a total of 381,905 POIs were obtained. The acquired POI data were transformed into the WGS84 coordinate system. The spatial distribution of the POI data is shown in Figure 3. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Spectral Band** & **Wavelength (\(\upmu\)m)** & **Spatial Resolution (m)** & **Swath Width (km)** \\ \hline Front-view Pan & 0.45–0.90 & 0.8 & \\ Rear-view Pan & 0.45–0.90 & 0.65 & \\ Blue & 0.45–0.52 & & \(\geq\)20 \\ Green & 0.52–0.59 & 2.6 & \\ Red & 0.63–0.69 & & \\ NIR & 0.77–0.89 & & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Parameters of bi-linear array stereo camera. OpenStreetMap (OSM) is a collaborative project that creates a free editable map database of the world, including vector data such as roads, water systems, lakes, green spaces, and building outlines, which has important reference value for the boundary division and type interpretation of urban functional units.