## 3 Data  
### Data Set Construction  
The data collection area is selected within the orthophoto region of the urban core built-up area, with a total sample coverage of approximately 4231 square kilometers. The original data consist of Google 19-level RGB three-channel civil satellite remote sensing image maps acquired by QGIS software (version 3.38.1), with a spatial resolution of 0.25 m. During the data preprocessing stage, the original satellite images of the four urban core built-up areas are manually cut into uniformly sized tiles of 256 \(\times\) 256 pixels. Ultimately, a total number of 10,640 samples are obtained in the study area, with 80% randomly allocated to the training set and the remaining 20% allocated to the test set [12; 50; 51]. Our data set has been uploaded to a data repository, and the download site is [[https://www.scidb.cn/en/s/yQJFfm](https://www.scidb.cn/en/s/yQJFfm)]([https://www.scidb.cn/en/s/yQJFfm](https://www.scidb.cn/en/s/yQJFfm)) (accessed on 15 May 2024).  
Since most of open source data set does not meet the requirements for relatively fine land classification, the image information of the remote sensing images in our data set was identified through visual interpretation. The land use classification of the data set was divided into 14 categories. The category names are as follows: building, building_greenland, building_street, construction_vacant, greenland, greenland_street, greenland_street_parking, parking, public space, railway, river_lake_square road_street, sport, and street_parking. These 14 categories of land use classification better reflect the characteristics of urban land use in cities in northern China. Some of these categories such as parking, green spaces, rivers, lakes, squares streets, and sports allow for more refined quantitative analyses of the built environment. For example, the greening rate of communities, the accessibility of neighborhoods to blue and green space and sports facilities, the quality of greening in residential neighborhoods and streets, the distribution of parking space, and the occupation of parking in public spaces such as sidewalks can be analyzed. The constructed data set contains remote sensing images from the core built-up areas of Handan, Shijiazhuang, Tangshan, and Xingtai. There are 200 remote sensing images for each category stored in folders named after each category, and each city has 14 folders according to the classification. The data format is TIF. The file naming method is \"city name + serial number\"; for example, one image in Handan data set is named \"handan11120.TIF\", and the classification samples are presented in Table 2.  
The rules for manual classification of the data set images include: defining building, parking, and road as the main classification categories; if the land use classification markers of a category in a tile account for more than two-thirds of the total image area, the land use classification of that tile is determined to be in that category, such as the building category and the parking category; if each of the two land use classification markers in a tile account for half of the image area, the land use classification of that tile is determined to be a mix of two categories, such as the building and green space category and the building and street category; if each of the three land use classification markers in a tile account for one-third of the image area, the land use classification of that tile is determined to be a mix of three categories, such as the green space, street and parking category; and if the land use classification markers in a tile are less than one-quarter of the image area, that category is not considered in the site classification results for that tile.