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license: cc-by-nc-sa-4.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: image
dtype: image
- name: mask
dtype: image
- name: sdf_mask
dtype:
array2_d:
shape:
- 1024
- 1024
dtype: float32
- name: road_network
dtype: image
- name: gps
sequence:
- name: id
dtype: string
- name: longitude
dtype: float32
- name: latitude
dtype: float32
- name: timestamp
dtype: string
- name: speed
dtype: float32
- name: direction
dtype: float32
- name: filename
dtype: string
splits:
- name: train
num_bytes: 5327869524.0
num_examples: 614
- name: test
num_bytes: 1221907723.0
num_examples: 152
download_size: 3125871408
dataset_size: 6549777247.0
tags:
- Satellite_iamge
- Remote_sensing
- GPS_data
- Multi-modal
---
# SDF-Guided Multi-modal Big Data Road Extraction
The source code about special session of PAKDD 2025 paper *"SDF-Guided Multi-modal Big Data Road Extraction"*
## Usage
```bash
pip install -r requirement.txt # install the dependency library
```
```bash
source tr_sz_sdf.sh # run code
```
## Shenzhen dataset
All of our *Shenzhen* dataset is based on the web Mercator projection in the GCJ-02 coordinate system.
### Dataset description
- **train_val/**
- **image/**: contains 614 satellite images (`x_y_sat.png `)
- **mask/**: contains 614 binary mask images (`x_y_mask.png `)
- **mask_sdf_T/**: contains 614 SDF mask images (`x_y_mask.npy `)
- **road_network/** :contains 614 road network images (`x_y_mask.png `)
- **test/**
- **image/**: contains 152 satellite images (`x_y_sat.png `)
- **mask/**: contains 152 mask images (`x_y_mask.png `)
- **mask_sdf_T/**: contains 152 SDF mask images (`x_y_mask.npy `)
- **road_network/** :contains 152 road network images (`x_y_mask.png `)
- **GPS/**
- **taxi/**: contains 766 GPS patch files (`x_y_gps.pkl`). Each stores the GPS records located in the area of input image `x_y_sat.png`
- **coordinates/**: contains `x_y_gps.txt` (web Mercator GCJ-02 format) files, (left up corner, right down corner) <- format
Each input image `image/x_y_sat.png ` is a RGB satellite image of 1024 $\times$ 1024 pixel size. Its corresponding GPS data is stored in file `/GPS/patch/x_y_gps.pkl`, and corresponding mask image is `mask/x_y_mask.png`.
### GPS Data
To save the loading time, we publish the dataset in Python's Pickle format, which can be directly loaded like:
```python
import pandas
import pickle
gps_data = pickle.load(open('dataset_sz_sdf/GPS/taxi/0_6_gps.pkl', 'rb'))
```
**Definition of columns**:
- `id`: Vehicle ID (integer)
- `time`: Timestamp (UNIX format, in second)
- `lat`: Latitude (in pixel coordinate)
- `lon`: Longitude (in pixel coordinate)
- `direction`: Heading (in degree, 0 means the vehicle is heading north or isn't moving)
- `speed`: Speed (in meter per minute)
- `time`: The time stamp.
The `lat`/`lon` are in the gcj02 System.
**Range of sampling**
Coordinate Range of satellite images in Nanshan district
> wgs84 format：\
> Top left corner：113.77477269727868, 22.658708423462986 \
> Lower right corner：114.01655951201688, 22.401131313831055
> web Mercator on GCJ-02 format：\
> TLC：12665921.334966816,2590450.8885846175\
> LRC：12692827.1689232 ,2559417.4551008344
Coordinate Range of road networks in Nanshan district
> wgs84 format：\
> TLC：113.72531536623958, 22.676333371889751640059225977739\
> LRC：114.07037282840729, 22.352754460489630359940774022261
> web Mercator on GCJ-02 format：\
> TLC：12660417.89499784 , 2592578.6326045664\
> LRC：12698827.572095804, 2553607.944832368
Coordinate range of train(satellite) ：
> wgs84 format:\
> TLC：113.77477269727868, 22.658708423462986\
> LRC：114.01655951201688, 22.52994959856712
> web Mercator on GCJ-02 format：\
> TLC：12665921.334966816, 2590450.8885846175\
> LRC：12692827.1689232 , 2574934.17184272595
Coordinate range of test(satellite) ：
> wgs84 format：\
> TLC：113.77477269727868, 22.52994959856712\
> LRC：114.01655951201688, 22.465558186041523
> web Mercator on GCJ-02 format：\
> TLC：12665921.334966816, 2574934.17184272595\
> LRC：12692827.1689232 , 2567175.813471780175
Coordinate range of Nanshan road network (overbold version)：
> web Mercator on GCJ-02 format：\
> TLC：12660417.89499784 , 2592493.9833760057\
> LRC：12698658.366469823, 2553607.944832368 |