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高斯两步移动搜索法(Ga2SFCA)高性能城市公共资源可达性分析工具

Project description

大城智算 · GASFCA

高斯两步移动搜索法(Ga2SFCA)高性能城市公共资源可达性分析工具

项目简介

GASFCA 是一套面向国土空间规划、城市治理与公共服务均等化研究的高性能可达性计算工具。
基于真实路网、高斯距离衰减、Numba 并行加速,提供全流程自动化分析:

数据预处理 → 路网拓扑优化 → 最短路径求解 → 多阈值可达性计算 → IDW 栅格生成 → 分位数可视化。

支持点/面数据自动适配,一键输出矢量、栅格、专题图,适用于公园、医疗、教育、养老等资源布局评估与优化。

核心特点

  • 点/面数据自动兼容:面自动投影、算面积、转中心点
  • 真实路网距离:NetworKit 极速最短路径
  • Numba 并行加速:远快于GIS手动
  • 多阈值批量计算:1000/1500/3000/5000m
  • 高斯距离衰减模型:贴近真实出行规律
  • IDW 生成连续可达性栅格
  • 单图独立分位数可视化:适配偏态数据
  • 一键输出 shp / csv / tif / png

安装

pip install gasfca

## 快速使用

```python
from gasfca import run_gasfca

# 数据路径
supply_shp_path = "supply.shp"
demand_shp_path = "demand.shp"
road_shp_path = "road.shp"

# 参数
supply_field = "value"
demand_field = "value"
d0_list = [1000, 1500, 3000, 5000]
target_crs = 3857
cell_size = 100

# 输出路径
output_shp_path = "result/accessibility.shp"
output_csv_path = "result/accessibility.csv"
output_raster_dir = "result/raster"

# 执行
run_gasfca(
    supply_shp_path=supply_shp_path,
    demand_shp_path=demand_shp_path,
    road_shp_path=road_shp_path,
    supply_field=supply_field,
    demand_field=demand_field,
    d0_list=d0_list,
    target_crs=target_crs,
    output_shp_path=output_shp_path,
    output_csv_path=output_csv_path,
    cell_size=cell_size,
    output_raster_dir=output_raster_dir,
    generate_plots=True,
    plot_n_quantiles=5,
    plot_cmap="RdYlGn_r",
    plot_dpi=300
)

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