osmnx下载包含建筑物高度的建筑物信息表
时间: 2024-05-08 14:17:30 浏览: 11
在OSM中,只有少数建筑物有高度信息。因此,如果您需要包含建筑物高度的建筑物信息表,您需要使用其他数据源,例如Lidar数据或航空摄影数据。您可以使用这些数据源创建自己的高度信息表,并将其与OSM数据合并。这可以通过使用Python库如geopandas和pandas来实现。以下是一个简单的例子:
首先,您需要下载Lidar数据或航空摄影数据,并将其转换为高度信息表。您可以使用Python库如PDAL和laspy来实现。以下是一个示例代码:
```python
import pdal
import laspy
import numpy as np
import pandas as pd
pipeline = [
{
"type": "readers.las",
"filename": "path/to/lidar/data.las"
},
{
"type": "filters.range",
"limits": "Classification[2:2]"
},
{
"type": "filters.ferry",
"dimensions": "X,Y,Z",
"value": "Classification",
"mode": "greater"
},
{
"type": "writers.text",
"format": "csv",
"filename": "path/to/output.csv"
}
]
result = pdal.pipeline(pipeline)
data = pd.read_csv("path/to/output.csv", usecols=["X", "Y", "Z"])
data.to_csv("path/to/output.csv", index=False)
```
这个代码将读取Lidar数据,并仅保留分类为2(表示建筑物)的点。然后,它使用ferry filter将点的高度值从Classification字段中提取到Z字段中。最后,它将结果保存为CSV文件。
接下来,您需要将高度信息表与OSM数据合并。以下是一个示例代码:
```python
import osmnx as ox
import pandas as pd
import geopandas as gpd
# download OSM data
place_name = "New York, New York, USA"
graph = ox.graph_from_place(place_name)
# extract building footprints from OSM data
buildings = ox.footprints.footprints_from_place(place_name)
# read height information from CSV file
heights = pd.read_csv("path/to/heights.csv", usecols=["X", "Y", "Z"])
# convert height information to GeoDataFrame
geometry = gpd.points_from_xy(heights["X"], heights["Y"])
heights_gdf = gpd.GeoDataFrame(heights, geometry=geometry)
# spatial join OSM building footprints with height information
buildings_with_heights = gpd.sjoin(buildings, heights_gdf, op="contains")
# merge height information with OSM data
graph_with_heights = ox.buildings.merge_building_heights(graph, buildings_with_heights)
# save graph with height information
ox.save_graphml(graph_with_heights, "path/to/graph_with_heights.graphml")
```
这个代码将下载OSM数据并提取建筑物轮廓。然后,它将高度信息读入Pandas DataFrame中,并将其转换为GeoDataFrame。接下来,它使用空间连接将建筑物轮廓与高度信息表连接起来。最后,它将高度信息与OSM数据合并,并保存带有高度信息的图形。您现在可以使用OSMnx绘制带有建筑物高度的地图。