将 Matplotlib 的填充等高线图 (contourf_plot) 转换为 GeoJSON

Question

我正在开发一个项目，在 Google Colab 环境中使用 Matplotlib 中的 plt.contourf 成功生成填充等高线图。现在，我正在尝试将这些填充的轮廓多边形转换为 GeoJSON，以便与 Folium 无缝集成。

import numpy as np
import folium
from folium import plugins
import matplotlib.pyplot as plt
from matplotlib.colors import to_hex, Normalize

# Specify the URL of the NetCDF file
url = "https://www.star.nesdis.noaa.gov/socd/mecb/sar/AKDEMO_products/APL_winds/tropical/2024/SH052024_BELAL/STAR_SAR_20240116013937_SH052024_05S_MERGED_FIX_3km.nc"

# Download the NetCDF file content
response = requests.get(url)
nc_content = BytesIO(response.content)
# Open the NetCDF file using xarray
dataset = xr.open_dataset(nc_content)

# Access the 'sar_wind' variable
sar_wind = dataset['sar_wind'].values

# Access the 'latitude' and 'longitude' variables
latitude = dataset['latitude'].values
longitude = dataset['longitude'].values
# Set iso values for filled contours
iso_values_filled = np.linspace(np.min(sar_wind), np.max(sar_wind), 11)  # One extra value for filling the background

# Create a filled contour plot
contourf_plot = plt.contourf(longitude, latitude, sar_wind, levels=iso_values_filled, cmap='viridis')

# Convert filled contour polygons to GeoJSON
geojson_data_polygon = {"type": "FeatureCollection", "features": []}

# Normalize iso values for colormap mapping
norm = Normalize(vmin=np.min(iso_values_filled), vmax=np.max(iso_values_filled))

for level, collection in zip(iso_values_filled, contourf_plot.collections):
    for path in collection.get_paths():
        coordinates = path.vertices.tolist()
        # Close the polygon by repeating the first vertex
        coordinates.append(coordinates[0])
        color_hex = to_hex(plt.cm.viridis(norm(level)))  # Map normalized iso value to colormap
        geojson_data_polygon["features"].append({
            "type": "Feature",
            "geometry": {
                "type": "Polygon",
                "coordinates": [coordinates]
            },
            "properties": {
                "level": level,
                "color": color_hex
            }
        })

# Create a Folium map centered on the average latitude and longitude
center_lat, center_lon = np.mean(latitude), np.mean(longitude)
mymap_polygon = folium.Map(location=[center_lat, center_lon], zoom_start=8)

# Add filled contour polygons as GeoJSON overlay with colored areas
folium.GeoJson(
    geojson_data_polygon,
    style_function=lambda feature: {
        'fillColor': feature['properties']['color'],
        'color': feature['properties']['color'],
        'weight': 2,
        'fillOpacity': 0.7
    }
).add_to(mymap_polygon)

# Display the map with filled contour polygons
mymap_polygon

问题：

contourf_plot 给出了这张图，它是期望的结果。

但是大叶可以：

我们可以看到多边形没有构建。

目标： 我的目标是将轮廓图的填充轮廓多边形转换为 GeoJSON 格式，以便我可以在 Folium 中显示它们。

Answer 1

如果您在第一个图形上绘制等高线，您会发现等高线排列不正确。 您需要处理轮廓坐标，我建议使用geojsoncontour。

只需将

contourf_plot = ...

行后面的代码更改为 :

import geojsoncontour
import branca

# Create geogson strings
geojson = geojsoncontour.contourf_to_geojson(
    contourf=contourf_plot,
    min_angle_deg=3.0,
    ndigits=5,
    stroke_width=1,
    fill_opacity=0.7)

# Normalize iso values for colormap mapping
norm = Normalize(vmin=np.min(iso_values_filled), vmax=np.max(iso_values_filled))
# Covert float to hex colors
color_hex = []
for level in iso_values_filled: 
    color_hex.append( to_hex(plt.cm.viridis(norm(level))))

# Create a Folium map centered on the average latitude and longitude
center_lat, center_lon = np.mean(latitude), np.mean(longitude)
mymap_polygon = folium.Map(location=[center_lat, center_lon], zoom_start=8)

# Creat colormap
cm = branca.colormap.LinearColormap(color_hex)

# Add filled contour polygons as GeoJSON overlay with colored areas
folium.GeoJson(
    geojson,
    style_function=lambda x: {
        'color':     x['properties']['stroke'],
        'weight':    x['properties']['stroke-width'],
        'fillColor': x['properties']['fill'],
        'fillOpacity':   0.7,
    }).add_to(mymap_polygon)

# Update color map 
mymap_polygon.add_child(cm)

你将会得到结果

mymap_polygon

: