Python绘图：在地图上添加小地图
# Python绘图：在地图上添加小地图
在科学研究中，我们经常需要在大范围的地图上添加小地图来突出显示研究区域。本文将介绍如何使用Python的cartopy和matplotlib库来实现这一功能。
## 基本概念
### 什么是小地图（Inset Map）
小地图是一个嵌入在主地图中的小型地图，通常用于：
- **显示研究区域位置**：在大范围地图中标出具体研究区域
- **提供地理背景**：为读者提供地理位置的参考
- **增强地图可读性**：帮助读者更好地理解空间关系
### 应用场景
- **科学论文**：在研究区域图中添加位置示意图
- **数据报告**：在区域分析图中提供全局视角
- **演示文稿**：增强地图的表达效果
## 技术准备
### 所需库
```python
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
import cartopy.feature as cfeature
import numpy as np
from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER
import matplotlib.patches as patches
from matplotlib.patches import Rectangle
import cartopy.io.shapereader as shpreader
```
### 安装依赖
```bash
pip install matplotlib cartopy numpy
# 如果需要额外的地图数据
pip install cartopy[plotting]
```
## 基础实现
### 1. 简单的小地图示例
```python
def create_basic_inset_map():
"""
创建基础的小地图示例
"""
# 创建主图
fig = plt.figure(figsize=(12, 8))
# 主地图 - 中国东部区域
ax_main = fig.add_subplot(111, projection=ccrs.PlateCarree())
ax_main.set_extent([105, 125, 25, 45], ccrs.PlateCarree())
# 添加地图特征
ax_main.add_feature(cfeature.COASTLINE, linewidth=0.8)
ax_main.add_feature(cfeature.BORDERS, linewidth=0.6)
ax_main.add_feature(cfeature.RIVERS, alpha=0.6)
ax_main.add_feature(cfeature.LAKES, alpha=0.6)
# 添加网格
gl = ax_main.gridlines(draw_labels=True, alpha=0.5)
gl.top_labels = False
gl.right_labels = False
gl.xformatter = LONGITUDE_FORMATTER
gl.yformatter = LATITUDE_FORMATTER
# 创建小地图 - 显示整个中国
ax_inset = fig.add_axes([0.02, 0.65, 0.3, 0.3],
projection=ccrs.PlateCarree())
ax_inset.set_extent([70, 140, 10, 55], ccrs.PlateCarree())
# 添加小地图特征
ax_inset.add_feature(cfeature.COASTLINE, linewidth=0.5)
ax_inset.add_feature(cfeature.BORDERS, linewidth=0.4)
ax_inset.add_feature(cfeature.LAND, color='lightgray', alpha=0.5)
ax_inset.add_feature(cfeature.OCEAN, color='lightblue', alpha=0.3)
# 在小地图上标出主地图的范围
rect = patches.Rectangle((105, 25), 20, 20,
linewidth=2, edgecolor='red',
facecolor='none', transform=ccrs.PlateCarree())
ax_inset.add_patch(rect)
# 添加标题
ax_main.set_title('中国东部地区详细地图', fontsize=14, pad=20)
plt.tight_layout()
return fig, ax_main, ax_inset
# 创建地图
fig, ax_main, ax_inset = create_basic_inset_map()
plt.show()
```
### 2. 高级小地图功能
```python
class InsetMapCreator:
"""
小地图创建器类
"""
def __init__(self, figsize=(12, 10)):
self.fig = plt.figure(figsize=figsize)
self.ax_main = None
self.ax_inset = None
def create_main_map(self, extent, projection=ccrs.PlateCarree()):
"""
创建主地图
Parameters:
-----------
extent : list
地图范围 [lon_min, lon_max, lat_min, lat_max]
projection : cartopy projection
地图投影
"""
self.ax_main = self.fig.add_subplot(111, projection=projection)
self.ax_main.set_extent(extent, ccrs.PlateCarree())
# 添加基本地图特征
self.ax_main.add_feature(cfeature.COASTLINE, linewidth=1.0)
self.ax_main.add_feature(cfeature.BORDERS, linewidth=0.8)
self.ax_main.add_feature(cfeature.RIVERS, alpha=0.6)
self.ax_main.add_feature(cfeature.LAKES, alpha=0.6)
self.ax_main.add_feature(cfeature.LAND, color='lightgray', alpha=0.3)
self.ax_main.add_feature(cfeature.OCEAN, color='lightblue', alpha=0.3)
return self.ax_main
def add_inset_map(self, position, inset_extent,
main_extent=None, projection=ccrs.PlateCarree()):
"""
添加小地图
Parameters:
-----------
position : list
小地图位置 [x, y, width, height] (相对坐标)
inset_extent : list
小地图显示范围
main_extent : list
主地图范围（用于在小地图上标注）
projection : cartopy projection
小地图投影
"""
self.ax_inset = self.fig.add_axes(position, projection=projection)
self.ax_inset.set_extent(inset_extent, ccrs.PlateCarree())
# 添加小地图特征
self.ax_inset.add_feature(cfeature.COASTLINE, linewidth=0.5)
self.ax_inset.add_feature(cfeature.BORDERS, linewidth=0.4)
self.ax_inset.add_feature(cfeature.LAND, color='lightgray', alpha=0.5)
self.ax_inset.add_feature(cfeature.OCEAN, color='lightblue', alpha=0.3)
# 标注主地图范围
if main_extent:
lon_min, lon_max, lat_min, lat_max = main_extent
rect = patches.Rectangle((lon_min, lat_min),
lon_max - lon_min,
lat_max - lat_min,
linewidth=2, edgecolor='red',
facecolor='red', alpha=0.3,
transform=ccrs.PlateCarree())
self.ax_inset.add_patch(rect)
return self.ax_inset
def add_gridlines(self, ax, **kwargs):
"""
添加网格线
"""
gl = ax.gridlines(draw_labels=True, alpha=0.5, **kwargs)
gl.top_labels = False
gl.right_labels = False
gl.xformatter = LONGITUDE_FORMATTER
gl.yformatter = LATITUDE_FORMATTER
return gl
def add_scale_bar(self, ax, length_km=100, location='lower right'):
"""
添加比例尺
"""
# 这里是一个简化的比例尺实现
# 实际应用中可能需要更精确的计算
# 根据纬度估算经度距离
lat_center = (ax.get_extent()[2] + ax.get_extent()[3]) / 2
lon_per_km = 1 / (111.32 * np.cos(np.radians(lat_center)))
length_lon = length_km * lon_per_km
# 确定比例尺位置
extent = ax.get_extent()
if location == 'lower right':
x_start = extent[1] - length_lon - 0.5
y_pos = extent[2] + 0.5
elif location == 'lower left':
x_start = extent[0] + 0.5
y_pos = extent[2] + 0.5
else:
x_start = extent[0] + 0.5
y_pos = extent[2] + 0.5
# 绘制比例尺
ax.plot([x_start, x_start + length_lon], [y_pos, y_pos],
'k-', linewidth=3, transform=ccrs.PlateCarree())
ax.text(x_start + length_lon/2, y_pos + 0.2, f'{length_km} km',
ha='center', va='bottom', fontsize=10,
transform=ccrs.PlateCarree())
# 使用示例
def create_advanced_map():
"""
创建高级地图示例
"""
# 创建地图对象
map_creator = InsetMapCreator(figsize=(14, 10))
# 主地图：长三角地区
main_extent = [118, 122, 30, 33]
ax_main = map_creator.create_main_map(main_extent)
# 添加网格
map_creator.add_gridlines(ax_main)
# 添加小地图：中国全图
inset_extent = [70, 140, 10, 55]
ax_inset = map_creator.add_inset_map([0.02, 0.65, 0.3, 0.3],
inset_extent, main_extent)
# 添加比例尺
map_creator.add_scale_bar(ax_main, length_km=50)
# 添加标题
ax_main.set_title('长江三角洲地区地图', fontsize=16, pad=20)
return map_creator.fig
# 创建高级地图
fig = create_advanced_map()
plt.show()
```
## 实际应用案例
### 1. 科研论文中的研究区域图
```python
def create_research_area_map():
"""
创建科研论文用的研究区域地图
"""
fig = plt.figure(figsize=(12, 8))
# 主地图：华南地区
ax_main = fig.add_subplot(111, projection=ccrs.PlateCarree())
main_extent = [108, 118, 20, 26]
ax_main.set_extent(main_extent, ccrs.PlateCarree())
# 添加地形特征
ax_main.add_feature(cfeature.COASTLINE, linewidth=1.2)
ax_main.add_feature(cfeature.BORDERS, linewidth=1.0)
ax_main.add_feature(cfeature.RIVERS, linewidth=0.8, alpha=0.6)
ax_main.add_feature(cfeature.LAKES, alpha=0.6)
# 添加城市点
cities = {
'广州': (113.26, 23.13),
'深圳': (114.06, 22.55),
'香港': (114.17, 22.28),
'珠海': (113.55, 22.27)
}
for city, (lon, lat) in cities.items():
ax_main.plot(lon, lat, 'ro', markersize=8, transform=ccrs.PlateCarree())
ax_main.text(lon + 0.1, lat + 0.1, city, fontsize=10,
transform=ccrs.PlateCarree(),
bbox=dict(boxstyle="round,pad=0.3", facecolor="white", alpha=0.8))
# 添加研究区域框
research_area = patches.Rectangle((113, 22), 2, 2,
linewidth=3, edgecolor='blue',
facecolor='blue', alpha=0.2,
transform=ccrs.PlateCarree())
ax_main.add_patch(research_area)
# 小地图：中国南部
ax_inset = fig.add_axes([0.02, 0.02, 0.35, 0.35],
projection=ccrs.PlateCarree())
ax_inset.set_extent([100, 125, 15, 35], ccrs.PlateCarree())
ax_inset.add_feature(cfeature.COASTLINE, linewidth=0.6)
ax_inset.add_feature(cfeature.BORDERS, linewidth=0.5)
ax_inset.add_feature(cfeature.LAND, color='lightgray', alpha=0.5)
ax_inset.add_feature(cfeature.OCEAN, color='lightblue', alpha=0.3)
# 在小地图上标出主地图范围
main_rect = patches.Rectangle((main_extent[0], main_extent[2]),
main_extent[1] - main_extent[0],
main_extent[3] - main_extent[2],
linewidth=2, edgecolor='red',
facecolor='red', alpha=0.3,
transform=ccrs.PlateCarree())
ax_inset.add_patch(main_rect)
# 添加网格和标签
gl = ax_main.gridlines(draw_labels=True, alpha=0.5)
gl.top_labels = False
gl.right_labels = False
gl.xformatter = LONGITUDE_FORMATTER
gl.yformatter = LATITUDE_FORMATTER
# 添加标题和标注
ax_main.set_title('珠江三角洲研究区域', fontsize=16, pad=20)
# 添加图例
legend_elements = [
plt.Line2D([0], [0], marker='o', color='w', markerfacecolor='red',
markersize=8, label='主要城市'),
patches.Patch(facecolor='blue', alpha=0.2, label='研究区域')
]
ax_main.legend(handles=legend_elements, loc='upper right')
plt.tight_layout()
return fig
# 创建研究区域地图
fig = create_research_area_map()
plt.show()
```
### 2. 气象数据可视化
```python
def create_weather_map_with_inset():
"""
创建带小地图的气象数据可视化
"""
# 模拟气象数据
def generate_sample_data():
lons = np.linspace(110, 120, 50)
lats = np.linspace(30, 40, 40)
lon_grid, lat_grid = np.meshgrid(lons, lats)
# 模拟温度数据
temperature = 20 + 10 * np.sin((lon_grid - 115) * np.pi / 5) * \
np.cos((lat_grid - 35) * np.pi / 5)
return lon_grid, lat_grid, temperature
# 生成数据
lon_grid, lat_grid, temperature = generate_sample_data()
fig = plt.figure(figsize=(14, 10))
# 主地图
ax_main = fig.add_subplot(111, projection=ccrs.PlateCarree())
main_extent = [110, 120, 30, 40]
ax_main.set_extent(main_extent, ccrs.PlateCarree())
# 绘制温度数据
contour = ax_main.contourf(lon_grid, lat_grid, temperature,
levels=20, cmap='RdYlBu_r', alpha=0.8,
transform=ccrs.PlateCarree())
# 添加等值线
contour_lines = ax_main.contour(lon_grid, lat_grid, temperature,
levels=10, colors='black', alpha=0.6,
linewidths=0.8, transform=ccrs.PlateCarree())
ax_main.clabel(contour_lines, inline=True, fontsize=8)
# 添加地理特征
ax_main.add_feature(cfeature.COASTLINE, linewidth=1.0)
ax_main.add_feature(cfeature.BORDERS, linewidth=0.8)
ax_main.add_feature(cfeature.RIVERS, alpha=0.6)
# 添加颜色条
cbar = plt.colorbar(contour, ax=ax_main, orientation='vertical',
pad=0.05, shrink=0.8)
cbar.set_label('温度 (°C)', fontsize=12)
# 小地图
ax_inset = fig.add_axes([0.02, 0.65, 0.25, 0.25],
projection=ccrs.PlateCarree())
ax_inset.set_extent([100, 130, 20, 45], ccrs.PlateCarree())
ax_inset.add_feature(cfeature.COASTLINE, linewidth=0.6)
ax_inset.add_feature(cfeature.BORDERS, linewidth=0.5)
ax_inset.add_feature(cfeature.LAND, color='lightgray', alpha=0.5)
ax_inset.add_feature(cfeature.OCEAN, color='lightblue', alpha=0.3)
# 标注主地图区域
main_rect = patches.Rectangle((main_extent[0], main_extent[2]),
main_extent[1] - main_extent[0],
main_extent[3] - main_extent[2],
linewidth=2, edgecolor='red',
facecolor='red', alpha=0.4,
transform=ccrs.PlateCarree())
ax_inset.add_patch(main_rect)
# 添加网格
gl = ax_main.gridlines(draw_labels=True, alpha=0.5)
gl.top_labels = False
gl.right_labels = False
gl.xformatter = LONGITUDE_FORMATTER
gl.yformatter = LATITUDE_FORMATTER
ax_main.set_title('华中地区气温分布\n2024年1月平均温度', fontsize=14, pad=20)
plt.tight_layout()
return fig
# 创建气象地图
fig = create_weather_map_with_inset()
plt.show()
```
## 高级技巧
### 1. 多个小地图
```python
def create_multiple_inset_maps():
"""
创建包含多个小地图的复合地图
"""
fig = plt.figure(figsize=(16, 12))
# 主地图：东亚地区
ax_main = fig.add_subplot(111, projection=ccrs.PlateCarree())
main_extent = [100, 140, 20, 50]
ax_main.set_extent(main_extent, ccrs.PlateCarree())
ax_main.add_feature(cfeature.COASTLINE)
ax_main.add_feature(cfeature.BORDERS)
ax_main.add_feature(cfeature.LAND, color='lightgray', alpha=0.3)
ax_main.add_feature(cfeature.OCEAN, color='lightblue', alpha=0.3)
# 小地图1：全球视角
ax_inset1 = fig.add_axes([0.02, 0.7, 0.25, 0.25],
projection=ccrs.PlateCarree())
ax_inset1.set_global()
ax_inset1.add_feature(cfeature.COASTLINE, linewidth=0.5)
ax_inset1.add_feature(cfeature.LAND, color='lightgray', alpha=0.5)
ax_inset1.add_feature(cfeature.OCEAN, color='lightblue', alpha=0.3)
# 在全球地图上标出东亚区域
global_rect = patches.Rectangle((main_extent[0], main_extent[2]),
main_extent[1] - main_extent[0],
main_extent[3] - main_extent[2],
linewidth=2, edgecolor='red',
facecolor='red', alpha=0.3,
transform=ccrs.PlateCarree())
ax_inset1.add_patch(global_rect)
ax_inset1.set_title('全球位置', fontsize=10)
# 小地图2：特定区域放大
ax_inset2 = fig.add_axes([0.02, 0.4, 0.25, 0.25],
projection=ccrs.PlateCarree())
detail_extent = [115, 125, 35, 42]
ax_inset2.set_extent(detail_extent, ccrs.PlateCarree())
ax_inset2.add_feature(cfeature.COASTLINE)
ax_inset2.add_feature(cfeature.BORDERS)
ax_inset2.add_feature(cfeature.LAND, color='lightgray', alpha=0.3)
ax_inset2.set_title('华北地区详图', fontsize=10)
# 在主地图上标出详图区域
detail_rect = patches.Rectangle((detail_extent[0], detail_extent[2]),
detail_extent[1] - detail_extent[0],
detail_extent[3] - detail_extent[2],
linewidth=2, edgecolor='blue',
facecolor='blue', alpha=0.2,
transform=ccrs.PlateCarree())
ax_main.add_patch(detail_rect)
# 添加网格
gl = ax_main.gridlines(draw_labels=True, alpha=0.5)
gl.top_labels = False
gl.right_labels = False
gl.xformatter = LONGITUDE_FORMATTER
gl.yformatter = LATITUDE_FORMATTER
ax_main.set_title('东亚地区地图', fontsize=16, pad=20)
plt.tight_layout()
return fig
# 创建多小地图示例
fig = create_multiple_inset_maps()
plt.show()
```
### 2. 交互式小地图
```python
def create_interactive_inset():
"""
创建可交互的小地图（基础版本）
"""
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(16, 8),
subplot_kw={'projection': ccrs.PlateCarree()})
# 主地图
main_extent = [70, 140, 10, 55]
ax1.set_extent(main_extent, ccrs.PlateCarree())
ax1.add_feature(cfeature.COASTLINE)
ax1.add_feature(cfeature.BORDERS)
ax1.add_feature(cfeature.LAND, color='lightgray', alpha=0.3)
ax1.add_feature(cfeature.OCEAN, color='lightblue', alpha=0.3)
ax1.set_title('点击选择区域', fontsize=14)
# 详图
ax2.set_title('选中区域详图', fontsize=14)
# 添加点击事件处理
def on_click(event):
if event.inaxes == ax1:
# 获取点击位置
lon, lat = event.xdata, event.ydata
if lon is not None and lat is not None:
# 设置详图范围（以点击点为中心）
margin = 3 # 度
detail_extent = [lon - margin, lon + margin,
lat - margin, lat + margin]
# 更新详图
ax2.clear()
ax2.set_extent(detail_extent, ccrs.PlateCarree())
ax2.add_feature(cfeature.COASTLINE)
ax2.add_feature(cfeature.BORDERS)
ax2.add_feature(cfeature.RIVERS, alpha=0.6)
ax2.add_feature(cfeature.LAKES, alpha=0.6)
ax2.add_feature(cfeature.LAND, color='lightgray', alpha=0.3)
ax2.set_title(f'详图: {lon:.1f}°E, {lat:.1f}°N', fontsize=14)
# 在主图上显示选中区域
ax1.clear()
ax1.set_extent(main_extent, ccrs.PlateCarree())
ax1.add_feature(cfeature.COASTLINE)
ax1.add_feature(cfeature.BORDERS)
ax1.add_feature(cfeature.LAND, color='lightgray', alpha=0.3)
ax1.add_feature(cfeature.OCEAN, color='lightblue', alpha=0.3)
# 添加选中区域框
rect = patches.Rectangle((detail_extent[0], detail_extent[2]),
detail_extent[1] - detail_extent[0],
detail_extent[3] - detail_extent[2],
linewidth=2, edgecolor='red',
facecolor='red', alpha=0.3,
transform=ccrs.PlateCarree())
ax1.add_patch(rect)
ax1.set_title('点击选择区域（已选中区域以红框标出）', fontsize=14)
plt.draw()
# 绑定点击事件
fig.canvas.mpl_connect('button_press_event', on_click)
return fig
# 创建交互式地图
fig = create_interactive_inset()
plt.show()
```
## 实用函数库
```python
class MapUtils:
"""
地图工具类
"""
@staticmethod
def calculate_extent_from_center(center_lon, center_lat,
width_km, height_km):
"""
根据中心点和尺寸计算地图范围
"""
# 简化计算，实际应用中可能需要更精确的投影计算
lat_per_km = 1 / 111.32
lon_per_km = 1 / (111.32 * np.cos(np.radians(center_lat)))
half_width = (width_km / 2) * lon_per_km
half_height = (height_km / 2) * lat_per_km
return [center_lon - half_width, center_lon + half_width,
center_lat - half_height, center_lat + half_height]
@staticmethod
def add_north_arrow(ax, x=0.95, y=0.95, size=0.05):
"""
添加指北针
"""
# 创建指北针
arrow = patches.FancyArrowPatch((x, y-size), (x, y),
connectionstyle="arc3",
arrowstyle='->',
mutation_scale=20,
color='black',
transform=ax.transAxes)
ax.add_patch(arrow)
ax.text(x+0.01, y-size/2, 'N', fontsize=12, fontweight='bold',
ha='left', va='center', transform=ax.transAxes)
@staticmethod
def add_coordinate_text(ax, lon, lat, text, **kwargs):
"""
在指定坐标添加文本
"""
default_kwargs = {
'fontsize': 10,
'ha': 'center',
'va': 'center',
'bbox': dict(boxstyle="round,pad=0.3",
facecolor="white", alpha=0.8)
}
default_kwargs.update(kwargs)
ax.text(lon, lat, text, transform=ccrs.PlateCarree(),
**default_kwargs)
# 使用工具类的示例
def create_map_with_utils():
"""
使用工具类创建地图
"""
fig = plt.figure(figsize=(12, 10))
# 主地图
ax_main = fig.add_subplot(111, projection=ccrs.PlateCarree())
# 使用工具函数计算范围
center_extent = MapUtils.calculate_extent_from_center(
116.4, 39.9, 500, 400 # 北京为中心，500km x 400km
)
ax_main.set_extent(center_extent, ccrs.PlateCarree())
ax_main.add_feature(cfeature.COASTLINE)
ax_main.add_feature(cfeature.BORDERS)
ax_main.add_feature(cfeature.LAND, color='lightgray', alpha=0.3)
# 添加指北针
MapUtils.add_north_arrow(ax_main)
# 添加标注
MapUtils.add_coordinate_text(ax_main, 116.4, 39.9, '北京')
MapUtils.add_coordinate_text(ax_main, 117.2, 39.1, '天津')
# 添加小地图
ax_inset = fig.add_axes([0.02, 0.65, 0.3, 0.3],
projection=ccrs.PlateCarree())
ax_inset.set_extent([100, 130, 30, 50], ccrs.PlateCarree())
ax_inset.add_feature(cfeature.COASTLINE, linewidth=0.5)
ax_inset.add_feature(cfeature.LAND, color='lightgray', alpha=0.5)
# 在小地图上标出主地图范围
rect = patches.Rectangle((center_extent[0], center_extent[2]),
center_extent[1] - center_extent[0],
center_extent[3] - center_extent[2],
linewidth=2, edgecolor='red',
facecolor='red', alpha=0.3,
transform=ccrs.PlateCarree())
ax_inset.add_patch(rect)
ax_main.set_title('华北地区地图（以北京为中心）', fontsize=14, pad=20)
plt.tight_layout()
return fig
# 创建使用工具类的地图
fig = create_map_with_utils()
plt.show()
```
## 总结
通过本文的介绍，我们学习了如何在Python中创建带有小地图的地图可视化：
### 主要技术要点
1. **基础实现**：使用matplotlib和cartopy创建主地图和小地图
2. **高级功能**：添加比例尺、指北针、网格线等地图元素
3. **实际应用**：科研论文、气象数据可视化等场景
4. **交互功能**：动态更新小地图内容
### 最佳实践
1. **合理布局**：小地图位置不应遮挡主要内容
2. **清晰标注**：用明显的颜色和线条标出研究区域
3. **适当简化**：小地图应突出重点，避免过多细节
4. **一致投影**：确保主地图和小地图使用合适的投影
### 扩展应用
这种技术可以应用于：
- **学术论文**：研究区域位置图
- **数据报告**：区域分析可视化
- **科学演示**：增强地图表达效果
- **Web应用**：交互式地图界面
通过掌握这些技术，您可以创建更加专业和直观的地图可视化作品。
## 参考资源
- [Cartopy官方文档](https://scitools.org.uk/cartopy/docs/latest/)
- [Matplotlib地图绘制教程](https://matplotlib.org/basemap/)
- [地理数据可视化最佳实践](https://geovisualization.github.io/)
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*希望本文对您的地图制作工作有所帮助！如有问题，欢迎在评论区讨论。*