Python Folium地理信息可视化案例
0、背景
在研究、挖掘GPS位置数据、轨迹数据的过程中，地理信息的可视化展示是非常关键的一步。
folium是js上著名的地理信息可视化库leaflet.js为Python提供的接口，通过它，我们可以通过在Python端编写代码操纵数据，来调用leaflet的相关功能，基于内建的osm或自行获取的osm资源和地图原件进行地理信息内容的可视化，以及制作优美的可交互地图。[1]
1、Folium官方文档、官方案例
folium documentation:
https://python-visualization.github.io/folium/
folium examples:
https://nbviewer.jupyter.org/github/python-visualization/folium/tree/master/examples/
2、各类基于Folium包的地图类型
2.1 Density Map
def density_map(self, all_data):
lat = np.array(all_data["lat"][0:len(all_data)])
lon = np.array(all_data["lon"][0:len(all_data)])
# duration is not essential
columns_list = all_data.columns()
if 'duration' in columns_list:
duration = np.array(all_data["duration"][0:len(all_data)], dtype=float)
new_data = [[lat[i], lon[i], duration[i]] for i in range(len(all_data))]
else:
new_data = [[lat[i], lon[i]] for i in range(len(all_data))]
density_map = folium.Map(location=[all_data['lat'].mean(), all_data['lon'].mean()],
zoom_start=12,
tiles='http://webrd02.is.autonavi.com/appmaptile?lang=zh_cn&size=1&scale=1&style=8&x={x}&y={y}&z={z}',
attr="http://ditu.amap.com/"
)
HeatMap(new_data, radius=20).add_to(density_map)
#blur=15, gradient={0.4: 'blue', 0.65: 'lime', 1: 'red'}
return density_map
folium.map参数:https://python-visualization.github.io/folium/modules.html#module-folium.map
location：tuple或list类型输入，用于控制初始地图中心点的坐标，格式为(纬度，经度)或[纬度，经度]，默认为None
width：int型或str型，int型时，传入的是地图宽度的像素值；str型时，传入的是地图宽度的百分比，形式为'xx%'。默认为'100%'
height：控制地图的高度，格式同width
tiles：str型，用于控制绘图调用的地图样式，默认为'OpenStreetMap'，也有一些其他的内建地图样式；也可以传入'None'来绘制一个没有风格的朴素地图，或传入一个URL来使用其它的自选osm
可选的样式包括：
”OpenStreetMap”
”Stamen Terrain”, “Stamen Toner”, “Stamen Watercolor”
”CartoDB positron”, “CartoDB dark_matter”
”Mapbox Bright”, “Mapbox Control Room” (Limited zoom)
”Cloudmade” (Must pass API key)
”Mapbox” (Must pass API key)
max_zoom：int型，控制地图可以放大程度的上限，默认为18
attr：str型，当在tiles中使用自选URL内的osm时使用，用于给自选osm命名
control_scale：bool型，控制是否在地图上添加比例尺，默认为False即不添加
no_touch：bool型，控制地图是否禁止接受来自设备的触控事件譬如拖拽等，默认为False，即不禁止
Heatmap Parameters
-
data (list of points of the form [lat, lng] or [lat, lng, weight]) – The points you want to plot. You can also provide a numpy.array of shape (n,2) or (n,3).
-
name (string, default None) – The name of the Layer, as it will appear in LayerControls.
-
min_opacity (default 1.) – The minimum opacity the heat will start at.
-
max_zoom (default 18) – Zoom level where the points reach maximum intensity (as intensity scales with zoom), equals maxZoom of the map by default
-
max_val (float, default 1.) – Maximum point intensity
-
radius (int, default 25) – Radius of each “point” of the heatmap
-
blur (int, default 15) – Amount of blur
-
gradient (dict, default None) – Color gradient config. e.g. {0.4: ‘blue’, 0.65: ‘lime’, 1: ‘red’}
-
overlay (bool, default True) – Adds the layer as an optional overlay (True) or the base layer (False).
-
control (bool, default True) – Whether the Layer will be included in LayerControls.
-
show (bool, default True) – Whether the layer will be shown on opening (only for overlays).
2.2 Line Map
def line_map(self, all_data):
line_map = folium.Map(location=[all_data['lat'].mean(), all_data['lon'].mean()],
zoom_start=12,
tiles='Stamen Terrain',
attr="http://ditu.amap.com/")
route = []
for name, row in all_data.iterrows():
route.append([row["lat"], row["lon"]])
folium.PolyLine(route,
weight=5, # 粗细
opacity=0.8, # 透明度
color='orange').add_to(line_map)
return line_mapfolium.PolyLine 参数：
weight：route粗细
opacity：透明度
2.3 Plot Map （结合DBSCAN聚类的聚类结果展示）
def plot_map(self, all_data):
plot_map = folium.Map(location=[all_data['lat'].mean(), all_data['lon'].mean()],
zoom_start=10,
tiles='http://webrd02.is.autonavi.com/appmaptile?lang=zh_cn&size=1&scale=1&style=8&x={x}&y={y}&z={z}',
attr="http://ditu.amap.com/")
color = ['#F0EDF9', '#E2DBF3', '#D3CAEE', '#B7A6E2', '#A895DD', '#9A83D7', '#8C71D1', '#7D60CC', '#6F4EC6',
'#613DC1', '#5938B0', '#50329E', '#472D8D', '#3E277B', '#35226A', '#2D1C58', '#241747', '#1B1135',
'#F0EDF9', '#E2DBF3', '#D3CAEE', '#C5B8E8', '#B7A6E2', '#A895DD', '#9A83D7', '#8C71D1', '#7D60CC',
'#6F4EC6', '#613DC1', '#5938B0', '#50329E', '#472D8D', '#3E277B', '#35226A', '#2D1C58', '#241747',
'#1B1135'] # 37种
for name, row in all_data.iterrows():
if int(row['classlabel']) == -1:
folium.Circle(radius=20, location=[row["lat"], row["lon"]], popup="离群--停车点:{0}".format(name),
color='black', fill=True, fill_color='black').add_to(plot_map)
else:
i = int(row['classlabel'])
folium.Circle(radius=20, location=[row["lat"], row["lon"]], popup="{0}类--停车点:{1}".format(i, name),
color=color[i], fill=True, fill_color=color[i]).add_to(plot_map)
return plot_map
参考资料
[1]https://www.cnblogs.com/feffery/p/9282808.html
[2]色域表供参考https://www.sioe.cn/yingyong/yanse-rgb-16/ by https://blog.csdn.net/junshan2009/article/details/87000143