GPS数据Python解析及地图可视化

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发布于 2020-07-20 10:15:23

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发布于 2020-07-20 10:15:23

文章被收录于专栏：数据医生专栏

本篇文章主要介绍如何使用pynmea2库解析传感器的GPS信号，以及如何使用folium库绘制GPS轨迹图。

GPS数据解析

参考资料： NMEA pynmea2

根据NMEA协议，我们从传感器上接收到的GPS经纬度数据格式如下：

例：$GPRMC,024813.640,A,3158.4608,N,11848.3737,E,10.05,324.27,150706,,,A*50
字段0：$GPRMC，语句ID，表明该语句为Recommended Minimum Specific GPS/TRANSIT Data（RMC）推荐最小定位信息
字段1：UTC时间，hhmmss.sss格式
字段2：状态，A=定位，V=未定位
字段3：纬度ddmm.mmmm，度分格式（前导位数不足则补0）
字段4：纬度N（北纬）或S（南纬）
字段5：经度dddmm.mmmm，度分格式（前导位数不足则补0）
字段6：经度E（东经）或W（西经）
字段7：速度，节，Knots
字段8：方位角，度
字段9：UTC日期，DDMMYY格式
字段10：磁偏角，（000 - 180）度（前导位数不足则补0）
字段11：磁偏角方向，E=东W=西
字段12：模式，A=自动，D=差分，E=估测，N=数据无效（3.0协议内容）
字段13：校验值（$与*之间的数异或后的值）

这里以GPRMC为例，GPGGA同理。

根据协议内容，我们可以自己编写Python脚本对GPS数据进行解析。但是，实际上Python已经有现成的库可以调用——pymea2。

推荐下载方式：

pip install pynmea2

下载完成后即可导入包，并通过pynmea2.parse()方法对GPS数据进行解析，示例如下：

import pynmea2

text = "$GNRMC,074733.00,A,2241.28818,N,11358.44210,E,3.866,,070720,,,A*60"
msg = pynmea2.parse(text)

解析结果如下：

原始GPS信号的经纬度采用的是60进制的格式，通过msg.lat和msg.lon就能分别显示维度和经度信息：

而地图常用的格式应该是10进制的，通过msg.latitude和msg.longitude就能分别显示10进制的维度和经度信息：

使用folium绘制经纬度轨迹图

folium-quickstart

通过上面的解析方法，我们已经获取了传感器的维度和经度信息，接下来就能够在地图上进行可视化展示，这里我采用的是Python的folium库。

假设我们最终获取到的一批经纬度数据如下：

/*
* 提示：该行代码过长，系统自动注释不进行高亮。一键复制会移除系统注释 
* locations = [[22.674574, 113.993353], [22.674544, 113.993362], [22.674521, 113.993376], [22.67447, 113.99342], [22.674471, 113.993428], [22.674485, 113.993434], [22.674487, 113.993437], [22.674471, 113.993416], [22.674452, 113.993416], [22.674449, 113.993412], [22.674443, 113.993389], [22.674444, 113.993382], [22.67445, 113.993363], [22.67444, 113.993358], [22.67444, 113.993351], [22.67444, 113.993338], [22.674441, 113.993331], [22.674485, 113.993265], [22.674452, 113.993305], [22.674511, 113.99323], [22.674504, 113.993236], [22.674484, 113.99326], [22.674419, 113.993359], [22.67441, 113.993369], [22.674403, 113.993381], [22.674406, 113.993385], [22.674406, 113.993395], [22.674404, 113.993397], [22.674403, 113.9934], [22.674402, 113.993411], [22.6744, 113.993414], [22.674398, 113.993417], [22.674308, 113.993457], [22.674269, 113.99347], [22.67423, 113.99349], [22.674191, 113.993506], [22.674151, 113.993532], [22.674045, 113.993583], [22.673965, 113.993597], [22.673879, 113.993607], [22.673724, 113.993639], [22.673321, 113.993752], [22.673212, 113.993784], [22.673101, 113.993825], [22.672887, 113.993894], [22.672785, 113.993937], [22.672684, 113.993977], [22.672476, 113.994081], [22.672063, 113.994352], [22.671971, 113.994427], [22.671873, 113.994503], [22.67178, 113.994583], [22.671449, 113.994935], [22.671373, 113.995017], [22.671315, 113.995096], [22.671252, 113.995173], [22.671199, 113.995219], [22.671165, 113.99525], [22.671108, 113.995304], [22.671128, 113.995301], [22.671125, 113.995312], [22.671131, 113.995302], [22.671133, 113.995301], [22.671136, 113.99531], [22.671135, 113.995313], [22.671131, 113.995316], [22.671077, 113.995376], [22.671059, 113.995395], [22.671039, 113.995415], [22.670993, 113.995452], [22.670868, 113.995574], [22.670666, 113.995825], [22.67061, 113.995877], [22.670563, 113.995943], [22.670503, 113.996008], [22.670448, 113.996076], [22.670393, 113.996143], [22.670233, 113.996335], [22.670022, 113.996558], [22.669967, 113.996622], 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114.010189], [22.650174, 114.01019], [22.650174, 114.01019], [22.650175, 114.010185], [22.650177, 114.010184], [22.65018, 114.010183], [22.650181, 114.010184], [22.650179, 114.010183], [22.650175, 114.010181], [22.650164, 114.010177], [22.650164, 114.010168], [22.65016, 114.010171], [22.650156, 114.010171], [22.650077, 114.010223], [22.65005, 114.010245], [22.650019, 114.010266], [22.64999, 114.01029], [22.64996, 114.010309], [22.649917, 114.010341], [22.649892, 114.010353], [22.649874, 114.010367], [22.649844, 114.01039], [22.649637, 114.010561], [22.649569, 114.010614], [22.649493, 114.010679], [22.649349, 114.010807], [22.64928, 114.010869], [22.649211, 114.010927], [22.649142, 114.010986], [22.649075, 114.011046], [22.64888, 114.01122], [22.648835, 114.011255], [22.648791, 114.01129], [22.648697, 114.011371], [22.648469, 114.011552], [22.64841, 114.011602], [22.648349, 114.011651], [22.648288, 114.011697], [22.648226, 114.011744], [22.648162, 114.01179], [22.647882, 114.012002], 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[22.645955, 114.011391], [22.64595, 114.011385], [22.645947, 114.011383], [22.64595, 114.011378], [22.645932, 114.011349], [22.645955999999998, 114.011367], [22.645954, 114.011364], [22.64595, 114.011361], [22.645944, 114.011363], [22.645945, 114.011366], [22.645925, 114.011378], [22.645917, 114.011377], [22.645914, 114.01137], [22.645915, 114.011394], [22.645914, 114.011395], [22.645919, 114.011399], [22.645902, 114.011416], [22.645927, 114.01145], [22.645934, 114.01145], [22.645931, 114.011415], [22.645931, 114.011423], [22.64594, 114.011465], [22.645958, 114.011438], [22.64597, 114.011438], [22.645948, 114.011414], [22.645972, 114.011407], [22.645969, 114.011389], [22.645957, 114.011383], [22.645966, 114.011391], [22.646028, 114.011349], [22.646038, 114.011348], [22.646038, 114.011346], [22.646144, 114.011338], [22.646165, 114.011331], [22.646185, 114.011323], [22.646296, 114.011279], [22.646366, 114.011254], [22.646385, 114.011245], [22.646409, 114.011188], [22.64643, 114.011175], [22.645819, 114.011172], [22.645744, 114.011106], [22.645695, 114.011069], [22.64569, 114.011058], [22.64581, 114.011152], [22.645709, 114.011067], [22.645675, 114.011042], [22.645633, 114.011031], [22.645633, 114.011066], [22.645639, 114.011083], [22.645645000000002, 114.01109], [22.64563, 114.011079], [22.645635, 114.011107], [22.645651, 114.011131], [22.645679, 114.011169], [22.645688, 114.011188], [22.645694, 114.011194], [22.645697, 114.011206], [22.6457, 114.011215], [22.645707, 114.011226], [22.645692, 114.011203], [22.645708, 114.011211], [22.645718, 114.011244], [22.645722, 114.011281]]
*/

注意：顺序为[纬度，经度]。

编写Python函数绘制GPS轨迹图：

def draw_gps(locations, output_path, file_name):
    """
    绘制gps轨迹图
    :param locations: list, 需要绘制轨迹的经纬度信息，格式为[[lat1, lon1], [lat2, lon2], ...]
    :param output_path: str, 轨迹图保存路径
    :param file_name: str, 轨迹图保存文件名
    :return: None
    """
    m = folium.Map(locations[0], zoom_start=15, attr='default')  #中心区域的确定

    folium.PolyLine(    # polyline方法为将坐标用线段形式连接起来
        locations,    # 将坐标点连接起来
        weight=3,  # 线的大小为3
        color='orange',  # 线的颜色为橙色
        opacity=0.8    # 线的透明度
    ).add_to(m)    # 将这条线添加到刚才的区域m内
    
    # 起始点，结束点
    folium.Marker(locations[0], popup='<b>Starting Point</b>').add_to(m)
    folium.Marker(locations[-1], popup='<b>End Point</b>').add_to(m)
    
    m.save(os.path.join(output_path, file_name))  # 将结果以HTML形式保存到指定路径

GPS轨迹图结果：

解决folium国内访问太慢的问题

如果我们直接用浏览器打开生成的HTML文件，有可能会发现网络访问非常缓慢，需要加载大概1分钟才能看到地图显现。我们打开用folium生成的HTML文件就可以看到：

由于生成的HTML文件调用的很多资源都是访问的国外资源，所以在国内打开可能会比较慢。这时候我们可以考虑把这些静态资源下载到本地，然后采用Python读取HTML，修改静态资源路径的方式，把HTML中的css和js路径修改成本地路径，这样就能够极大程度的提高速度。示例如下：

可以看到示例中有一行我没有进行修改，这是因为我在前面绘制地图的时候增加了起始点的绘制，如果把这个css路径改了就会导致无法正常显示起始点（没有下载起始点图标），再加上这个css网络访问起来并不慢，所以我没有进行替换。

<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/leaflet@1.6.0/dist/leaflet.css"/>

修改了静态资源访问路径的HTML，再次打开的速度应该是非常快的，如果地图加载依然比较慢，那就是地图瓦片的网络问题了，而非静态资源的问题。

切换为高德底图

如果觉得folium默认使用的底图太丑，也可以将其修改为国内的高德底图，这样不仅更好看，而且底图的加载速度也会更快。把前面的绘制GPS轨迹代码修改如下：

def draw_gps(locations, output_path, file_name):
    """
    绘制gps轨迹图
    :param locations: list, 需要绘制轨迹的经纬度信息，格式为[[lat1, lon1], [lat2, lon2], ...]
    :param output_path: str, 轨迹图保存路径
    :param file_name: str, 轨迹图保存文件名
    :return: None
    """
    m = folium.Map(locations[0],  # 中心区域的确定
                   zoom_start=15,
                   tiles="http://webrd02.is.autonavi.com/appmaptile?lang=zh_cn&size=1&scale=1&style=7&x={x}&y={y}&z={z}",  # 设置高德底图
                   attr='default')

    folium.PolyLine(    # polyline方法为将坐标用线段形式连接起来
        locations,    # 将坐标点连接起来
        weight=3,  # 线的大小为3
        color='orange',  # 线的颜色为橙色
        opacity=0.8    # 线的透明度
    ).add_to(m)    # 将这条线添加到刚才的区域m内
    
    # 起始点，结束点
    folium.Marker(locations[0], popup='<b>Starting Point</b>').add_to(m)
    folium.Marker(locations[-1], popup='<b>End Point</b>').add_to(m)
    
    m.save(os.path.join(output_path, file_name))  # 将结果以HTML形式保存到指定路径

其实就是设置了folium.Map()方法的tiles参数而已。采用高德底图的GPS轨迹结果如下：