【WP7】判断GPS坐标是否在中国

      由于某些原因,国内地图总会有些偏移。虽说这是个相对偏移,但总会对需要坐标定位的应用造成几百米的漂移。若定位坐标在国外,则不会存在此问题。因此我们需要判别当前坐标是否在国内,然后决定是否进行坐标修正。

      判定坐标是否在国内,有下列几种方法可选:

  1. 通过网络地图接口查询
  2. 根据国家行政边界判定
  3. 根据国家行政边界近似判定

 

方法1,通过网络地图接口查询

      网络接口:http://maps.google.com/maps/api/geocode/xml?latlng=xxx,xxx&sensor=false,其中latlng参数填写的是坐标的经纬度参数。

      例如进行如下调用:http://maps.google.com/maps/api/geocode/xml?latlng=39.829632,117.059326&sensor=false

      返回结果如下:

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<?xml version="1.0" encoding="UTF-8"?>
<GeocodeResponse>
 <status>OK</status>
 <result>
  <type>route</type>
  <formatted_address>274 Provincial Rd, Sanhe, Langfang, Hebei, China</formatted_address>
  <address_component>
   <long_name>274 Provincial Rd</long_name>
   <short_name>S274</short_name>
   <type>route</type>
  </address_component>
  <address_component>
   <long_name>Sanhe</long_name>
   <short_name>Sanhe</short_name>
   <type>sublocality</type>
   <type>political</type>
  </address_component>
  <address_component>
   <long_name>Langfang</long_name>
   <short_name>Langfang</short_name>
   <type>locality</type>
   <type>political</type>
  </address_component>
  <address_component>
   <long_name>Hebei</long_name>
   <short_name>Hebei</short_name>
   <type>administrative_area_level_1</type>
   <type>political</type>
  </address_component>
  <address_component>
   <long_name>China</long_name>
   <short_name>CN</short_name>
   <type>country</type>
   <type>political</type>
  </address_component>
  <geometry>
   <location>
    <lat>39.8483120</lat>
    <lng>117.0741900</lng>
   </location>
   <location_type>APPROXIMATE</location_type>
   <viewport>
    <southwest>
     <lat>39.8292258</lat>
     <lng>117.0728091</lng>
    </southwest>
    <northeast>
     <lat>39.8674069</lat>
     <lng>117.0757736</lng>
    </northeast>
   </viewport>
   <bounds>
    <southwest>
     <lat>39.8292258</lat>
     <lng>117.0728091</lng>
    </southwest>
    <northeast>
     <lat>39.8674069</lat>
     <lng>117.0757736</lng>
    </northeast>
   </bounds>
  </geometry>
 </result>
 <result>
  <type>sublocality</type>
  <type>political</type>
  <formatted_address>Sanhe, Langfang, Hebei, China</formatted_address>
  <address_component>
   <long_name>Sanhe</long_name>
   <short_name>Sanhe</short_name>
   <type>sublocality</type>
   <type>political</type>
  </address_component>
  <address_component>
   <long_name>Langfang</long_name>
   <short_name>Langfang</short_name>
   <type>locality</type>
   <type>political</type>
  </address_component>
  <address_component>
   <long_name>Hebei</long_name>
   <short_name>Hebei</short_name>
   <type>administrative_area_level_1</type>
   <type>political</type>
  </address_component>
  <address_component>
   <long_name>China</long_name>
   <short_name>CN</short_name>
   <type>country</type>
   <type>political</type>
  </address_component>
  <geometry>
   <location>
    <lat>39.9827180</lat>
    <lng>117.0782950</lng>
   </location>
   <location_type>APPROXIMATE</location_type>
   <viewport>
    <southwest>
     <lat>39.8081545</lat>
     <lng>116.7572022</lng>
    </southwest>
    <northeast>
     <lat>40.0850111</lat>
     <lng>117.2599867</lng>
    </northeast>
   </viewport>
   <bounds>
    <southwest>
     <lat>39.8081545</lat>
     <lng>116.7572022</lng>
    </southwest>
    <northeast>
     <lat>40.0850111</lat>
     <lng>117.2599867</lng>
    </northeast>
   </bounds>
  </geometry>
 </result>
 <result>
  <type>locality</type>
  <type>political</type>
  <formatted_address>Langfang, Hebei, China</formatted_address>
  <address_component>
   <long_name>Langfang</long_name>
   <short_name>Langfang</short_name>
   <type>locality</type>
   <type>political</type>
  </address_component>
  <address_component>
   <long_name>Hebei</long_name>
   <short_name>Hebei</short_name>
   <type>administrative_area_level_1</type>
   <type>political</type>
  </address_component>
  <address_component>
   <long_name>China</long_name>
   <short_name>CN</short_name>
   <type>country</type>
   <type>political</type>
  </address_component>
  <geometry>
   <location>
    <lat>39.5380470</lat>
    <lng>116.6837520</lng>
   </location>
   <location_type>APPROXIMATE</location_type>
   <viewport>
    <southwest>
     <lat>39.4355307</lat>
     <lng>116.5841675</lng>
    </southwest>
    <northeast>
     <lat>39.6029123</lat>
     <lng>116.8444061</lng>
    </northeast>
   </viewport>
   <bounds>
    <southwest>
     <lat>38.4703170</lat>
     <lng>116.1166769</lng>
    </southwest>
    <northeast>
     <lat>40.0850111</lat>
     <lng>117.2599867</lng>
    </northeast>
   </bounds>
  </geometry>
 </result>
 <result>
  <type>administrative_area_level_1</type>
  <type>political</type>
  <formatted_address>Hebei, China</formatted_address>
  <address_component>
   <long_name>Hebei</long_name>
   <short_name>Hebei</short_name>
   <type>administrative_area_level_1</type>
   <type>political</type>
  </address_component>
  <address_component>
   <long_name>China</long_name>
   <short_name>CN</short_name>
   <type>country</type>
   <type>political</type>
  </address_component>
  <geometry>
   <location>
    <lat>38.0370570</lat>
    <lng>114.4686650</lng>
   </location>
   <location_type>APPROXIMATE</location_type>
   <viewport>
    <southwest>
     <lat>36.0482067</lat>
     <lng>113.4653687</lng>
    </southwest>
    <northeast>
     <lat>42.6197178</lat>
     <lng>119.8542560</lng>
    </northeast>
   </viewport>
   <bounds>
    <southwest>
     <lat>36.0482067</lat>
     <lng>113.4653687</lng>
    </southwest>
    <northeast>
     <lat>42.6197178</lat>
     <lng>119.8542560</lng>
    </northeast>
   </bounds>
  </geometry>
 </result>
 <result>
  <type>country</type>
  <type>political</type>
  <formatted_address>China</formatted_address>
  <address_component>
   <long_name>China</long_name>
   <short_name>CN</short_name>
   <type>country</type>
   <type>political</type>
  </address_component>
  <geometry>
   <location>
    <lat>35.8616600</lat>
    <lng>104.1953970</lng>
   </location>
   <location_type>APPROXIMATE</location_type>
   <viewport>
    <southwest>
     <lat>18.1535216</lat>
     <lng>73.4994137</lng>
    </southwest>
    <northeast>
     <lat>53.5609740</lat>
     <lng>134.7728100</lng>
    </northeast>
   </viewport>
   <bounds>
    <southwest>
     <lat>18.1535216</lat>
     <lng>73.4994137</lng>
    </southwest>
    <northeast>
     <lat>53.5609740</lat>
     <lng>134.7728100</lng>
    </northeast>
   </bounds>
  </geometry>
 </result>
</GeocodeResponse>

      查询结果各字段的含义可以参考Google Map API的Reverse Geocoding (Address Lookup)章节。简化后可以直接判断返回的字符串中是否存在“<short_name>CN</short_name>”作为判定所查询坐标是否在中国的依据。

 

方法2,根据国家行政边界判定

      由于国家行政边界是由多个简单多边形组成的。对多个多边形进行命中测试 (Hit Testing),只要其中一个多边形测试成功,则表示整个命中测试成功。但多边形的命中测试有些麻烦,更简单的方法是判别点是否在多边形内(Point in polygon(PIP))。这些算法中简单高效的莫过于是光线投射算法 (Ray casting algorithm)

      光线投射算法的要义是:在二维空间的任意一点射出一条射线,射线穿过多边形边界奇数次则这个点在多边形内,否则在多边形外。此方法适用于复杂多边形。实现此算法往往会限制射线的方向是向右的,这样的好处是简化了许多计算。此算法的一个实现参考1987年Paul Bourke教授所写“Determining if a point lies on the interior of a polygon”的Solution 1。

      在 Windows Phone 7 中的实现,首先需要获取到国家行政边界的WGS84坐标数据。Alexey Strakh(链接有恶意软件警告)所开发的gMaps应用中包含了此边界数据。因此,自己可以把数据抠出来。抠出的数据由四部分组成我国的行政边界:大陆、台湾省、海南省、崇明岛。此数据相对来说比较准确,但是边界附近误差较大。每次判别坐标是否在此区域内的计算次数较多,大约需要几百次的几何计算。

      此方法的实现代码如下:

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#region polygon
 
List<Point[]> polygon = new List<Point[]>();
 
private void InitPolygon()
{
    polygon.Add(new Point[]  //Mainland
    {
        new Point(27.32083, 88.91693),
        new Point(27.54243, 88.76464),
        new Point(28.00805, 88.83575),
        new Point(28.1168, 88.62435),
        new Point(27.86605, 88.14279),
        new Point(27.82305, 87.19275),
        new Point(28.11166, 86.69527),
        new Point(27.90888, 86.45137),
        new Point(28.15805, 86.19769),
        new Point(27.88625, 86.0054),
        new Point(28.27916, 85.72137),
        new Point(28.30666, 85.11095),
        new Point(28.59104, 85.19518),
        new Point(28.54444, 84.84665),
        new Point(28.73402, 84.48623),
        new Point(29.26097, 84.11651),
        new Point(29.18902, 83.5479),
        new Point(29.63166, 83.19109),
        new Point(30.06923, 82.17525),
        new Point(30.33444, 82.11123),
        new Point(30.385, 81.42623),
        new Point(30.01194, 81.23221),
        new Point(30.20435, 81.02536),
        new Point(30.57552, 80.207),
        new Point(30.73374, 80.25423),
        new Point(30.96583, 79.86304),
        new Point(30.95708, 79.55429),
        new Point(31.43729, 79.08082),
        new Point(31.30895, 78.76825),
        new Point(31.96847, 78.77075),
        new Point(32.24304, 78.47594),
        new Point(32.5561, 78.40595),
        new Point(32.63902, 78.74623),
        new Point(32.35083, 78.9711),
        new Point(32.75666, 79.52874),
        new Point(33.09944, 79.37511),
        new Point(33.42863, 78.93623),
        new Point(33.52041, 78.81387),
        new Point(34.06833, 78.73581),
        new Point(34.35001, 78.98535),
        new Point(34.6118, 78.33707),
        new Point(35.28069, 78.02305),
        new Point(35.49902, 78.0718),
        new Point(35.50133, 77.82393),
        new Point(35.6125, 76.89526),
        new Point(35.90665, 76.55304),
        new Point(35.81458, 76.18061),
        new Point(36.07082, 75.92887),
        new Point(36.23751, 76.04166),
        new Point(36.66343, 75.85984),
        new Point(36.73169, 75.45179),
        new Point(36.91156, 75.39902),
        new Point(36.99719, 75.14787),
        new Point(37.02782, 74.56543),
        new Point(37.17, 74.39089),
        new Point(37.23733, 74.91574),
        new Point(37.40659, 75.18748),
        new Point(37.65243, 74.9036),
        new Point(38.47256, 74.85442),
        new Point(38.67438, 74.35471),
        new Point(38.61271, 73.81401),
        new Point(38.88653, 73.70818),
        new Point(38.97256, 73.85235),
        new Point(39.23569, 73.62005),
        new Point(39.45483, 73.65569),
        new Point(39.59965, 73.95471),
        new Point(39.76896, 73.8429),
        new Point(40.04202, 73.99096),
        new Point(40.32792, 74.88089),
        new Point(40.51723, 74.8588),
        new Point(40.45042, 75.23394),
        new Point(40.64452, 75.58284),
        new Point(40.298, 75.70374),
        new Point(40.35324, 76.3344),
        new Point(41.01258, 76.87067),
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    polygon.Add(new Point[]  //Taiwan
    {
        new Point(25.13474, 121.4441),
        new Point(25.28361, 121.5632),
        new Point(25.00722, 122.0004),
        new Point(24.85028, 121.8182),
        new Point(24.47638, 121.8397),
        new Point(23.0875, 121.3556),
        new Point(21.92791, 120.7196),
        new Point(22.31277, 120.6103),
        new Point(22.54044, 120.3071),
        new Point(23.04437, 120.0539),
        new Point(23.61708, 120.1112),
        new Point(25.00166, 121.0017),
        new Point(25.13474, 121.4441)
    });
    polygon.Add(new Point[]  //Hainan
    {
        new Point(19.52888, 110.855),
        new Point(19.16761, 110.4832),
        new Point(18.80083, 110.5255),
        new Point(18.3852, 110.0503),
        new Point(18.39152, 109.7594),
        new Point(18.19777, 109.7036),
        new Point(18.50562, 108.6871),
        new Point(19.28028, 108.6283),
        new Point(19.76, 109.2939),
        new Point(19.7236, 109.1653),
        new Point(19.89972, 109.2572),
        new Point(19.82861, 109.4658),
        new Point(19.99389, 109.6108),
        new Point(20.13361, 110.6655),
        new Point(19.97861, 110.9425),
        new Point(19.63829, 111.0215),
        new Point(19.52888, 110.855)
    });
    polygon.Add(new Point[]  //Chongming
    {
        new Point(31.80054, 121.2039),
        new Point(31.49972, 121.8736),
        new Point(31.53111, 121.5464),
        new Point(31.80054, 121.2039)
    });
}
private bool IsInsideChina(GeoCoordinate positionToCheck)
{
    if (positionToCheck == null || positionToCheck.IsUnknown)
        return false;
    return polygon.Any(s => IsInsidePolygon(s, positionToCheck.Latitude, positionToCheck.Longitude));
}
private bool IsInsidePolygon(Point[] poly, double x, double y)
{
    var index = 0;
    var inside = false;
    var prePoint = poly[0];
    for (index = 1; index < poly.Length; index++)
    {
        var nextPoint = poly[index];
        if (y > Math.Min(prePoint.Y, nextPoint.Y)
            && y <= Math.Max(prePoint.Y, nextPoint.Y)
            && x <= Math.Max(prePoint.X, nextPoint.X)
            && prePoint.Y != nextPoint.Y)
        {
            double xinters = (y - prePoint.Y) * (nextPoint.X - prePoint.X) / (nextPoint.Y - prePoint.Y) + prePoint.X;
            if (prePoint.X == nextPoint.X || x <= xinters)
                inside ^= true;
        }
        prePoint = nextPoint;
    }
    return inside;
}
 
private void MainPage_Loaded(object sender, RoutedEventArgs e)
{
    InitPolygon();
    foreach (var points in polygon)
    {
        var poly = new MapPolyline();
        poly.Locations = new LocationCollection();
        for (int i = 0; i < points.Length; i++)
        {
            poly.Locations.Add(new GeoCoordinate(points[i].X, points[i].Y));
        }
        poly.Stroke = new SolidColorBrush(Colors.Red);
        myMap.Children.Add(poly);
    }
    myMap.SetView(new GeoCoordinate(39.4916649164344, 108.745576123357), 3.7090892722116307);
}
 
#endregion

方法3,根据国家行政边界近似判定

      有时候需要一种快速的方法判定,这种快速判定的方法是从Nokia Maps中挖掘出来的。基本思路是:把整个行政区域划分为几个小的矩形,然后再排除掉一些矩形区域。只要一个点在限定的区域内,并且不在排除的区域内,则判定成功,否则失败。下图中蓝色区域为限定区域,红色区域为排除区域。

此方法的实现代码如下:

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#region rectangle
 
private class Rectangle
{
    public double West;
    public double North;
    public double East;
    public double South;
    public Rectangle(double latitude1, double longitude1, double latitude2, double longitude2)
    {
        this.West = Math.Min(longitude1, longitude2);
        this.North = Math.Max(latitude1, latitude2);
        this.East = Math.Max(longitude1, longitude2);
        this.South = Math.Min(latitude1, latitude2);
    }
}
 
private static Rectangle[] region = new Rectangle[]
{
    new Rectangle(49.220400, 079.446200, 42.889900, 096.330000),
    new Rectangle(54.141500, 109.687200, 39.374200, 135.000200),
    new Rectangle(42.889900, 073.124600, 29.529700, 124.143255),
    new Rectangle(29.529700, 082.968400, 26.718600, 097.035200),
    new Rectangle(29.529700, 097.025300, 20.414096, 124.367395),
    new Rectangle(20.414096, 107.975793, 17.871542, 111.744104),
 
};
private static Rectangle[] exclude = new Rectangle[]
{
    new Rectangle(25.398623, 119.921265, 21.785006, 122.497559),
    new Rectangle(22.284000, 101.865200, 20.098800, 106.665000),
    new Rectangle(21.542200, 106.452500, 20.487800, 108.051000),
    new Rectangle(55.817500, 109.032300, 50.325700, 119.127000),
    new Rectangle(55.817500, 127.456800, 49.557400, 137.022700),
    new Rectangle(44.892200, 131.266200, 42.569200, 137.022700),
};
 
public static bool IsInsideChina(GeoCoordinate pos)
{
    for (int i = 0; i < region.Length; i++)
    {
        if (InRectangle(region[i], pos))
        {
            for (int j = 0; j < exclude.Length; j++)
            {
                if (InRectangle(exclude[j], pos))
                {
                    return false;
                }
            }
            return true;
        }
    }
    return false;
}
 
private static bool InRectangle(Rectangle rect, GeoCoordinate pos)
{
    return rect.West <= pos.Longitude && rect.East >= pos.Longitude && rect.North >= pos.Latitude && rect.South <= pos.Latitude;
}
 
private void MainPage_Loaded(object sender, RoutedEventArgs e)
{
    DrawRect(region, new SolidColorBrush(Colors.Blue));
    DrawRect(exclude, new SolidColorBrush(Colors.Red));
    myMap.SetView(new GeoCoordinate(39.4916649164344, 108.745576123357), 3.7090892722116307);
}
 
private void DrawRect(Rectangle[] rects, SolidColorBrush brush)
{
    foreach (var rect in rects)
    {
        var poly = new MapPolyline();
        poly.Locations = new LocationCollection();
        poly.Locations.Add(new GeoCoordinate(rect.North, rect.West));
        poly.Locations.Add(new GeoCoordinate(rect.North, rect.East));
        poly.Locations.Add(new GeoCoordinate(rect.South, rect.East));
        poly.Locations.Add(new GeoCoordinate(rect.South, rect.West));
        poly.Locations.Add(new GeoCoordinate(rect.North, rect.West));
        poly.Stroke = brush;
        myMap.Children.Add(poly);
    }
}
 
#endregion

 

      这几种方法的比较

  备注
方法1
通过网络地图接口查询
简单、准确
信息量大
速度慢
依赖网络
可用Google、Baidu地图接口
方法2
根据国家行政边界判定
准确 代码相对较多
判别计算次数较多
陆地边界数据误差较大
方法和数据从gMaps中挖掘
方法3
根据国家行政边界近似判定
快速
相对准确
边界误差较大 方法和数据从Nokia Maps中挖掘

 

PS:你可能会问,在方法3中为什么把台湾给排除掉了,这是因为所谓的坐标偏移对台湾地区不适用。对于香港澳门地区,视情况需要单独判定。

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