• gps各种地图坐标系转换


    原文地址:https://my.oschina.net/fankun2013/blog/338100

    地图供应商比较多,产生了许多地图坐标。地图坐标正确转换是个问题。在之前开发地图应用的时候发现从WGS84坐标系(GPS)转换成某个地图坐标系都比较困难。然后只能使用地图供应商提供的webservice接口转换。百度也提供了免费的webservice接口(限制并发量)。对于少数点的转换性能还可以,但是对于非常多点的转换压力比较大(使用多线程并行计算).个人感觉比较繁琐,而且很难保证转换的稳定性。

         时间飞逝,百度地图更新了新版本,给我们带来了福音,map API中自带了相关坐标的转换,这就省事多了。但是其它的地图貌似没有提供转换API.怎么办呢?真是高手在民间呀,哪个牛人透露转换的算法呢?估计是和百度相关的牛人吧。下面是对算法的收集和整理。提供java版本。js版本参考:http://www.oschina.net/code/snippet_260395_39205

    这下使用地图转换就比较准确了。

    public class CoordinateConvertUtil {
        private static  double PI         = Math.PI;  
        private static  double AXIS             = 6378245.0;  //
            private static  double OFFSET             = 0.00669342162296594323;  //(a^2 - b^2) / a^2
            private static  double X_PI        = PI * 3000.0 / 180.0;
          
        public static void main(String[] args) {
            // 116.39806876799298,39.90830142538959
            // 116.397826,39.90894374525333
            // 116.3978262189183,39.90894374525333
            String lon = "116.391910";
            String lat = "39.906050";
            lon = "";
            lat = "";
            double [] arr2 = bd092GCJ(39.9151, 116.4039595 );
            System.out.println(arr2[0]+ "," + arr2[1]);
            double [] arr = bd092WGS(39.9151, 116.4039595 );
            System.out.println(arr[0]+ "," + arr[1]);
        }
        
        //GCJ-02=>BD09 火星坐标系=>百度坐标系
        public static double[] gcj2BD09(double glat, double glon){
            double x = glon;
            double y = glat;  
            double[] latlon = new double[2];
            double z = Math.sqrt(x * x + y * y) + 0.00002 * Math.sin(y * X_PI);  
            double theta = Math.atan2(y, x) + 0.000003 * Math.cos(x * X_PI);  
            latlon[0] = z * Math.sin(theta) + 0.006;
            latlon[1] = z * Math.cos(theta) + 0.0065;  
            return latlon;
        }
        
        //BD09=>GCJ-02 百度坐标系=>火星坐标系
        public static double[] bd092GCJ(double glat, double glon){
            double x = glon - 0.0065;
            double y = glat - 0.006;  
            double[] latlon = new double[2];
            double z = Math.sqrt(x * x + y * y) - 0.00002 * Math.sin(y * X_PI);  
            double theta = Math.atan2(y, x) - 0.000003 * Math.cos(x * X_PI);  
            latlon[0] = z * Math.sin(theta);
            latlon[1] = z * Math.cos(theta);  
            return latlon;
        }
        //BD09=>WGS84 百度坐标系=>地球坐标系
        public static double[] bd092WGS(double glat, double glon){
                double[] latlon = bd092GCJ(glat,glon);
                return gcj2WGS(latlon[0],latlon[1]);
            }
            // WGS84=》BD09   地球坐标系=>百度坐标系
            public static double[] wgs2BD09(double wgLat, double wgLon) {  
                double[] latlon = wgs2GCJ(wgLat,wgLon);
                return gcj2BD09(latlon[0],latlon[1]);
            }  
        
        // WGS84=》GCJ02   地球坐标系=>火星坐标系
            public static double[] wgs2GCJ(double wgLat, double wgLon) {  
                double[] latlon  = new double[2];
                if (outOfChina(wgLat, wgLon)){ 
                    latlon[0] = wgLat;  
                    latlon[1] = wgLon;  
                   return latlon;  
                 }  
                double[] deltaD =  delta(wgLat,wgLon);
                latlon[0] = wgLat + deltaD[0];
                latlon[1] = wgLon + deltaD[1];
                return latlon;
            }  
            //GCJ02=>WGS84   火星坐标系=>地球坐标系(粗略)
            public static double[] gcj2WGS(double glat,double glon){
                double[] latlon  = new double[2];
                if (outOfChina(glat, glon)){ 
                    latlon[0] = glat;  
                    latlon[1] = glon;  
                   return latlon;  
                 }  
                double[] deltaD =  delta(glat,glon);
                latlon[0] = glat - deltaD[0];
                latlon[1] = glon - deltaD[1];
                return latlon;
            }
           //GCJ02=>WGS84   火星坐标系=>地球坐标系(精确)
            public static double[] gcj2WGSExactly(double gcjLat,double gcjLon){
                 double initDelta = 0.01;
                 double threshold = 0.000000001;
                 double dLat = initDelta, dLon = initDelta;
                 double mLat = gcjLat - dLat, mLon = gcjLon - dLon;
                 double pLat = gcjLat + dLat, pLon = gcjLon + dLon;
                 double wgsLat, wgsLon, i = 0;
                 while (true) {
                     wgsLat = (mLat + pLat) / 2;
                     wgsLon = (mLon + pLon) / 2;
                     double[] tmp = wgs2GCJ(wgsLat, wgsLon);
                     dLat = tmp[0] - gcjLat;
                     dLon = tmp[1] - gcjLon;
                     if ((Math.abs(dLat) < threshold) && (Math.abs(dLon) < threshold))
                         break;
          
                     if (dLat > 0) pLat = wgsLat; else mLat = wgsLat;
                     if (dLon > 0) pLon = wgsLon; else mLon = wgsLon;
          
                     if (++i > 10000) break;
                 }
                 double[] latlon = new double[2];
                 latlon[0] = wgsLat;
                 latlon[1] = wgsLon;
                 return latlon;
            }
        
            //两点距离
            public static double distance(double latA, double logA, double latB,double  logB){
                int earthR = 6371000;
                double x = Math.cos(latA*Math.PI/180) * Math.cos(latB*Math.PI/180) * Math.cos((logA-logB)*Math.PI/180);
                double y = Math.sin(latA*Math.PI/180) * Math.sin(latB*Math.PI/180);
                double s = x + y;
                if (s > 1)
                    s = 1;
                if (s < -1)
                    s = -1;
                double alpha = Math.acos(s);
                double distance = alpha * earthR;
                return distance;
            }
             
            public static double[] delta(double wgLat, double wgLon){
                 double[] latlng  = new double[2];
                 double dLat = transformLat(wgLon - 105.0, wgLat - 35.0);  
                 double dLon = transformLon(wgLon - 105.0, wgLat - 35.0);  
                 double radLat = wgLat / 180.0 * PI;  
                 double magic = Math.sin(radLat);  
                 magic = 1 - OFFSET * magic * magic;  
                 double sqrtMagic = Math.sqrt(magic);  
                 dLat = (dLat * 180.0) / ((AXIS * (1 - OFFSET)) / (magic * sqrtMagic) * PI);  
                 dLon = (dLon * 180.0) / (AXIS / sqrtMagic * Math.cos(radLat) * PI);  
                 latlng[0] =dLat;
                 latlng[1] =dLon;
                    return latlng;
            }
            
            public static boolean outOfChina(double lat, double lon){  
                if (lon < 72.004 || lon > 137.8347)  
                    return true;  
                if (lat < 0.8293 || lat > 55.8271)  
                    return true;  
                return false;  
            }  
        
            public static double transformLat(double x, double y){  
                double ret = -100.0 + 2.0 * x + 3.0 * y + 0.2 * y * y + 0.1 * x * y + 0.2 * Math.sqrt(Math.abs(x));  
                ret += (20.0 * Math.sin(6.0 * x * PI) + 20.0 * Math.sin(2.0 * x * PI)) * 2.0 / 3.0;  
                ret += (20.0 * Math.sin(y * PI) + 40.0 * Math.sin(y / 3.0 * PI)) * 2.0 / 3.0;  
                ret += (160.0 * Math.sin(y / 12.0 * PI) + 320 * Math.sin(y * PI / 30.0)) * 2.0 / 3.0;  
                return ret;  
            }  
        
            public static double transformLon(double x, double y){  
                double ret = 300.0 + x + 2.0 * y + 0.1 * x * x + 0.1 * x * y + 0.1 * Math.sqrt(Math.abs(x));  
                ret += (20.0 * Math.sin(6.0 * x * PI) + 20.0 * Math.sin(2.0 * x * PI)) * 2.0 / 3.0;  
                ret += (20.0 * Math.sin(x * PI) + 40.0 * Math.sin(x / 3.0 * PI)) * 2.0 / 3.0;  
                ret += (150.0 * Math.sin(x / 12.0 * PI) + 300.0 * Math.sin(x / 30.0 * PI)) * 2.0 / 3.0;  
                return ret;  
            }  
    }
  • 相关阅读:
    MongoDB中聚合工具Aggregate等的介绍与使用
    《PHP7底层设计与源码实现》学习笔记1——PHP7的新特性和源码结构
    数据结构与算法之PHP排序算法(桶排序)
    数据结构与算法之PHP排序算法(快速排序)
    数据结构与算法之PHP排序算法(归并排序)
    数据结构与算法之PHP排序算法(希尔排序)
    数据结构与算法之PHP排序算法(堆排序)
    从关系型数据库到非关系型数据库
    redis在windows下安装和PHP中使用
    PHP-redis中文文档
  • 原文地址:https://www.cnblogs.com/oskyhg/p/8919907.html
Copyright © 2020-2023  润新知