百度墨卡托坐标转化笔记
一、墨卡托坐标转化
调研了python和java多种实现方式的转换，发现有的不符合需求，原因还没找到。
我是用百度地图返回的poi边界（返回的是墨卡托坐标）
转换的原理没有深入研究，直接拿来用的，测试可行，非常感谢https://blog.csdn.net/qq_33734315/article/details/121071650
挺好奇MCBAND,MC2LL 这两个变量是从哪里找到的，还是自己研究出来的，太厉害了。
下面两种实现转换后的经纬度均为百度坐标系
调研的java代码实现
package utils;
import java.io.*;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
/**
* 百度geo返回的结果转换
* 墨卡托坐标转成百度坐标
*/
public class MocatorConvert {
private static final Double[] MCBAND = {12890594.86, 8362377.87, 5591021d, 3481989.83, 1678043.12, 0d};
private static final Double[][] MC2LL = {{1.410526172116255e-8, 0.00000898305509648872, -1.9939833816331, 200.9824383106796, -187.2403703815547, 91.6087516669843, -23.38765649603339, 2.57121317296198, -0.03801003308653, 17337981.2}, {-7.435856389565537e-9, 0.000008983055097726239, -0.78625201886289, 96.32687599759846, -1.85204757529826, -59.36935905485877, 47.40033549296737, -16.50741931063887, 2.28786674699375, 10260144.86}, {-3.030883460898826e-8, 0.00000898305509983578, 0.30071316287616, 59.74293618442277, 7.357984074871, -25.38371002664745, 13.45380521110908, -3.29883767235584, 0.32710905363475, 6856817.37}, {-1.981981304930552e-8, 0.000008983055099779535, 0.03278182852591, 40.31678527705744, 0.65659298677277, -4.44255534477492, 0.85341911805263, 0.12923347998204, -0.04625736007561, 4482777.06}, {3.09191371068437e-9, 0.000008983055096812155, 0.00006995724062, 23.10934304144901, -0.00023663490511, -0.6321817810242, -0.00663494467273, 0.03430082397953, -0.00466043876332, 2555164.4}, {2.890871144776878e-9, 0.000008983055095805407, -3.068298e-8, 7.47137025468032, -0.00000353937994, -0.02145144861037, -0.00001234426596, 0.00010322952773, -0.00000323890364, 826088.5}};
public static void main(String[] args) {
String geo = "4|13139481.25,2796369.48;13139944.08,2796651.95|1-13139481.25,2796439.55,13139533.24,2796369.48,13139572.31,2796398.44,13139925.51,2796431.39,13139944.08,2796444.84,13139801.3,2796651.95,13139481.25,2796439.55;";
String ss = mc2jw(geo);
System.out.println(ss);
Double x = 13139533.24;
Double y = 2796369.48;
Map rs = convertMC2LL(x, y);
System.out.println(rs.values());
}
/**
* 墨卡托坐标转成百度坐标 返回的百度坐标
* @param geo
* @return
*/
public static String mc2jw(String geo) {
//String geo = "4|13517816.2,3597097.8;13527673.6,3607970.0|1-13520242.7,3597248.8,13520242.7,3597399.8,13519636.1,3597399.8,13519636.1,3598607.8,13519484.4,3598607.8,13519484.4,3598758.8,13519029.5,3598758.8,13519029.5,3599060.8,13518574.5,3599060.8,13518574.5,3599211.8,13518271.2,3599211.8,13518271.2,3599815.9,13517816.2,3599815.9,13517816.2,3600268.9,13518119.6,3600268.9,13518119.6,3600570.9,13518271.2,3600570.9,13518271.2,3600872.9,13518574.5,3600872.9,13518574.5,3601023.9,13519181.1,3601023.9,13519181.1,3602533.9,13518877.8,3602533.9,13518877.8,3602986.9,13519332.8,3602986.9,13519332.8,3605100.9,13518574.5,3605100.9,13518574.5,3606611.0,13518422.8,3606611.0,13518422.8,3607064.0,13518574.5,3607064.0,13518574.5,3607366.0,13518877.8,3607366.0,13518877.8,3607819.0,13519332.8,3607819.0,13519332.8,3607970.0,13519787.7,3607970.0,13519787.7,3607064.0,13521152.6,3607064.0,13521152.6,3606460.0,13522062.5,3606460.0,13522062.5,3605856.0,13521910.8,3605856.0,13521910.8,3604345.9,13522669.1,3604345.9,13522669.1,3603288.9,13523730.7,3603288.9,13523730.7,3602533.9,13524185.6,3602533.9,13524185.6,3601023.9,13524337.3,3601023.9,13524337.3,3600721.9,13526157.1,3600721.9,13526157.1,3601174.9,13527218.6,3601174.9,13527218.6,3600419.9,13527370.3,3600419.9,13527370.3,3599513.9,13527673.6,3599513.9,13527673.6,3598758.8,13527218.6,3598758.8,13527218.6,3598305.8,13526612.0,3598305.8,13526612.0,3597097.8,13524943.9,3597097.8,13524943.9,3597550.8,13524792.2,3597550.8,13524792.2,3598154.8,13522517.4,3598154.8,13522517.4,3597701.8,13522214.1,3597701.8,13522214.1,3597550.8,13520697.6,3597550.8,13520697.6,3597097.8,13520242.7,3597097.8;";
List mocatorList = new ArrayList();
if (geo.length() <= 71) {
//没有边界，解析该点坐标
mocatorList = parseJeoPoint(geo);
} else {
//有边界
mocatorList = parseJeo(geo);
}
// 封装板块边界
StringBuilder sb = new StringBuilder();
for (int i = 0; i < mocatorList.size(); i++) {
String[] coordinate = mocatorList.get(i).split("\\#");
if (coordinate.length<2){
continue;
}
// 墨卡托坐标转换为百度经纬度坐标
Map location = convertMC2LL(Double.parseDouble(coordinate[0]), Double.parseDouble(coordinate[1]));
Double lng = location.get("lng");
Double lat = location.get("lat");
String coord = lng + "," + lat;
sb.append(coord);
if (i < mocatorList.size() - 1) {
sb.append(";");
}
}
return sb.toString();
}
/**
* 解析Jeo数据
*
* @param mocator
*/
public static List parseJeo(String mocator) {
List mocatorList = new ArrayList();
if (null == mocator) return null;
/* 拆分数据 */
String[] geos = mocator.split("\\|");
int n = Integer.parseInt(geos[0]);
String center = geos[1];
String polylineMoca = geos[2]; //墨卡托坐标
String[] plm = null;
if (n == 2) {
polylineMoca = "1-" + polylineMoca;
plm = polylineMoca.split("\\;");
String plmstr = "";
for (String str : plm) {
plmstr += str+",";
}
plm = new String[1];
plm[0] = plmstr;
} else {
plm = polylineMoca.split("\\;");
}
/* 获取墨卡托边界 */
String geo = null;
if (n == 4 || n == 2) {
for (int i = 0; i < plm.length; i++) {
String[] geoPaths = plm[i].split("\\-");
if (geoPaths[0].equals("1")) {
geo = geoPaths[1];
}
}
}
// 墨卡托坐标解析
String[] geoPolyline = new String[9999];
try {
geoPolyline = geo.split("\\,");
} catch (Exception e) {
System.out.println(e.getMessage());
}
for (int i = 0; i < geoPolyline.length-1; i += 2) {
mocatorList.add(geoPolyline[i] + "#" + geoPolyline[i + 1]);
}
return mocatorList;
}
/**
* 解析Jeo坐标点的数据
*
* @param mocatorpoint
*/
public static List parseJeoPoint(String mocatorpoint) {
List mocatorList = new ArrayList();
if (null == mocatorpoint) return null;
String str = mocatorpoint.substring(0, mocatorpoint.lastIndexOf("|"));
String str1 = mocatorpoint.substring(str.length() + 1, mocatorpoint.length() - 1);
/* 拆分数据 */
// 墨卡托坐标解析
String[] geoPolyline = str1.split("\\,");
for (int i = 0; i < geoPolyline.length; i += 2) {
mocatorList.add(geoPolyline[i] + "#" + geoPolyline[i + 1]);
}
return mocatorList;
}
/**
* 墨卡托坐标转经纬度坐标
*
* @param x
* @param y
* @return
*/
public static Map convertMC2LL(Double x, Double y) {
Double[] cF = null;
x = Math.abs(x);
y = Math.abs(y);
for (int cE = 0; cE < MCBAND.length; cE++) {
if (y >= MCBAND[cE]) {
cF = MC2LL[cE];
break;
}
}
Map location = converter(x, y, cF);
location.put("lng", location.get("x"));
location.remove("x");
location.put("lat", location.get("y"));
location.remove("y");
return location;
}
private static Map converter(Double x, Double y, Double[] cE) {
Double xTemp = cE[0] + cE[1] * Math.abs(x);
Double cC = Math.abs(y) / cE[9];
Double yTemp = cE[2] + cE[3] * cC + cE[4] * cC * cC + cE[5] * cC * cC * cC + cE[6] * cC * cC * cC * cC + cE[7] * cC * cC * cC * cC * cC + cE[8] * cC * cC * cC * cC * cC * cC;
xTemp *= (x < 0 ? -1 : 1);
yTemp *= (y < 0 ? -1 : 1);
Map location = new HashMap();
location.put("x", xTemp);
location.put("y", yTemp);
return location;
}
}
调研的python实现
MCBAND = [12890594.86, 8362377.87, 5591021, 3481989.83, 1678043.12, 0]
LLBAND = [75, 60, 45, 30, 15, 0]
MC2LL = [[1.410526172116255e-8, 0.00000898305509648872, -1.9939833816331, 200.9824383106796, -187.2403703815547,
91.6087516669843, -23.38765649603339, 2.57121317296198, -0.03801003308653, 17337981.2],
[-7.435856389565537e-9, 0.000008983055097726239, -0.78625201886289, 96.32687599759846, -1.85204757529826,
-59.36935905485877, 47.40033549296737, -16.50741931063887, 2.28786674699375, 10260144.86],
[-3.030883460898826e-8, 0.00000898305509983578, 0.30071316287616, 59.74293618442277, 7.357984074871,
-25.38371002664745, 13.45380521110908, -3.29883767235584, 0.32710905363475, 6856817.37],
[-1.981981304930552e-8, 0.000008983055099779535, 0.03278182852591, 40.31678527705744, 0.65659298677277,
-4.44255534477492, 0.85341911805263, 0.12923347998204, -0.04625736007561, 4482777.06],
[3.09191371068437e-9, 0.000008983055096812155, 0.00006995724062, 23.10934304144901, -0.00023663490511,
-0.6321817810242, -0.00663494467273, 0.03430082397953, -0.00466043876332, 2555164.4],
[2.890871144776878e-9, 0.000008983055095805407, -3.068298e-8, 7.47137025468032, -0.00000353937994,
-0.02145144861037, -0.00001234426596, 0.00010322952773, -0.00000323890364, 826088.5]]
LL2MC = [
[-0.0015702102444, 111320.7020616939, 1704480524535203, -10338987376042340, 26112667856603880, -35149669176653700,
26595700718403920, -10725012454188240, 1800819912950474, 82.5],
[0.0008277824516172526, 111320.7020463578, 647795574.6671607, -4082003173.641316, 10774905663.51142,
-15171875531.51559, 12053065338.62167, -5124939663.577472, 913311935.9512032, 67.5],
[0.00337398766765, 111320.7020202162, 4481351.045890365, -23393751.19931662, 79682215.47186455, -115964993.2797253,
97236711.15602145, -43661946.33752821, 8477230.501135234, 52.5],
[0.00220636496208, 111320.7020209128, 51751.86112841131, 3796837.749470245, 992013.7397791013, -1221952.21711287,
1340652.697009075, -620943.6990984312, 144416.9293806241, 37.5],
[-0.0003441963504368392, 111320.7020576856, 278.2353980772752, 2485758.690035394, 6070.750963243378,
54821.18345352118, 9540.606633304236, -2710.55326746645, 1405.483844121726, 22.5],
[-0.0003218135878613132, 111320.7020701615, 0.00369383431289, 823725.6402795718, 0.46104986909093,
2351.343141331292, 1.58060784298199, 8.77738589078284, 0.37238884252424, 7.45]]
def location_mokatuo(lng, lat): # 百度坐标转百度墨卡托坐标
cE = None
lng = get_loop(lng, -180, 180)
lat = get_range(lat, -74, 74)
for i in range(len(LLBAND)):
if lat >= LLBAND[i]:
cE = LL2MC[i]
break
if cE:
for i in range(len(LLBAND) - 1, 0, -1):
if lat <= -LLBAND[i]:
cE = LL2MC[i]
break
return converter(lng, lat, cE)
def converter(lng, lat, cE):
lngTemp = cE[0] + cE[1] * abs(lng)
cC = abs(lat) / cE[9]
latTemp = cE[2] + cE[3] * cC + cE[4] * cC * cC + cE[5] * cC * cC * cC + cE[6] * cC * cC * cC * cC + cE[
7] * cC * cC * cC * cC * cC + cE[8] * cC * cC * cC * cC * cC * cC
lngTemp *= (-1 if lng < 0 else 1)
latTemp *= (-1 if lat < 0 else 1)
return [lngTemp, latTemp]
def get_loop(lng, min1, max1):
while lng > max1:
lng -= max1 - min1
while lng < min1:
lng += max1 - min1
return lng
def get_range(lat, min1, max1):
if min1:
lat = max(lat, min1)
if max1:
lat = min(lat, max1)
return lat
def mokatuo_location(lng,lat): # 百度墨卡托转换百度坐标
cF = None
lng = abs(lng)
lat = abs(lat)
for i in range(len(MCBAND)):
if lat >= MCBAND[i]:
cF = MC2LL[i]
break
return converter(lng, lat, cF)
if __name__ == '__main__':
print(location_mokatuo(118.03315104440664, 24.498307986743058)) # 经纬度转墨卡托
print(mokatuo_location(13139533.24,2796369.48)) # 墨卡托转经纬度
二、坐标测试用例
墨卡托坐标: 13139533.24,2796369.48
百度: 118.03315104440664, 24.498307986743058
GPS: 118.02167877581007, 24.495393563196547
高德: 118.02657021322973, 24.492638370577403
三、调研资料
http://www.site-digger.com/tools/mct2latlng.html
这个工具里面测试了一下返回的经纬度坐标是百度的坐标系
https://www.cnblogs.com/feffery/p/11023673.html
这个实现用上面的测试用例测试没有通过，不知道是不是墨卡托用到的标准不同导致的？
https://blog.csdn.net/qq_33734315/article/details/121071650
主要是用到了这个大佬的思路和实现，非常感谢