参考文档：
http://blog.csdn.net/wangxiafghj/article/details/9014363geohash 算法原理及实现方式http://blog.charlee.li/geohash-intro/ geohash：用字符串实现附近地点搜索
http://blog.sina.com.cn/s/blog_7c05385f0101eofb.html 查找附近点--Geohash方案讨论
http://www.wubiao.info/372 查找附近的xxx 球面距离以及Geohash方案探讨
http://en.wikipedia.org/wiki/Haversine_formula Haversine formula球面距离公式
http://www.codecodex.com/wiki/Calculate_Distance_Between_Two_Points_on_a_Globe 球面距离公式代码实现
http://developer.baidu.com/map/jsdemo.htm#a6_1 球面距离公式验证
http://www.wubiao.info/470 Mysql or Mongodb LBS快速实现方案
geohash有以下几个特点：
首先，geohash用一个字符串表示经度和纬度两个坐标。某些情况下无法在两列上同时应用索引 （例如MySQL 4之前的版本，Google App Engine的数据层等），利用geohash，只需在一列上应用索引即可。
其次，geohash表示的并不是一个点，而是一个矩形区域。比如编码wx4g0ec19，它表示的是一个矩形区域。 使用者可以发布地址编码，既能表明自己位于北海公园附近，又不至于暴露自己的精确坐标，有助于隐私保护。
第三，编码的前缀可以表示更大的区域。例如wx4g0ec1，它的前缀wx4g0e表示包含编码wx4g0ec1在内的更大范围。 这个特性可以用于附近地点搜索。首先根据用户当前坐标计算geohash（例如wx4g0ec1）然后取其前缀进行查询 （SELECT * FROM place WHERE geohash LIKE 'wx4g0e%'），即可查询附近的所有地点。
Geohash比直接用经纬度的高效很多。
Geohash算法实现（PHP版本）
<?phpclass Geohash{ private $coding="0123456789bcdefghjkmnpqrstuvwxyz"; private $codingMap=array(); public function Geohash() { for($i=0; $i<32; $i++) { $this->codingMap[substr($this->coding,$i,1)]=str_pad(decbin($i), 5, "0", STR_PAD_LEFT); } } public function decode($hash) { $binary=""; $hl=strlen($hash); for($i=0; $i<$hl; $i++) { $binary.=$this->codingMap[substr($hash,$i,1)]; } $bl=strlen($binary); $blat=""; $blong=""; for ($i=0; $i<$bl; $i++) { if ($i%2) $blat=$blat.substr($binary,$i,1); else $blong=$blong.substr($binary,$i,1); } $lat=$this->binDecode($blat,-90,90); $long=$this->binDecode($blong,-180,180); // $lat=$this->binDecode($blat,2,54); // $long=$this->binDecode($blong,72,136); $latErr=$this->calcError(strlen($blat),-90,90); $longErr=$this->calcError(strlen($blong),-180,180); $latPlaces=max(1, -round(log10($latErr))) - 1; $longPlaces=max(1, -round(log10($longErr))) - 1; $lat=round($lat, $latPlaces); $long=round($long, $longPlaces); return array($lat,$long); } public function encode($lat,$long) { $plat=$this->precision($lat); $latbits=1; $err=45; while($err>$plat) { $latbits++; $err/=2; } $plong=$this->precision($long); $longbits=1; $err=90; while($err>$plong) { $longbits++; $err/=2; } $bits=max($latbits,$longbits); $longbits=$bits; $latbits=$bits; $addlong=1; while (($longbits+$latbits)%5 != 0) { $longbits+=$addlong; $latbits+=!$addlong; $addlong=!$addlong; } $blat=$this->binEncode($lat,-90,90, $latbits); $blong=$this->binEncode($long,-180,180,$longbits); $binary=""; $uselong=1; while (strlen($blat)+strlen($blong)) { if ($uselong) { $binary=$binary.substr($blong,0,1); $blong=substr($blong,1); } else { $binary=$binary.substr($blat,0,1); $blat=substr($blat,1); } $uselong=!$uselong; } $hash=""; for ($i=0; $i<strlen($binary); $i+=5) { $n=bindec(substr($binary,$i,5)); $hash=$hash.$this->coding[$n]; } return $hash; } private function calcError($bits,$min,$max) { $err=($max-$min)/2; while ($bits--) $err/=2; return $err; } private function precision($number) { $precision=0; $pt=strpos($number,'.'); if ($pt!==false) { $precision=-(strlen($number)-$pt-1); } return pow(10,$precision)/2; } private function binEncode($number, $min, $max, $bitcount) { if ($bitcount==0) return ""; $mid=($min+$max)/2; if ($number>$mid) return "1".$this->binEncode($number, $mid, $max,$bitcount-1); else return "0".$this->binEncode($number, $min, $mid,$bitcount-1); } private function binDecode($binary, $min, $max) { $mid=($min+$max)/2; if (strlen($binary)==0) return $mid; $bit=substr($binary,0,1); $binary=substr($binary,1); if ($bit==1) return $this->binDecode($binary, $mid, $max); else return $this->binDecode($binary, $min, $mid); }} ?>测试实例
<?php require_once("db_config.php");require_once('geohash.class.php'); $geohash=new Geohash; //经纬度转换成Geohash //获取附近的信息$n_latitude = 34.236080797698;$n_longitude = 109.0145193757;echo "当前位置为：经度108.7455，纬度34.3608<br/><br/>以下网点离我最近："; //开始$b_time = microtime(true); //方案A，直接利用数据库存储函数，遍历排序 //方案B geohash求出附近，然后排序 //当前 geohash值 $n_geohash = $geohash->encode($n_latitude,$n_longitude); //附近$n = 3;$like_geohash = substr($n_geohash, 0, $n); $sql = 'select * from retailersinfotable where geohash like "'.$like_geohash.'%"'; $query = mysql_query($sql); if(mysql_num_rows($query)) { while($row=mysql_fetch_array($query)) { $data[] = array ( "latitude" =>$row["Latitude"], "longitude"=>$row["Longitude"], "name" =>$row["RetailersName"], ); }} //算出实际距离 foreach($data as $key=>$val){ $distance = getDistance($n_latitude,$n_longitude,$val['latitude'],$val['longitude']); $data[$key]['distance'] = $distance; //排序列 $sortdistance[$key] = $distance;} //距离排序array_multisort($sortdistance,SORT_ASC,$data); //结束$e_time = microtime(true); echo "（计算耗时：" ;echo $e_time - $b_time; echo "秒）<br/>"; //var_dump($data); foreach($data as $key=>$val){ echo "</br>"; echo $val['distance']. " 米-------".$val['name'];} /*** @desc 根据两点间的经纬度计算距离* @param float $latitude 纬度值* @param float $longitude 经度值*/function getDistance($latitude1, $longitude1, $latitude2, $longitude2) { $earth_radius = 6371000; //approximate radius of earth in meters $dLat = deg2rad($latitude2 - $latitude1); $dLon = deg2rad($longitude2 - $longitude1); /* Using the Haversine formula http://en.wikipedia.org/wiki/Haversine_formula http://www.codecodex.com/wiki/Calculate_Distance_Between_Two_Points_on_a_Globe 验证：百度地图 http://developer.baidu.com/map/jsdemo.htm#a6_1 calculate the distance */ $a = sin($dLat/2) * sin($dLat/2) + cos(deg2rad($latitude1)) * cos(deg2rad($latitude2)) * sin($dLon/2) * sin($dLon/2); $c = 2 * asin(sqrt($a)); $d = $earth_radius * $c; return round($d); //四舍五入} ?>