I have given a location defined by latitude and longitude. Now i want to calculate a bounding box within e.g. 10 kilometers of that point.
The bounding box should be defined as latmin, lngmin and latmax, lngmax.
I need this stuff in order to use the panoramio API.
Does someone know the formula of how to get thos points?
Edit: Guys i am looking for a formula/function which takes lat & lng as input and returns a bounding box as latmin & lngmin and latmax & latmin. Mysql, php, c#, javascript is fine but also pseudocode should be okay.
Edit: I am not looking for a solution which shows me the distance of 2 points
The answer is
I was working on the bounding box problem as a side issue to finding all the points within SrcRad radius of a static LAT, LONG point. There have been quite a few calculations that use
maxLon = $lon + rad2deg($rad/$R/cos(deg2rad($lat)));
minLon = $lon - rad2deg($rad/$R/cos(deg2rad($lat)));
to calculate the longitude bounds, but I found this to not give all the answers that were needed. Because what you really want to do is
(SrcRad/RadEarth)/cos(deg2rad(lat))
I know, I know the answer should be the same, but I found that it wasn't. It appeared that by not making sure I was doing the (SRCrad/RadEarth) First and then dividing by the Cos part I was leaving out some location points.
After you get all your bounding box points, if you have a function that calculates the Point to Point Distance given lat, long it is easy to only get those points that are a certain distance radius from the fixed point. Here is what I did. I know it took a few extra steps but it helped me
-- GLOBAL Constants
gc_pi CONSTANT REAL := 3.14159265359; -- Pi
-- Conversion Factor Constants
gc_rad_to_degs CONSTANT NUMBER := 180/gc_pi; -- Conversion for Radians to Degrees 180/pi
gc_deg_to_rads CONSTANT NUMBER := gc_pi/180; --Conversion of Degrees to Radians
lv_stat_lat -- The static latitude point that I am searching from
lv_stat_long -- The static longitude point that I am searching from
-- Angular radius ratio in radians
lv_ang_radius := lv_search_radius / lv_earth_radius;
lv_bb_maxlat := lv_stat_lat + (gc_rad_to_deg * lv_ang_radius);
lv_bb_minlat := lv_stat_lat - (gc_rad_to_deg * lv_ang_radius);
--Here's the tricky part, accounting for the Longitude getting smaller as we move up the latitiude scale
-- I seperated the parts of the equation to make it easier to debug and understand
-- I may not be a smart man but I know what the right answer is... :-)
lv_int_calc := gc_deg_to_rads * lv_stat_lat;
lv_int_calc := COS(lv_int_calc);
lv_int_calc := lv_ang_radius/lv_int_calc;
lv_int_calc := gc_rad_to_degs*lv_int_calc;
lv_bb_maxlong := lv_stat_long + lv_int_calc;
lv_bb_minlong := lv_stat_long - lv_int_calc;
-- Now select the values from your location datatable
SELECT * FROM (
SELECT cityaliasname, city, state, zipcode, latitude, longitude,
-- The actual distance in miles
spherecos_pnttopntdist(lv_stat_lat, lv_stat_long, latitude, longitude, 'M') as miles_dist
FROM Location_Table
WHERE latitude between lv_bb_minlat AND lv_bb_maxlat
AND longitude between lv_bb_minlong and lv_bb_maxlong)
WHERE miles_dist <= lv_limit_distance_miles
order by miles_dist
;
I wrote a JavaScript function that returns the four coordinates of a square bounding box, given a distance and a pair of coordinates:
'use strict';
/**
* @param {number} distance - distance (km) from the point represented by centerPoint
* @param {array} centerPoint - two-dimensional array containing center coords [latitude, longitude]
* @description
* Computes the bounding coordinates of all points on the surface of a sphere
* that has a great circle distance to the point represented by the centerPoint
* argument that is less or equal to the distance argument.
* Technique from: Jan Matuschek <http://JanMatuschek.de/LatitudeLongitudeBoundingCoordinates>
* @author Alex Salisbury
*/
getBoundingBox = function (centerPoint, distance) {
var MIN_LAT, MAX_LAT, MIN_LON, MAX_LON, R, radDist, degLat, degLon, radLat, radLon, minLat, maxLat, minLon, maxLon, deltaLon;
if (distance < 0) {
return 'Illegal arguments';
}
// helper functions (degrees<–>radians)
Number.prototype.degToRad = function () {
return this * (Math.PI / 180);
};
Number.prototype.radToDeg = function () {
return (180 * this) / Math.PI;
};
// coordinate limits
MIN_LAT = (-90).degToRad();
MAX_LAT = (90).degToRad();
MIN_LON = (-180).degToRad();
MAX_LON = (180).degToRad();
// Earth's radius (km)
R = 6378.1;
// angular distance in radians on a great circle
radDist = distance / R;
// center point coordinates (deg)
degLat = centerPoint[0];
degLon = centerPoint[1];
// center point coordinates (rad)
radLat = degLat.degToRad();
radLon = degLon.degToRad();
// minimum and maximum latitudes for given distance
minLat = radLat - radDist;
maxLat = radLat + radDist;
// minimum and maximum longitudes for given distance
minLon = void 0;
maxLon = void 0;
// define deltaLon to help determine min and max longitudes
deltaLon = Math.asin(Math.sin(radDist) / Math.cos(radLat));
if (minLat > MIN_LAT && maxLat < MAX_LAT) {
minLon = radLon - deltaLon;
maxLon = radLon + deltaLon;
if (minLon < MIN_LON) {
minLon = minLon + 2 * Math.PI;
}
if (maxLon > MAX_LON) {
maxLon = maxLon - 2 * Math.PI;
}
}
// a pole is within the given distance
else {
minLat = Math.max(minLat, MIN_LAT);
maxLat = Math.min(maxLat, MAX_LAT);
minLon = MIN_LON;
maxLon = MAX_LON;
}
return [
minLon.radToDeg(),
minLat.radToDeg(),
maxLon.radToDeg(),
maxLat.radToDeg()
];
};
All of the above answer are only partially correct. Specially in region like Australia, they always include pole and calculate a very large rectangle even for 10kms.
Specially the algorithm by Jan Philip Matuschek at http://janmatuschek.de/LatitudeLongitudeBoundingCoordinates#UsingIndex included a very large rectangle from (-37, -90, -180, 180) for almost every point in Australia. This hits a large users in database and distance have to be calculated for all of the users in almost half the country.
I found that the Drupal API Earth Algorithm by Rochester Institute of Technology works better around pole as well as elsewhere and is much easier to implement.
https://www.rit.edu/drupal/api/drupal/sites%21all%21modules%21location%21earth.inc/7.54
Use earth_latitude_range and earth_longitude_range from the above algorithm for calculating bounding rectangle
And use the distance calculation formula documented by google maps to calculate distance
To search by kilometers instead of miles, replace 3959 with 6371. For (Lat, Lng) = (37, -122) and a Markers table with columns lat and lng, the formula is:
SELECT id, ( 3959 * acos( cos( radians(37) ) * cos( radians( lat ) ) * cos( radians( lng ) - radians(-122) ) + sin( radians(37) ) * sin( radians( lat ) ) ) ) AS distance FROM markers HAVING distance < 25 ORDER BY distance LIMIT 0 , 20;
Read my detailed answer at https://stackoverflow.com/a/45950426/5076414
Here I have converted Federico A. Ramponi's answer to C# for anybody interested:
public class MapPoint
{
public double Longitude { get; set; } // In Degrees
public double Latitude { get; set; } // In Degrees
}
public class BoundingBox
{
public MapPoint MinPoint { get; set; }
public MapPoint MaxPoint { get; set; }
}
// Semi-axes of WGS-84 geoidal reference
private const double WGS84_a = 6378137.0; // Major semiaxis [m]
private const double WGS84_b = 6356752.3; // Minor semiaxis [m]
// 'halfSideInKm' is the half length of the bounding box you want in kilometers.
public static BoundingBox GetBoundingBox(MapPoint point, double halfSideInKm)
{
// Bounding box surrounding the point at given coordinates,
// assuming local approximation of Earth surface as a sphere
// of radius given by WGS84
var lat = Deg2rad(point.Latitude);
var lon = Deg2rad(point.Longitude);
var halfSide = 1000 * halfSideInKm;
// Radius of Earth at given latitude
var radius = WGS84EarthRadius(lat);
// Radius of the parallel at given latitude
var pradius = radius * Math.Cos(lat);
var latMin = lat - halfSide / radius;
var latMax = lat + halfSide / radius;
var lonMin = lon - halfSide / pradius;
var lonMax = lon + halfSide / pradius;
return new BoundingBox {
MinPoint = new MapPoint { Latitude = Rad2deg(latMin), Longitude = Rad2deg(lonMin) },
MaxPoint = new MapPoint { Latitude = Rad2deg(latMax), Longitude = Rad2deg(lonMax) }
};
}
// degrees to radians
private static double Deg2rad(double degrees)
{
return Math.PI * degrees / 180.0;
}
// radians to degrees
private static double Rad2deg(double radians)
{
return 180.0 * radians / Math.PI;
}
// Earth radius at a given latitude, according to the WGS-84 ellipsoid [m]
private static double WGS84EarthRadius(double lat)
{
// http://en.wikipedia.org/wiki/Earth_radius
var An = WGS84_a * WGS84_a * Math.Cos(lat);
var Bn = WGS84_b * WGS84_b * Math.Sin(lat);
var Ad = WGS84_a * Math.Cos(lat);
var Bd = WGS84_b * Math.Sin(lat);
return Math.Sqrt((An*An + Bn*Bn) / (Ad*Ad + Bd*Bd));
}
Here I have converted Federico A. Ramponi's answer to PHP if anybody is interested:
<?php
# deg2rad and rad2deg are already within PHP
# Semi-axes of WGS-84 geoidal reference
$WGS84_a = 6378137.0; # Major semiaxis [m]
$WGS84_b = 6356752.3; # Minor semiaxis [m]
# Earth radius at a given latitude, according to the WGS-84 ellipsoid [m]
function WGS84EarthRadius($lat)
{
global $WGS84_a, $WGS84_b;
$an = $WGS84_a * $WGS84_a * cos($lat);
$bn = $WGS84_b * $WGS84_b * sin($lat);
$ad = $WGS84_a * cos($lat);
$bd = $WGS84_b * sin($lat);
return sqrt(($an*$an + $bn*$bn)/($ad*$ad + $bd*$bd));
}
# Bounding box surrounding the point at given coordinates,
# assuming local approximation of Earth surface as a sphere
# of radius given by WGS84
function boundingBox($latitudeInDegrees, $longitudeInDegrees, $halfSideInKm)
{
$lat = deg2rad($latitudeInDegrees);
$lon = deg2rad($longitudeInDegrees);
$halfSide = 1000 * $halfSideInKm;
# Radius of Earth at given latitude
$radius = WGS84EarthRadius($lat);
# Radius of the parallel at given latitude
$pradius = $radius*cos($lat);
$latMin = $lat - $halfSide / $radius;
$latMax = $lat + $halfSide / $radius;
$lonMin = $lon - $halfSide / $pradius;
$lonMax = $lon + $halfSide / $pradius;
return array(rad2deg($latMin), rad2deg($lonMin), rad2deg($latMax), rad2deg($lonMax));
}
?>
You're looking for an ellipsoid formula.
The best place I've found to start coding is based on the Geo::Ellipsoid library from CPAN. It gives you a baseline to create your tests off of and to compare your results with its results. I used it as the basis for a similar library for PHP at my previous employer.
Take a look at the location method. Call it twice and you've got your bbox.
You didn't post what language you were using. There may already be a geocoding library available for you.
Oh, and if you haven't figured it out by now, Google maps uses the WGS84 ellipsoid.
Since I needed a very rough estimate, so to filter out some needless documents in an elasticsearch query, I employed the below formula:
Min.lat = Given.Lat - (0.009 x N)
Max.lat = Given.Lat + (0.009 x N)
Min.lon = Given.lon - (0.009 x N)
Max.lon = Given.lon + (0.009 x N)
N = kms required form the given location. For your case N=10
Not accurate but handy.
Here I have converted Federico A. Ramponi's answer to C# for anybody interested:
public class MapPoint
{
public double Longitude { get; set; } // In Degrees
public double Latitude { get; set; } // In Degrees
}
public class BoundingBox
{
public MapPoint MinPoint { get; set; }
public MapPoint MaxPoint { get; set; }
}
// Semi-axes of WGS-84 geoidal reference
private const double WGS84_a = 6378137.0; // Major semiaxis [m]
private const double WGS84_b = 6356752.3; // Minor semiaxis [m]
// 'halfSideInKm' is the half length of the bounding box you want in kilometers.
public static BoundingBox GetBoundingBox(MapPoint point, double halfSideInKm)
{
// Bounding box surrounding the point at given coordinates,
// assuming local approximation of Earth surface as a sphere
// of radius given by WGS84
var lat = Deg2rad(point.Latitude);
var lon = Deg2rad(point.Longitude);
var halfSide = 1000 * halfSideInKm;
// Radius of Earth at given latitude
var radius = WGS84EarthRadius(lat);
// Radius of the parallel at given latitude
var pradius = radius * Math.Cos(lat);
var latMin = lat - halfSide / radius;
var latMax = lat + halfSide / radius;
var lonMin = lon - halfSide / pradius;
var lonMax = lon + halfSide / pradius;
return new BoundingBox {
MinPoint = new MapPoint { Latitude = Rad2deg(latMin), Longitude = Rad2deg(lonMin) },
MaxPoint = new MapPoint { Latitude = Rad2deg(latMax), Longitude = Rad2deg(lonMax) }
};
}
// degrees to radians
private static double Deg2rad(double degrees)
{
return Math.PI * degrees / 180.0;
}
// radians to degrees
private static double Rad2deg(double radians)
{
return 180.0 * radians / Math.PI;
}
// Earth radius at a given latitude, according to the WGS-84 ellipsoid [m]
private static double WGS84EarthRadius(double lat)
{
// http://en.wikipedia.org/wiki/Earth_radius
var An = WGS84_a * WGS84_a * Math.Cos(lat);
var Bn = WGS84_b * WGS84_b * Math.Sin(lat);
var Ad = WGS84_a * Math.Cos(lat);
var Bd = WGS84_b * Math.Sin(lat);
return Math.Sqrt((An*An + Bn*Bn) / (Ad*Ad + Bd*Bd));
}
I was working on the bounding box problem as a side issue to finding all the points within SrcRad radius of a static LAT, LONG point. There have been quite a few calculations that use
maxLon = $lon + rad2deg($rad/$R/cos(deg2rad($lat)));
minLon = $lon - rad2deg($rad/$R/cos(deg2rad($lat)));
to calculate the longitude bounds, but I found this to not give all the answers that were needed. Because what you really want to do is
(SrcRad/RadEarth)/cos(deg2rad(lat))
I know, I know the answer should be the same, but I found that it wasn't. It appeared that by not making sure I was doing the (SRCrad/RadEarth) First and then dividing by the Cos part I was leaving out some location points.
After you get all your bounding box points, if you have a function that calculates the Point to Point Distance given lat, long it is easy to only get those points that are a certain distance radius from the fixed point. Here is what I did. I know it took a few extra steps but it helped me
-- GLOBAL Constants
gc_pi CONSTANT REAL := 3.14159265359; -- Pi
-- Conversion Factor Constants
gc_rad_to_degs CONSTANT NUMBER := 180/gc_pi; -- Conversion for Radians to Degrees 180/pi
gc_deg_to_rads CONSTANT NUMBER := gc_pi/180; --Conversion of Degrees to Radians
lv_stat_lat -- The static latitude point that I am searching from
lv_stat_long -- The static longitude point that I am searching from
-- Angular radius ratio in radians
lv_ang_radius := lv_search_radius / lv_earth_radius;
lv_bb_maxlat := lv_stat_lat + (gc_rad_to_deg * lv_ang_radius);
lv_bb_minlat := lv_stat_lat - (gc_rad_to_deg * lv_ang_radius);
--Here's the tricky part, accounting for the Longitude getting smaller as we move up the latitiude scale
-- I seperated the parts of the equation to make it easier to debug and understand
-- I may not be a smart man but I know what the right answer is... :-)
lv_int_calc := gc_deg_to_rads * lv_stat_lat;
lv_int_calc := COS(lv_int_calc);
lv_int_calc := lv_ang_radius/lv_int_calc;
lv_int_calc := gc_rad_to_degs*lv_int_calc;
lv_bb_maxlong := lv_stat_long + lv_int_calc;
lv_bb_minlong := lv_stat_long - lv_int_calc;
-- Now select the values from your location datatable
SELECT * FROM (
SELECT cityaliasname, city, state, zipcode, latitude, longitude,
-- The actual distance in miles
spherecos_pnttopntdist(lv_stat_lat, lv_stat_long, latitude, longitude, 'M') as miles_dist
FROM Location_Table
WHERE latitude between lv_bb_minlat AND lv_bb_maxlat
AND longitude between lv_bb_minlong and lv_bb_maxlong)
WHERE miles_dist <= lv_limit_distance_miles
order by miles_dist
;
Illustration of @Jan Philip Matuschek excellent explanation.(Please up-vote his answer, not this; I am adding this as I took a little time in understanding the original answer)
The bounding box technique of optimizing of finding nearest neighbors would need to derive the minimum and maximum latitude,longitude pairs, for a point P at distance d . All points that fall outside these are definitely at a distance greater than d from the point. One thing to note here is the calculation of latitude of intersection as is highlighted in Jan Philip Matuschek explanation. The latitude of intersection is not at the latitude of point P but slightly offset from it. This is a often missed but important part in determining the correct minimum and maximum bounding longitude for point P for the distance d.This is also useful in verification.
The haversine distance between (latitude of intersection,longitude high) to (latitude,longitude) of P is equal to distance d.
Python gist here https://gist.github.com/alexcpn/f95ae83a7ee0293a5225
I wrote a JavaScript function that returns the four coordinates of a square bounding box, given a distance and a pair of coordinates:
'use strict';
/**
* @param {number} distance - distance (km) from the point represented by centerPoint
* @param {array} centerPoint - two-dimensional array containing center coords [latitude, longitude]
* @description
* Computes the bounding coordinates of all points on the surface of a sphere
* that has a great circle distance to the point represented by the centerPoint
* argument that is less or equal to the distance argument.
* Technique from: Jan Matuschek <http://JanMatuschek.de/LatitudeLongitudeBoundingCoordinates>
* @author Alex Salisbury
*/
getBoundingBox = function (centerPoint, distance) {
var MIN_LAT, MAX_LAT, MIN_LON, MAX_LON, R, radDist, degLat, degLon, radLat, radLon, minLat, maxLat, minLon, maxLon, deltaLon;
if (distance < 0) {
return 'Illegal arguments';
}
// helper functions (degrees<–>radians)
Number.prototype.degToRad = function () {
return this * (Math.PI / 180);
};
Number.prototype.radToDeg = function () {
return (180 * this) / Math.PI;
};
// coordinate limits
MIN_LAT = (-90).degToRad();
MAX_LAT = (90).degToRad();
MIN_LON = (-180).degToRad();
MAX_LON = (180).degToRad();
// Earth's radius (km)
R = 6378.1;
// angular distance in radians on a great circle
radDist = distance / R;
// center point coordinates (deg)
degLat = centerPoint[0];
degLon = centerPoint[1];
// center point coordinates (rad)
radLat = degLat.degToRad();
radLon = degLon.degToRad();
// minimum and maximum latitudes for given distance
minLat = radLat - radDist;
maxLat = radLat + radDist;
// minimum and maximum longitudes for given distance
minLon = void 0;
maxLon = void 0;
// define deltaLon to help determine min and max longitudes
deltaLon = Math.asin(Math.sin(radDist) / Math.cos(radLat));
if (minLat > MIN_LAT && maxLat < MAX_LAT) {
minLon = radLon - deltaLon;
maxLon = radLon + deltaLon;
if (minLon < MIN_LON) {
minLon = minLon + 2 * Math.PI;
}
if (maxLon > MAX_LON) {
maxLon = maxLon - 2 * Math.PI;
}
}
// a pole is within the given distance
else {
minLat = Math.max(minLat, MIN_LAT);
maxLat = Math.min(maxLat, MAX_LAT);
minLon = MIN_LON;
maxLon = MAX_LON;
}
return [
minLon.radToDeg(),
minLat.radToDeg(),
maxLon.radToDeg(),
maxLat.radToDeg()
];
};
Thanks @Fedrico A. for the Phyton implementation, I have ported it into a Objective C category class. Here is:
#import "LocationService+Bounds.h"
//Semi-axes of WGS-84 geoidal reference
const double WGS84_a = 6378137.0; //Major semiaxis [m]
const double WGS84_b = 6356752.3; //Minor semiaxis [m]
@implementation LocationService (Bounds)
struct BoundsLocation {
double maxLatitude;
double minLatitude;
double maxLongitude;
double minLongitude;
};
+ (struct BoundsLocation)locationBoundsWithLatitude:(double)aLatitude longitude:(double)aLongitude maxDistanceKm:(NSInteger)aMaxKmDistance {
return [self boundingBoxWithLatitude:aLatitude longitude:aLongitude halfDistanceKm:aMaxKmDistance/2];
}
#pragma mark - Algorithm
+ (struct BoundsLocation)boundingBoxWithLatitude:(double)aLatitude longitude:(double)aLongitude halfDistanceKm:(double)aDistanceKm {
double radianLatitude = [self degreesToRadians:aLatitude];
double radianLongitude = [self degreesToRadians:aLongitude];
double halfDistanceMeters = aDistanceKm*1000;
double earthRadius = [self earthRadiusAtLatitude:radianLatitude];
double parallelRadius = earthRadius*cosl(radianLatitude);
double radianMinLatitude = radianLatitude - halfDistanceMeters/earthRadius;
double radianMaxLatitude = radianLatitude + halfDistanceMeters/earthRadius;
double radianMinLongitude = radianLongitude - halfDistanceMeters/parallelRadius;
double radianMaxLongitude = radianLongitude + halfDistanceMeters/parallelRadius;
struct BoundsLocation bounds;
bounds.minLatitude = [self radiansToDegrees:radianMinLatitude];
bounds.maxLatitude = [self radiansToDegrees:radianMaxLatitude];
bounds.minLongitude = [self radiansToDegrees:radianMinLongitude];
bounds.maxLongitude = [self radiansToDegrees:radianMaxLongitude];
return bounds;
}
+ (double)earthRadiusAtLatitude:(double)aRadianLatitude {
double An = WGS84_a * WGS84_a * cosl(aRadianLatitude);
double Bn = WGS84_b * WGS84_b * sinl(aRadianLatitude);
double Ad = WGS84_a * cosl(aRadianLatitude);
double Bd = WGS84_b * sinl(aRadianLatitude);
return sqrtl( ((An * An) + (Bn * Bn))/((Ad * Ad) + (Bd * Bd)) );
}
+ (double)degreesToRadians:(double)aDegrees {
return M_PI*aDegrees/180.0;
}
+ (double)radiansToDegrees:(double)aRadians {
return 180.0*aRadians/M_PI;
}
@end
I have tested it and seems be working nice. Struct BoundsLocation should be replaced by a class, I have used it just to share it here.
You're looking for an ellipsoid formula.
The best place I've found to start coding is based on the Geo::Ellipsoid library from CPAN. It gives you a baseline to create your tests off of and to compare your results with its results. I used it as the basis for a similar library for PHP at my previous employer.
Take a look at the location method. Call it twice and you've got your bbox.
You didn't post what language you were using. There may already be a geocoding library available for you.
Oh, and if you haven't figured it out by now, Google maps uses the WGS84 ellipsoid.
I adapted a PHP script I found to do just this. You can use it to find the corners of a box around a point (say, 20 km out). My specific example is for Google Maps API:
Here I have converted Federico A. Ramponi's answer to PHP if anybody is interested:
<?php
# deg2rad and rad2deg are already within PHP
# Semi-axes of WGS-84 geoidal reference
$WGS84_a = 6378137.0; # Major semiaxis [m]
$WGS84_b = 6356752.3; # Minor semiaxis [m]
# Earth radius at a given latitude, according to the WGS-84 ellipsoid [m]
function WGS84EarthRadius($lat)
{
global $WGS84_a, $WGS84_b;
$an = $WGS84_a * $WGS84_a * cos($lat);
$bn = $WGS84_b * $WGS84_b * sin($lat);
$ad = $WGS84_a * cos($lat);
$bd = $WGS84_b * sin($lat);
return sqrt(($an*$an + $bn*$bn)/($ad*$ad + $bd*$bd));
}
# Bounding box surrounding the point at given coordinates,
# assuming local approximation of Earth surface as a sphere
# of radius given by WGS84
function boundingBox($latitudeInDegrees, $longitudeInDegrees, $halfSideInKm)
{
$lat = deg2rad($latitudeInDegrees);
$lon = deg2rad($longitudeInDegrees);
$halfSide = 1000 * $halfSideInKm;
# Radius of Earth at given latitude
$radius = WGS84EarthRadius($lat);
# Radius of the parallel at given latitude
$pradius = $radius*cos($lat);
$latMin = $lat - $halfSide / $radius;
$latMax = $lat + $halfSide / $radius;
$lonMin = $lon - $halfSide / $pradius;
$lonMax = $lon + $halfSide / $pradius;
return array(rad2deg($latMin), rad2deg($lonMin), rad2deg($latMax), rad2deg($lonMax));
}
?>
I wrote an article about finding the bounding coordinates:
http://JanMatuschek.de/LatitudeLongitudeBoundingCoordinates
The article explains the formulae and also provides a Java implementation. (It also shows why Federico's formula for the min/max longitude is inaccurate.)
It is very simple just go to panoramio website and then open World Map from panoramio website.Then go to specified location whichs latitude and longitude required.
Then you found latitude and longitude in address bar for example in this address.
http://www.panoramio.com/map#lt=32.739485&ln=70.491211&z=9&k=1&a=1&tab=1&pl=all
lt=32.739485 =>latitude ln=70.491211 =>longitude
this Panoramio JavaScript API widget create a bounding box around a lat/long pair and then returning all photos with in those bounds.
Another type of Panoramio JavaScript API widget in which you can also change background color with example and code is here.
It does not show in composing mood.It show after publishing.
<div dir="ltr" style="text-align: center;" trbidi="on">
<script src="https://ssl.panoramio.com/wapi/wapi.js?v=1&hl=en"></script>
<div id="wapiblock" style="float: right; margin: 10px 15px"></div>
<script type="text/javascript">
var myRequest = {
'tag': 'kahna',
'rect': {'sw': {'lat': -30, 'lng': 10.5}, 'ne': {'lat': 50.5, 'lng': 30}}
};
var myOptions = {
'width': 300,
'height': 200
};
var wapiblock = document.getElementById('wapiblock');
var photo_widget = new panoramio.PhotoWidget('wapiblock', myRequest, myOptions);
photo_widget.setPosition(0);
</script>
</div>
Here is an simple implementation using javascript which is based on the conversion of latitude degree to kms where 1 degree latitude ~ 111.2 km.
I am calculating bounds of the map from a given latitude, longitude and radius in kilometers.
function getBoundsFromLatLng(lat, lng, radiusInKm){
var lat_change = radiusInKm/111.2;
var lon_change = Math.abs(Math.cos(lat*(Math.PI/180)));
var bounds = {
lat_min : lat - lat_change,
lon_min : lng - lon_change,
lat_max : lat + lat_change,
lon_max : lng + lon_change
};
return bounds;
}
I wrote an article about finding the bounding coordinates:
http://JanMatuschek.de/LatitudeLongitudeBoundingCoordinates
The article explains the formulae and also provides a Java implementation. (It also shows why Federico's formula for the min/max longitude is inaccurate.)
You're looking for an ellipsoid formula.
The best place I've found to start coding is based on the Geo::Ellipsoid library from CPAN. It gives you a baseline to create your tests off of and to compare your results with its results. I used it as the basis for a similar library for PHP at my previous employer.
Take a look at the location method. Call it twice and you've got your bbox.
You didn't post what language you were using. There may already be a geocoding library available for you.
Oh, and if you haven't figured it out by now, Google maps uses the WGS84 ellipsoid.
All of the above answer are only partially correct. Specially in region like Australia, they always include pole and calculate a very large rectangle even for 10kms.
Specially the algorithm by Jan Philip Matuschek at http://janmatuschek.de/LatitudeLongitudeBoundingCoordinates#UsingIndex included a very large rectangle from (-37, -90, -180, 180) for almost every point in Australia. This hits a large users in database and distance have to be calculated for all of the users in almost half the country.
I found that the Drupal API Earth Algorithm by Rochester Institute of Technology works better around pole as well as elsewhere and is much easier to implement.
https://www.rit.edu/drupal/api/drupal/sites%21all%21modules%21location%21earth.inc/7.54
Use earth_latitude_range and earth_longitude_range from the above algorithm for calculating bounding rectangle
And use the distance calculation formula documented by google maps to calculate distance
To search by kilometers instead of miles, replace 3959 with 6371. For (Lat, Lng) = (37, -122) and a Markers table with columns lat and lng, the formula is:
SELECT id, ( 3959 * acos( cos( radians(37) ) * cos( radians( lat ) ) * cos( radians( lng ) - radians(-122) ) + sin( radians(37) ) * sin( radians( lat ) ) ) ) AS distance FROM markers HAVING distance < 25 ORDER BY distance LIMIT 0 , 20;
Read my detailed answer at https://stackoverflow.com/a/45950426/5076414
Since I needed a very rough estimate, so to filter out some needless documents in an elasticsearch query, I employed the below formula:
Min.lat = Given.Lat - (0.009 x N)
Max.lat = Given.Lat + (0.009 x N)
Min.lon = Given.lon - (0.009 x N)
Max.lon = Given.lon + (0.009 x N)
N = kms required form the given location. For your case N=10
Not accurate but handy.
Here is an simple implementation using javascript which is based on the conversion of latitude degree to kms where 1 degree latitude ~ 111.2 km.
I am calculating bounds of the map from a given latitude, longitude and radius in kilometers.
function getBoundsFromLatLng(lat, lng, radiusInKm){
var lat_change = radiusInKm/111.2;
var lon_change = Math.abs(Math.cos(lat*(Math.PI/180)));
var bounds = {
lat_min : lat - lat_change,
lon_min : lng - lon_change,
lat_max : lat + lat_change,
lon_max : lng + lon_change
};
return bounds;
}
You're looking for an ellipsoid formula.
The best place I've found to start coding is based on the Geo::Ellipsoid library from CPAN. It gives you a baseline to create your tests off of and to compare your results with its results. I used it as the basis for a similar library for PHP at my previous employer.
Take a look at the location method. Call it twice and you've got your bbox.
You didn't post what language you were using. There may already be a geocoding library available for you.
Oh, and if you haven't figured it out by now, Google maps uses the WGS84 ellipsoid.
Illustration of @Jan Philip Matuschek excellent explanation.(Please up-vote his answer, not this; I am adding this as I took a little time in understanding the original answer)
The bounding box technique of optimizing of finding nearest neighbors would need to derive the minimum and maximum latitude,longitude pairs, for a point P at distance d . All points that fall outside these are definitely at a distance greater than d from the point. One thing to note here is the calculation of latitude of intersection as is highlighted in Jan Philip Matuschek explanation. The latitude of intersection is not at the latitude of point P but slightly offset from it. This is a often missed but important part in determining the correct minimum and maximum bounding longitude for point P for the distance d.This is also useful in verification.
The haversine distance between (latitude of intersection,longitude high) to (latitude,longitude) of P is equal to distance d.
Python gist here https://gist.github.com/alexcpn/f95ae83a7ee0293a5225
It is very simple just go to panoramio website and then open World Map from panoramio website.Then go to specified location whichs latitude and longitude required.
Then you found latitude and longitude in address bar for example in this address.
http://www.panoramio.com/map#lt=32.739485&ln=70.491211&z=9&k=1&a=1&tab=1&pl=all
lt=32.739485 =>latitude ln=70.491211 =>longitude
this Panoramio JavaScript API widget create a bounding box around a lat/long pair and then returning all photos with in those bounds.
Another type of Panoramio JavaScript API widget in which you can also change background color with example and code is here.
It does not show in composing mood.It show after publishing.
<div dir="ltr" style="text-align: center;" trbidi="on">
<script src="https://ssl.panoramio.com/wapi/wapi.js?v=1&hl=en"></script>
<div id="wapiblock" style="float: right; margin: 10px 15px"></div>
<script type="text/javascript">
var myRequest = {
'tag': 'kahna',
'rect': {'sw': {'lat': -30, 'lng': 10.5}, 'ne': {'lat': 50.5, 'lng': 30}}
};
var myOptions = {
'width': 300,
'height': 200
};
var wapiblock = document.getElementById('wapiblock');
var photo_widget = new panoramio.PhotoWidget('wapiblock', myRequest, myOptions);
photo_widget.setPosition(0);
</script>
</div>
Here is Federico Ramponi's answer in Go. Note: no error-checking :(
import (
"math"
)
// Semi-axes of WGS-84 geoidal reference
const (
// Major semiaxis (meters)
WGS84A = 6378137.0
// Minor semiaxis (meters)
WGS84B = 6356752.3
)
// BoundingBox represents the geo-polygon that encompasses the given point and radius
type BoundingBox struct {
LatMin float64
LatMax float64
LonMin float64
LonMax float64
}
// Convert a degree value to radians
func deg2Rad(deg float64) float64 {
return math.Pi * deg / 180.0
}
// Convert a radian value to degrees
func rad2Deg(rad float64) float64 {
return 180.0 * rad / math.Pi
}
// Get the Earth's radius in meters at a given latitude based on the WGS84 ellipsoid
func getWgs84EarthRadius(lat float64) float64 {
an := WGS84A * WGS84A * math.Cos(lat)
bn := WGS84B * WGS84B * math.Sin(lat)
ad := WGS84A * math.Cos(lat)
bd := WGS84B * math.Sin(lat)
return math.Sqrt((an*an + bn*bn) / (ad*ad + bd*bd))
}
// GetBoundingBox returns a BoundingBox encompassing the given lat/long point and radius
func GetBoundingBox(latDeg float64, longDeg float64, radiusKm float64) BoundingBox {
lat := deg2Rad(latDeg)
lon := deg2Rad(longDeg)
halfSide := 1000 * radiusKm
// Radius of Earth at given latitude
radius := getWgs84EarthRadius(lat)
pradius := radius * math.Cos(lat)
latMin := lat - halfSide/radius
latMax := lat + halfSide/radius
lonMin := lon - halfSide/pradius
lonMax := lon + halfSide/pradius
return BoundingBox{
LatMin: rad2Deg(latMin),
LatMax: rad2Deg(latMax),
LonMin: rad2Deg(lonMin),
LonMax: rad2Deg(lonMax),
}
}
Source: Stackoverflow.com