Reputation: 383
Given a series of GPS coordinate pairs, I need to calculate the area of a polygon (n-gon). This is relatively small (not larger than 50,000 sqft). The geocodes are created by applying an affine transform with data from a world file.
I have tried to use a two step approach by doing converting the geocodes to cartesian coordinates:
double xPos = (lon-lonAnchor)*( Math.toRadians( 6378137 ) )*Math.cos( latAnchor );
double yPos = (lat-latAnchor)*( Math.toRadians( 6378137 ) );
then I use a cross product calculation to determine the area.
The issue is that the results are a bit off in accuracy (around 1%). Is there anything I can look into to improve this?
Thanks.
Upvotes: 9
Views: 59473
Reputation: 119
Google Maps Utils library provide a method to calculate the Area.
You have to add below dependency
implementation("com.google.maps.android:android-maps-utils:3.8.2")
And then call below method and give it yours Latitude and Longitude list. It will return area in square meters.
fun surfaceArea(list: List<LatLng>): Double {
if (list.size < 3) {
return 0.0
}
return SphericalUtil.computeArea(list)
}
Upvotes: 0
Reputation: 9564
Adapted RiskyPathak's snippet to PHP
function CalculatePolygonArea($coordinates) {
$area = 0;
$coordinatesCount = sizeof($coordinates);
if ($coordinatesCount > 2) {
for ($i = 0; $i < $coordinatesCount - 1; $i++) {
$p1 = $coordinates[$i];
$p2 = $coordinates[$i + 1];
$p1Longitude = $p1[0];
$p2Longitude = $p2[0];
$p1Latitude = $p1[1];
$p2Latitude = $p2[1];
$area += ConvertToRadian($p2Longitude - $p1Longitude) * (2 + sin(ConvertToRadian($p1Latitude)) + sin(ConvertToRadian($p2Latitude)));
}
$area = $area * 6378137 * 6378137 / 2;
}
return abs(round(($area)));
}
function ConvertToRadian($input) {
$output = $input * pi() / 180;
return $output;
}
// mssing clossing )
Upvotes: 0
Reputation: 1688
I'm not sure why, but the results I'm getting using the formula above , are nowhere near the results google maps is returning when measuring the same area.
So digging around, I've came up with this javascript method to calculate a polygon area defined by GPS coordinates:
const PI = Math.PI;
const EARTH_RADIUS_IN_METERS = 6378137;
const EARTH_CIRCUMFERENCE_IN_METERS = 2*EARTH_RADIUS_IN_METERS*PI;
function areaClaculator(points) {
let area = null;
if (!isValueEmpty(points) && points.length > 2) {
let p0 = points[0]
let newPoints = [];
for (let i=1; i<points.length; i++) {
let p = points[i];
let y = (p.lat - p0.lat) / 360 * EARTH_CIRCUMFERENCE_IN_METERS;
let x = (p.lng - p0.lng) / 360 * EARTH_CIRCUMFERENCE_IN_METERS * Math.cos(rad(p.lat));
let entry = {};
entry.x = x;
entry.y = y;
newPoints.push(entry);
}
if (!isValueEmpty(newPoints) && newPoints.length > 1) {
area = 0;
for (let i=0;i< newPoints.length - 1; i++) {
let p1 = newPoints[i];
let p2 = newPoints[i+1];
area += ((p1.y * p2.x) - (p1.x*p2.y))/2;
}
area = Math.abs(area);
}
}
return area;
}
function rad(degrees) {
return degrees * PI / 180;
}
Where points stores values like: {lng: -73.462556156587, lat: 45.48566183708046}
Upvotes: 0
Reputation: 1
Tried to do this in swift playground and got results that are way off Example coord: (39.58571008386715,-104.94522892318253) that I am plugging into the function
func deg2rad(_ number: Double) -> Double {
return number * .pi / 180
}
func areaCalc(lat: [Double]?, lon: [Double]?){
guard let lat = lat,
let lon = lon
else { return }
var area: Double = 0.0
if(lat.count > 2){
for i in stride(from: 0, to: lat.count - 1, by: 1) {
let p1lon = lon[i]
let p1lat = lat[i]
let p2lon = lon[i+1]
let p2lat = lat[i+1]
area = area + (deg2rad(p2lon - p1lon)) * (2 + sin(deg2rad(p1lat))) + (sin(deg2rad(p2lat)))
}
area = area * 6378137.0 * 6378137.0
area = abs(area / 2)
}
}
Upvotes: 0
Reputation: 11
The reason for this "1%" discrepancy is The earth is very slightly ellipsoidal so by calculating using a spherical model gives errors typically up to 0.3%, give or take the location.
Upvotes: 1
Reputation: 250
Adapted RiskyPathak's snippet to Ruby
def deg2rad(input)
input * Math::PI / 180.0
end
def polygone_area(coordinates)
return 0.0 unless coordinates.size > 2
area = 0.0
coor_p = coordinates.first
coordinates[1..-1].each{ |coor|
area += deg2rad(coor[1] - coor_p[1]) * (2 + Math.sin(deg2rad(coor_p[0])) + Math.sin(deg2rad(coor[0])))
coor_p = coor
}
(area * 6378137 * 6378137 / 2.0).abs # 6378137 Earth's radius in meters
end
Upvotes: 0
Reputation: 171
Thank you Risky Pathak!
In the spirit of sharing, here's my adaptation in Delphi:
interface
uses
System.Math;
TMapGeoPoint = record
Latitude: Double;
Longitude: Double;
end;
function AreaInAcres(AGeoPoints: TList<TMapGeoPoint>): Double;
implementation
function AreaInAcres(AGeoPoints: TList<TMapGeoPoint>): Double;
var
Area: Double;
i: Integer;
P1, P2: TMapGeoPoint;
begin
Area := 0;
// We need at least 2 points
if (AGeoPoints.Count > 2) then
begin
for I := 0 to AGeoPoints.Count - 1 do
begin
P1 := AGeoPoints[i];
if i < AGeoPoints.Count - 1 then
P2 := AGeoPoints[i + 1]
else
P2 := AGeoPoints[0];
Area := Area + DegToRad(P2.Longitude - P1.Longitude) * (2 +
Sin(DegToRad(P1.Latitude)) + Sin(DegToRad(P2.Latitude)));
end;
Area := Area * 6378137 * 6378137 / 2;
end;
Area := Abs(Area); //Area (in sq meters)
// 1 Square Meter = 0.000247105 Acres
result := Area * 0.000247105;
end;
Upvotes: 0
Reputation: 1929
Based on the solution by Risky Pathak here is the solution for SQL (Redshift) to calculate areas for GeoJSON multipolygons (with the assumption that linestring 0 is the outermost polygon)
create or replace view geo_area_area as
with points as (
select ga.id as key_geo_area
, ga.name, gag.linestring
, gag.position
, radians(gag.longitude) as x
, radians(gag.latitude) as y
from geo_area ga
join geo_area_geometry gag on (gag.key_geo_area = ga.id)
)
, polygons as (
select key_geo_area, name, linestring, position
, x
, lag(x) over (partition by key_geo_area, linestring order by position) as prev_x
, y
, lag(y) over (partition by key_geo_area, linestring order by position) as prev_y
from points
)
, area_linestrings as (
select key_geo_area, name, linestring
, abs( sum( (x - prev_x) * (2 + sin(y) + sin(prev_y)) ) ) * 6378137 * 6378137 / 2 / 10^6 as area_km_squared
from polygons
where position != 0
group by 1, 2, 3
)
select key_geo_area, name
, sum(case when linestring = 0 then area_km_squared else -area_km_squared end) as area_km_squared
from area_linestrings
group by 1, 2
;
Upvotes: 0
Reputation: 616
I checked on internet for various polygon area formulas(or code) but did not find any one good or easy to implement.
Now I have written the code snippet to calculate area of a polygon drawn on earth surface. The polygon can have n vertices with each vertex has having its own latitude longitude.
Few Important Points
The output area will have unit of square metres
private static double CalculatePolygonArea(IList<MapPoint> coordinates)
{
double area = 0;
if (coordinates.Count > 2)
{
for (var i = 0; i < coordinates.Count - 1; i++)
{
MapPoint p1 = coordinates[i];
MapPoint p2 = coordinates[i + 1];
area += ConvertToRadian(p2.Longitude - p1.Longitude) * (2 + Math.Sin(ConvertToRadian(p1.Latitude)) + Math.Sin(ConvertToRadian(p2.Latitude)));
}
area = area * 6378137 * 6378137 / 2;
}
return Math.Abs(area);
}
private static double ConvertToRadian(double input)
{
return input * Math.PI / 180;
}
Upvotes: 12
Reputation: 31
I am modifying a Google Map so that a user can calculate the area of a polygon by clicking the vertices. It wasn't giving correct areas until I made sure the Math.cos(latAnchor) was in radians first
So:
double xPos = (lon-lonAnchor)*( Math.toRadians( 6378137 ) )*Math.cos( latAnchor );
became:
double xPos = (lon-lonAnchor)*( 6378137*PI/180 ) )*Math.cos( latAnchor*PI/180 );
where lon, lonAnchor and latAnchor are in degrees. Works like a charm now.
Upvotes: 3
Reputation: 10074
1% error seems a bit high due to just your approximation. Are you comparing against actual measurements or some ideal calculation? Remember that there is error in the GPS as well that might be contributing.
If you want a more accurate method for doing this there's a good answer at this question. If you're going for a faster way you can use the WGS84 geoid instead of your reference sphere for converting to cartesian coordinates (ECEF). Here's the wiki link for that conversion.
Upvotes: 1