Calculating Distances Between Geometric Points

In this article, we will explore how to calculate distances between points on a sphere (such as the Earth) when only latitude and longitude values are available. We’ll dive into the world of spherical geometry and discuss the various methods for calculating these distances.

Introduction

When working with geographic data, it’s essential to consider the spherical nature of our planet. Unlike flat surfaces, where Euclidean distance formulas apply, spherical coordinates (latitude and longitude) require special treatment to calculate distances accurately. In this article, we’ll explore the concepts behind calculating distances in spherical geometry and how they can be applied to real-world problems.

Understanding Geometric Coordinates

To tackle the problem of calculating distances between points on a sphere, it’s crucial to understand the basics of geometric coordinates. Latitude and longitude values represent points on the surface of a sphere (our planet) using angular measurements.

• Latitude: A measurement between 0° and 90° north or south of the equator.
• Longitude: A measurement between 0° and 180° east or west of the prime meridian.

When dealing with latitude and longitude values, it’s essential to recognize that these coordinates are not absolute but rather relative to a specific reference point (in this case, the Earth).

The Problem: Calculating Distances Between Points

Given two points on a sphere (a) and (b), we want to calculate the distance between them. This is where things get interesting, as it’s not as simple as using Euclidean distance formulas.

The problem lies in the fact that the Earth is not flat and spherical coordinates don’t directly translate to linear distances. To overcome this challenge, we’ll explore different methods for calculating distances between points on a sphere.

Spherical Distance Formulas

There are several ways to calculate distances between points on a sphere. We’ll discuss two popular formulas:

1. Great Circle Distance Formula:

   • This formula calculates the shortest distance between two points on a sphere, which is often referred to as the “great circle” distance.
   • The formula involves the use of spherical trigonometry and can be expressed as:

     d = arccos(sin(lat_a) \* sin(lat_b) + cos(lat_a) \* cos(lat_b) \* cos(long_b - long_a))
     

   • Where:
     • d is the distance between points a and b.
     • lat_a and lat_b are the latitudes of points a and b, respectively.
     • long_a and long_b are the longitudes of points a and b, respectively.

2. Haversine Formula:

   • This formula is another way to calculate distances between points on a sphere and is often used for web mapping applications.
   • The formula involves the use of the Haversine function, which can be expressed as:

     d = 2 \* atan2(sqrt(a), sqrt(1-a))
     

   • Where:
     • d is the distance between points a and b.
     • a is the cosine of half the central angle (Δσ) in radians, which can be calculated using the formula:

       a = sin²(lat_b - lat_a) + cos(lat_a) \* cos(lat_b) \* sin(long_b - long_a)²
       

     • Where:
       • lat_a and lat_b are the latitudes of points a and b, respectively.
       • long_a and long_b are the longitudes of points a and b, respectively.

Calculating Distances Using SQL

In an ideal scenario, it would be best to perform distance calculations directly in SQL. This approach allows you to filter results based on radius and sort distances using various methods.

To achieve this, you can use the Great Circle Distance Formula or Haversine Formula within your SQL queries. Here’s an example using the Great Circle Distance Formula:

SELECT 
    pl.latitude,
    pl.longitude,
    ST_Distance_Sphere(GeomFromText('POINT (0 0)'), GeomFromText('POINT (' || pl.latitude || ' ' || pl.longitude || ')')) AS distance
FROM 
    vehicle_location pl
WHERE 
    ST_DWithin(pl.geometry, GeomFromText('POINT (0 0)'), 1000);

In this example, the SQL query calculates the distance between each point in the vehicle_location table and a reference point (0° latitude, 0° longitude). The result is filtered to only include points within a radius of 1000 meters.

Implementing Distance Calculations in PHP

When dealing with large datasets or complex calculations, it may be more efficient to perform distance calculations using PHP. In this scenario, you can use the Haversine Formula or Great Circle Distance Formula to calculate distances between points.

Here’s an example implementation of the Haversine Formula:

function haversineDistance($lat1, $lon1, $lat2, $lon2) {
    $earthRadius = 6371; // kilometers

    $dLat = deg2rad($lat2 - $lat1);
    $dLon = deg2rad($lon2 - $lon1);

    $a = sin($dLat / 2) + cos(deg2rad($lat1)) * cos(deg2rad($lat2)) * sin($dLon / 2);
    $c = 2 * atan2(sqrt($a), sqrt(1 - $a));

    return $earthRadius * $c;
}

function deg2rad($deg) {
    return $deg * pi() / 180;
}

In this example, the haversineDistance function calculates the distance between two points using the Haversine Formula. The deg2rad helper function converts degrees to radians.

Conclusion

Calculating distances between points on a sphere requires special consideration due to the Earth’s spherical shape. By understanding the concepts of geometric coordinates and applying the appropriate distance formulas, you can accurately calculate distances between points in geographic applications.

In this article, we explored two popular distance formulas (Great Circle Distance Formula and Haversine Formula) and discussed their use cases. We also touched upon implementing distance calculations directly in SQL or using PHP for complex scenarios.

By following these concepts and techniques, you’ll be better equipped to tackle the challenges of calculating distances between points on a sphere in your own projects.

Last modified on 2025-03-14