Calculating distance between two different scenes from aerial drone images can be done easily using their GPS co-ordinates. For example, the gps coordinate of scene 1 is 42.3755, -71.1180 and and the gps co-ordinate of scene 2 is 42.3770, -71.1167

Scene 1: (42.3755, -71.1180)

Scene 2: (42.3770, -71.1167)

And the distance between them is calculated by the Haversine formula which computes the shortest distance over the Earth's surface between two latitude-longitude points.

If the two locations have GPS coordinates (lat1,lon1) and (lat2,lon2):

The steps in Python are:

 Convert latitudes and longitudes from degrees to radians.

 Compute differences Δlat=lat2−lat1 and Δlon=lon2−lon1.

 Use the Haversine formula:

a= 〖sin〗^2 (Δlat/2)+cos⁡(〖lat〗_1 ) ×cos⁡(〖lat〗_2 )× 〖sin〗^2 (Δlon/2)

c=2×arctan2(√a,√(1-a))

d=R×c

Where R is Earth's radius (mean radius = 6371 km).

import math

def haversine_distance(lat1, lon1, lat2, lon2):

    R = 6371 # Earth radius in km

    lat1_rad = math.radians(lat1)

    lat2_rad = math.radians(lat2)

    delta_lat = math.radians(lat2 - lat1)

    delta_lon = math.radians(lon2 - lon1)

    a = math.sin(delta_lat / 2) ** 2 + math.cos(lat1_rad) * math.cos(lat2_rad) * math.sin(delta_lon / 2) ** 2

    c = 2 * math.atan2(math.sqrt(a), math.sqrt(1 - a))

    distance = R * c

    return distance

# Example usage:

# Scene 1 GPS: lat1, lon1

# Scene 2 GPS: lat2, lon2

lat1, lon1 = 42.3770, -71.1167 # Scene 1 approx coords

lat2, lon2 = 42.3755, -71.1180 # Scene 2 approx coords

distance_km = haversine_distance(lat1, lon1, lat2, lon2)

print(f"Distance between scenes: {distance_km:.3f} km")

Distance between scenes: 0.198 km