How Can I Correct Negative Bearing Values When Using the Haversine Formula in Python to Calculate Distance and Bearing Between GPS Points?

Haversine Formula in Python: Calculating Distance and Bearing Between GPS Points

In this Python guide, we'll delve into the Haversine formula, a powerful tool for determining the distance and bearing between two GPS coordinates.

Problem:

We aim to compute the distance and bearing between two GPS points but encounter a discrepancy in the bearing output, which produces negative values while it should be within the range of 0-360 degrees.

Code:

The provided code utilizes the Haversine formula to calculate both distance and bearing:

from math import radians, cos, sin, asin, sqrt

def haversine(lon1, lat1, lon2, lat2):
    # Convert decimal degrees to radians
    lon1, lat1, lon2, lat2 = map(radians, [lon1, lat1, lon2, lat2])

    # Haversine formula
    dlon = lon2 - lon1
    dlat = lat2 - lat1
    a = sin(dlat/2)**2 + cos(lat1) * cos(lat2) * sin(dlon/2)**2
    c = 2 * asin(sqrt(a))
    r = 6371 # Radius of earth in kilometers
    return c * r

Bearing Calculation:

The issue with the provided code lies in the bearing calculation. To correct it, we need to modify the line:

Bearing = atan2(cos(lat1)*sin(lat2)-sin(lat1)*cos(lat2)*cos(lon2-lon1), sin(lon2-lon1)*cos(lat2))

To:

Bearing = degrees(atan2(sin(lon2-lon1)*cos(lat2), cos(lat1)*sin(lat2)-sin(lat1)*cos(lat2)*cos(lon2-lon1)))

This adjustment ensures that the bearing output aligns with the expected range of 0-360 degrees.

Conclusion:

With the bearing calculation fixed, the code now accurately determines the distance and bearing between the provided GPS points. The Haversine formula proves to be a robust tool for geographical calculations, enabling precise measurement of distances on the Earth's surface.

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