spatial-analysis

Python scripts I use for the analysis of spatial data

Installation

You can either download/clone this repo and use as is, or you can pip install it with the following command:

pip install git+https://github.com/nathanrooy/spatial-analysis

Usage

Haversine

Calculate the distance between two longitude/latitude pairs using the Haversine formula. For more information on the math/implementation details, see this blog post [here].

>>> from spatial import haversine
>>> p1 = [-84.4941318, 39.113223]     # p1=[longitude_1, latitude_1]
>>> p2 = [-81.4061265, 41.250386]     # p2=[longitude_2, latitude_2]
>>> haversine(p1, p2)                 # meters (default)
353922.9402484654

By default, the distance returned is in meters (m), however additional units can be specified as follows:

>>> haversine(p1, p2, units='km')  # kilometers
353.9229402484654
>>> haversine(p1, p2, units='mi')  # miles
219.9174513051292
>>> haversine(p1, p2, units='nm')  # nautical miles
191.10309948621241
>>> haversine(p1, p2, units='yd')  # yards
387054.83402915805
>>> haversine(p1, p2, units='ft')  # feet
1161164.1428910822
>>> haversine(p1, p2, units='m')   # meters
353922.9402484654

Vincenty Inverse

If more accuracy is needed than what the Haversine formula can provide, a good option is Vincenty's Inverse formulae. For more information on the math/implementation details, see this blog post [here].

>>> from spatial import vincenty_inverse as vi
>>> p1 = [-84.4941318, 39.113223]     # p1=[longitude_1, latitude_1]
>>> p2 = [-81.4061265, 41.250386]     # p2=[longitude_2, latitude_2]
>>> vi(p1, p2)                        # meters (default)
354188.01859971555

Just like the haversine method, vincenty_inverse supports meters,kilometers,miles,nautical miles,yards, and feet as seen below:

>>> vi(p1, p2, units='km')  # kilometers
354.1880185997156
>>> vi(p1, p2, units='mi')  # miles
220.08216330532386
>>> vi(p1, p2, units='nm')  # nautical miles
191.24623034541875
>>> vi(p1, p2, units='yd')  # yards
387344.7272391767
>>> vi(p1, p2, units='ft')  # feet
1162033.8222521099
>>> vi(p1, p2, units='m')   # meters
354188.01859971555

Since Vincenty's inverse formulae is an iterative approach, it employs two methods for stopping. The first is to simply specify a maximum number of iterations using maxIter as seen below:

>>> vi(p1, p2, maxIter=500)

The default value for maxIter is 250 iterations. The second stopping method is specified using tol. When the iteration-to-iteration difference in distance residual drops below the value specified by tol, the iteration loop terminates. By default, this value is 1E-12.

>>> vi(p1, p2, tol=1E-10)

When using tol as the primary stopping criteria, make sure to increase maxIter to a sufficiently high level so as to not force an early exit.