## Name

Reverse_Geocode — Takes a geometry point in a known spatial ref sys and returns a record containing an array of theoretically possible addresses and an array of cross streets. If include_strnum_range = true, includes the street range in the cross streets.

## Synopsis

`record Reverse_Geocode(`geometry pt, boolean include_strnum_range=false, geometry[] OUT intpt, norm_addy[] OUT addy, varchar[] OUT street`)`;

## Description

Takes a geometry point in a known spatial ref and returns a record containing an array of theoretically possible addresses and an array of cross streets. If include_strnum_range = true, includes the street range in the cross streets. include_strnum_range defaults to false if not passed in. Addresses are sorted according to which road a point is closest to so first address is most likely the right one.

Why do we say theoretical instead of actual addresses. The Tiger data doesn't have real addresses, but just street ranges. As such the theoretical address is an interpolated address based on the street ranges. Like for example interpolating one of my addresses returns a 26 Court St. and 26 Court Sq., though there is no such place as 26 Court Sq. This is because a point may be at a corner of 2 streets and thus the logic interpolates along both streets. The logic also assumes addresses are equally spaced along a street, which of course is wrong since you can have a municipal building taking up a good chunk of the street range and the rest of the buildings are clustered at the end.

Note: Hmm this function relies on Tiger data. If you have not loaded data covering the region of this point, then hmm you will get a record filled with NULLS.

Returned elements of the record are as follows:

1. `intpt` is an array of points: These are the center line points on the street closest to the input point. There are as many points as there are addresses.

2. `addy` is an array of norm_addy (normalized addresses): These are an array of possible addresses that fit the input point. The first one in the array is most likely. Generally there should be only one, except in the case when a point is at the corner of 2 or 3 streets, or the point is somewhere on the road and not off to the side.

3. `street` an array of varchar: These are cross streets (or the street) (streets that intersect or are the street the point is projected to be on).

Availability: 2.0.0

## Examples

Example of a point at the corner of two streets, but closest to one. This is approximate location of MIT: 77 Massachusetts Ave, Cambridge, MA 02139 Note that although we don't have 3 streets, PostgreSQL will just return null for entries above our upper bound so safe to use. This includes street ranges

```SELECT pprint_addy(r.addy[1]) As st1, pprint_addy(r.addy[2]) As st2, pprint_addy(r.addy[3]) As st3,
array_to_string(r.street, ',') As cross_streets
FROM reverse_geocode(ST_GeomFromText('POINT(-71.093902 42.359446)',4269),true) As r;

result
------
st1                                  | st2 | st3 |               cross_streets
-------------------------------------------+-----+-----+----------------------------------------------
67 Massachusetts Ave, Cambridge, MA 02139 |     |     | 67 - 127 Massachusetts Ave,32 - 88 Vassar St```

Here we choose not to include the address ranges for the cross streets and picked a location really really close to a corner of 2 streets thus could be known by two different addresses.

```SELECT pprint_addy(r.addy[1]) As st1, pprint_addy(r.addy[2]) As st2,
pprint_addy(r.addy[3]) As st3, array_to_string(r.street, ',') As cross_str
FROM reverse_geocode(ST_GeomFromText('POINT(-71.06941 42.34225)',4269)) As r;

result
--------
st1               |               st2               | st3 | cross_str
---------------------------------+---------------------------------+-----+------------------------
5 Bradford St, Boston, MA 02118 | 49 Waltham St, Boston, MA 02118 |     | Waltham St
```

For this one we reuse our geocoded example from Geocode and we only want the primary address and at most 2 cross streets.

```SELECT actual_addr, lon, lat, pprint_addy((rg).addy[1]) As int_addr1,
(rg).street[1] As cross1, (rg).street[2] As cross2
FROM (SELECT address As actual_addr, lon, lat,
reverse_geocode( ST_SetSRID(ST_Point(lon,lat),4326) ) As rg
FROM addresses_to_geocode WHERE rating > -1) As foo;

actual_addr                     |    lon    |   lat    |                 int_addr1                 |     cross1      |   cross2
-----------------------------------------------------+-----------+----------+-------------------------------------------+-----------------+------------
529 Main Street, Boston MA, 02129                   | -71.07181 | 42.38359 | 527 Main St, Boston, MA 02129             | Medford St      |
77 Massachusetts Avenue, Cambridge, MA 02139        | -71.09428 | 42.35988 | 77 Massachusetts Ave, Cambridge, MA 02139 | Vassar St       |
26 Capen Street, Medford, MA                        | -71.12377 | 42.41101 | 9 Edison Ave, Medford, MA 02155           | Capen St        | Tesla Ave
124 Mount Auburn St, Cambridge, Massachusetts 02138 | -71.12304 | 42.37328 | 3 University Rd, Cambridge, MA 02138      | Mount Auburn St |
950 Main Street, Worcester, MA 01610                | -71.82368 | 42.24956 | 3 Maywood St, Worcester, MA 01603         | Main St         | Maywood Pl
```