Basics of Location Data
Location data are information about the geographic positions of devices (such as smartphones or tablets) or structures (such as buildings, attractions).
The geographic positions of location data are called coordinates, and they are commonly expressed in Latitude and Longitude format.
Additional attributes such as elevation or altitude may be included and helps data users get more accurate picture of the geographic positions of their data.
People commonly mean GPS data when they talk about location data. In reality, there are various types of location data.
It is important to know how the data is collected as it determines the accuracy and depth of the collected data, this have direct implications on the suitability and usability of the data for a business.
The combination of these two components specifies the position of any location on the surface of Earth. Lat/long data points can be expressed in decimal degrees (DD). The other convention for expressing lat/long is in degrees, minutes, seconds (DMS). For example, below is the same point expressed in DD and DMS (you can find many converters online):
DD: 47.21746, -1.5476425
DMS: 47° 13’ 2.856”, 1° 32’ 51.5106”
You can see these DMS coordinates at airports, where the gates are marked in degrees, minutes and seconds
Another important thing to understand about decimal degrees is that they carry a level of precision. The number of decimal places required for a particular precision at the equator is:
A value in decimal degrees to a precision of 4 decimal places is precise to 11.132 meters at the equator. A value in decimal degrees to 5 decimal places is precise to 1.1132 meter at the Equator.
Geohash
Invented by Gustavo Niemeyer, Geohash is a geocoding system that allows the expression of a location anywhere in the world using an alphanumeric string. Geohash is a unique string derived by encoding and reducing the two-dimensional geographic coordinates (latitude and longitude) into a string of digits and letters. A Geohash can be as vague or accurate as needed depending on the length of the string.
Geohashes use Base-32 alphabet encoding i.e., uses all digits 0-9 and almost all lower-case letters except "a", "i", "l" and "o". It is a convenient way to express a location anywhere in the world. Geohashes basically divide the world into a grid with 32 cells. Each cell will also contain 32 cells, and each one of these will contain 32 cells (and so on repeatedly).
Adding characters to the geohash sub-divides a cell, effectively zooming in to a more detailed area. This is referred to as geohash precision. Geohash Precision is a number between 1 and 12 that specifies the precision (i.e., number of characters) of the geohash. Each additional character of the geohash adds precision to your location.
At Quadrant, we usually provide 12-precision geohash for all the events.
The cell sizes of geohashes of different lengths are as follows; note that the cell width reduces moving away from the equator (to 0 at the poles):
Visually:
Geohashes have a certain property that makes them suitable for geospatial queries like localized search (points with similar geohashes that are near each other with the same geohash prefixes).
For example, if you want to list the number of persons who were seen in and around the Empire State Building, you can first determine the geohashes you want to cover and then run a simple query:
SELECT * FROM table_name WHERE geohash like 'dr5ru6%' or geohash like 'dr5ru3%' or geohash like 'dr5rud%' or geohash like 'dr5ru9%';
Doing this improves processing times and costs, as it allows you to quick sort through large amounts of data and work on more precise subsets of data. In fact, most data scientists use geohash to quickly sort through large location data sets, and then build specific queries (such as polygons) around the specific point/area of interest. In doing so, you can reduce your costs and increase your speed of processing, while maintaining accuracy and precision.
Types of geo-indexing systems
Geodata is information about geographic locations that is stored in a format that can be used with a geographic information system (GIS). For example, at Quadrant, our geo data is stored in three different formats which can be used for geospatial analysis: Country Codes, Latitude & Longitude coordinates, and Geohashes.
Country Codes
Usually the ISO2 2-digit alpha country code represents the locale of the devices i.e. the devices registered to users from the stipulated countries. At Quadrant, in addition to the country code, we also derive another attribute called ‘country’, where the country represents the events / devices that are seen within the geographical boundaries of stipulated countries. For example, if you want to get the total number of events seen within Singapore by using its country code, you can run a simple query: SELECT count(*) FROM table_name WHERE country = ‘SG’;
Lat/long coordinates
Coordinates can be used to identify where an event was recorded. We can use the coordinates to either list devices from a single location: SELECT * FROM table_name WHERE latitude = ‘41.9022’ and longitude = ‘-76.37695’
Or we can use a bounding box, which is an area defined by two longitudes and two latitudes, to get information from a certain area or a country.
Bounding box for Australia:
To get the total number of events seen within Australia by using a bounding box, you can run a simple query:
SELECT count(*) FROM table_name WHERE (latitude BETWEEN -43.96119063892024 and -10.660607953624762 and longitude BETWEEN 112.5 and 154.51171875);
Geofencing
A geo-fence is a virtual perimeter for a real-world geographic area. They could be a radius around a single point, or a predefined set of boundary. Once a geo-fenced boundary is defined, the opportunities what businesses can do is limited by only their creativity.
One common use of geo-fencing is for businesses to set up geo-fences around their competitors. And push marketing promotions to customers that enters the zone. This is sometimes referred to as geo-conquest. Businesses could also provide Location Based Services within geo-fenced region.
Geofencing is ideal for catchment area analysis; a catchment is an area from which businesses expects to draw their customers from. Catchment areas can help businesses identify where to run their next marketing campaign or set up their next store.
Latitude and longitude shows the position of a device or structure. They are commonly accompanied by horizontal accuracy, which tells users the degree of error in a particular data point.
Altitude or elevation pinpoints the height above a reference point, usually sea level.
Timestamps are typically used for logging events alone or in a sequence.
In the case of location data, they provide context to the movement of a particular device.
Location data feeds commonly record timestamps in Unix time, otherwise known as Unix Epoch time, or Epoch for short.
Internet Protocol Address, or commonly known as IP address, is a numerical label assigned to each device connected to a computer network.
IP addresses can be used for location, however, accuracy can be problematic. One common occurrence when looking up an IP address's location is being directed to the network provider's location.
Depending on the business uses, IP address may provide a good rough measure of geographic location.
The Mobile Ad ID or Device ID is a unique 36-character identifier of smartphones. Mobile Ad IDs helps to identify, track and differentiate between mobile devices.
The Mobile Ad ID/Device ID is widely used across the marketing ecosystem, especially for targeting devices with ads through demand-side platforms (DSPs) and supply-side platforms (SSPs) in the app advertising supply chain.
For iOS devices the unique device ID is called Identifier For Advertising (IDFA). Apple customers can receive their mobile device ID numbers through iTunes or the Apple App Store. Before the rollout of iOS 6, this device ID was called a Unique Device Identifier (UDID) in the Apple ecosystem.
For Android devices the device ID is called Google Advertising ID (GAID). These mobile device IDs are randomly generated during the first activation of a mobile device and remain constant for the lifetime of the device unless reset by the user. Typically the IDs belonging to iOS devices will be in upper-case and those belonging to Android devices will be in lower-case.
As they are a unique identifier, they can be used to calculate aggregated metrics such as Daily Active Users (DAU), Monthly Active Users (MAU), etc. To learn more about the different queries you can run using the device ID please visit our Resources library.
Horizontal Accuracy
GPS satellites broadcast their signals in space with a certain accuracy. However, this accuracy is not directly controllable by the app developer, at least not through any software mechanism. The accuracy received depends on additional factors such as satellite geometry, signal blockage, atmospheric conditions, and receiver design features/quality.
Horizontal Accuracy is a radius around a 2D point, implying that the true location is somewhere within the circle formed by the given point as a center and the accuracy as a radius. As shown in the example below, the exact location of the device will be anywhere within the orange shaded circle:
Different use cases require different levels of accuracy readings. For example, a relatively weak level of horizontal accuracy would be acceptable in city- or country-level analyses, as opposed to a more precise segmentation of users that visited stores within a retail park.
It is important to understand the difference between the horizontal accuracy of a point and the precision of a point, which discussed in a previous post, is represented by the number of decimal points in the latitude and longitude coordinates. Simply put, the precision of a point is a measure of how exact the pinpoint location of a data point is on a map. The horizontal accuracy is a measure of how close the data point is to the actual (ground truth) point.
