Coordinate Reference Systems (CRS) and Geodetic Datums: What’s the difference?

Coordinate Reference Systems (CRS) and Geodetic Datums: What’s the difference?

Coordinate Reference Systems (CRS) and geodetic datums are both used to represent the Earth’s surface, but they are different concepts, and importantly, serve different purposes. We provide definitions, highlight their differences and considerations for practical applications.

Coordinate Reference System (CRS)

A CRS is a coordinate-based system that provides a standardised framework for describing and locating points on the Earth’s surface. CRS is primarily used to represent specific locations on the Earth’s surface with precision and consistency.

A CRS can also be referred to as a spatial reference system (SRS) in many cases.

It defines a set of coordinates that can be used to represent the location of a point on the Earth’s surface.

A CRS typically includes a reference point (an origin), a set of axes (coordinate axes), and a unit of measurement (such as metres).

Geodetic Datum

A geodetic datum, on the other hand, is a mathematical model that defines the shape and size of the Earth’s surface, as well as the location of a reference point (the geodetic origin) and the orientation of the axes.

A geodetic datum provides the framework for measuring and comparing positions on the Earth’s surface.

It includes parameters describing the Earth’s ellipsoidal shape (semi-major and semi-minor axes), the flattening of the Earth, and the position of the datum origin.

Geodetic datums are essential for achieving high accuracy in geospatial measurements, especially over large areas.

What’s the difference?

While a CRS and a geodetic datum both provide frameworks for representing the Earth’s surface, they are different in their scope and purpose.

They serve distinct purposes in spatial representation and measurement.

The main differences between Coordinate Reference Systems and Geodetic Datums

Coordinate Reference Systems (CRS)Geodetic Datums
USESA CRS is used to represent the location of a point on the Earth's surfaceA geodetic datum is used to define the shape and size of the Earth's surface and the reference point used to measure positions
PRIMARY FOCUSA CRS deals primarily with coordinate systemA geodetic datum deals with the underlying shape and size of the Earth's reference ellipsoid
DEFINITIONSCRS definitions typically remain consistentGeodetic datums may evolve over time due to improvements in measurement techniques and advancements in geodesy
OPTIONSMultiple CRS are availableMultiple geodetic datums are available

It’s important to note that in many cases, CRSs are defined based on specific geodetic datums, ensuring compatibility and accuracy in spatial representations.

For example, the UTM system uses the WGS84 geodetic datum.

The decision between which CRS or geodetic datum to use

There are multiple choices of both CRS and geodetic datums available for users to select from.

The choice of CRS and geodetic datum depends on various factors such as the geographic region, application, and desired level of accuracy.

Geographic Region

Geographic Region

Different regions of the world may use specific CRS and geodetic datum combinations that are optimised for that region’s geographical characteristics.

Learn about the geodetic datums we use and reference in Australia.

Applications

Application

The type of application you’re working on can influence your choice of CRS and geodetic datum.

For example, surveying and mapping applications often require high accuracy, so a CRS and geodetic datum that offer precision are chosen. On the other hand, less accurate CRS and datum choices may be suitable for applications like general-purpose Geographic Information Systems or web mapping.

Accuracy

Desired Level of Accuracy

The level of precision required for a particular project or task is a crucial deciding factor. Some CRS and geodetic datum combinations are designed to provide centimetre-level accuracy, while others may provide accuracy at the metre or even decimetre level. So the choice really depends on the project’s specific accuracy requirements.

In practice, these above factors need to be carefully considered to ensure users choose the CRS and geodetic datum that is appropriate and aligns to their needs.

Considerations include whether it accurately represents geospatial data, can be integrated seamlessly with other data sources or used in specific analysis or modeling purposes. This will help avoid errors and inconsistencies in geospatial data handling and analysis.

Practical uses for CRS and geodetic datums

In practical terms, when working with geospatial data and mapping, you often need to specify both the CRS and the geodetic datum to ensure accurate and consistent spatial referencing and calculations. Keep in mind different geographic regions and applications may use specific datums and CRS to meet their needs, so understanding the distinction between them is essential for accurate geospatial referencing and analysis.

How to set these in Snowflake

If using a Geography data type the CRS used is WGS 84 and cannot be changed.

If using the Geometry data type, the CRS (or SRS) can be set with the ST_SETSRID function. To change the CRS of a geometry, use the ST_TRANSFORM function.

SELECT
ST_TRANSFORM(
ST_GEOMFROMWKT('POINT(389866.35 5819003.03)', 32633),
3857
) AS transformed_geom;

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What is H3?

What is H3?

There are a number of geospatial indexing systems which caters to spatial data types, query requirements, and use cases, with the choice often depending largely on the needs of your geospatial application and type of data. H3 is the relatively newer kid on the geospatial block, promising accuracy and scalability. Let’s delve in to understand its defining characteristics, how it works, and its practical applications.

What is H3?

H3 is a geospatial indexing system developed by Uber Technologies. It’s designed to partition the Earth’s surface into a hierarchical grid of hexagons. Each hexagon is assigned a unique H3 index, and this grid provides a way to represent and analyse geographic data with consistent precision.

In simpler terms, H3 is a way of breaking down the world into pieces, similar to how a jigsaw puzzle has pieces that fit together. These pieces are shaped like hexagons, like the honeycomb in a beehive.

These hexagons come in different sizes, so bigger hexagons can be used to talk about big areas like a country, whereas small hexagons can be used to talk about tiny areas like a neighbourhood.

Each of these hexagons is assigned a special code to help computers and maps understand where a place is on Earth. So instead of saying you’re at a certain latitude or longitude, you can simply give the code and your location can be pinpointed exactly.

Key characteristics of H3

  1. Hierarchical Grid
    This geospatial indexing system uses a hierarchical structure with multiple levels of hexagons. At each level, hexagons are subdivided into smaller hexagons, providing a scalable way to represent locations at different levels of detail.
  2. Uniform Precision
    Uniform precision across the globe means that hexagons at the same level of the hierarchy will represent approximately the same area, and are consistently spaced between hexagons.
  3. Spatial Relationships
    H3 provides better spatial relationships than traditional rectangular grids like latitude and longitude or Geohash. Hexagons have a more natural fit for mapping many real-world features and are less prone to distortions, especially near the poles.
  4. Resolution Levels
    By supporting multiple resolution levels, this system allows users to choose the appropriate level of detail for their application. Higher resolution levels provide more precision but may result in a larger number of hexagons to manage.
  5. Efficient Spatial Queries
    H3 makes it efficient to perform spatial queries, such as point-in-polygon tests, nearest-neighbor searches, and spatial aggregations. This is particularly valuable for applications like ride-sharing, logistics, and urban planning.
  6. Open Source
    H3 is open-source and available to the public, making it accessible for developers and researchers to use and contribute to its development.
  7. Geospatial Libraries
    H3 has been integrated into various geospatial libraries and programming languages, making it easier for developers to work with this geospatial indexing system in their applications.

How does H3 work?

Here’s a technical explanation of how H3 works:

  1. Hexagonal Grid
    H3 starts by subdividing the Earth’s surface into hexagonal grids. These hexagons are the basic building blocks of the system.
  2. Hierarchical Levels
    H3 employs a hierarchical approach with multiple zoom levels. At each zoom level, the hexagons are divided into smaller hexagons. This hierarchy allows for representing locations with varying levels of precision.
  3. Unique Hexagon IDs
    Each hexagon in the grid is assigned a unique identifier called an H3 index. These indices are used to identify specific geographic areas. An H3 index consists of two parts: a base cell and a resolution level. The base cell determines the general area, and the resolution level refines the precision within that area.

What does H3 look like?

This geospatial indexing system partitions the globe into hexagons for accurate analysis, as indicated in this image.

Geohash vs H3 Comparison

Source: Uber

Real estate applications of H3

As you can imagine, a geospatial indexing system developed by ride-share company, Uber would make it indispensable for ride-sharing and navigation, optimising driver and passenger matching, but also in determining best pickup and drop off points, fare calculations and route planning.

Due to its ability to represent geo locations accurately and analyse geographical data efficiently, it has wide appeal and vast uses in real-estate too. In most situations, anytime you might use the more commonly used Geohash, you could potentially use H3.

So, how does H3 compare?

H3 is one of the geospatial indexing systems at your disposal, answering to various spatial data types, query requirements, and use cases. However, the choice between using H3 and other indexing systems depends largely on the needs of your geospatial application and type of data.

Read how H3 and Geohash compare if you’re considering which system to adopt.

Snowflake releases H3 functionality

Snowflake provides SQL functions that enable you to use H3 with GEOGRAPHY objects.
This preview feature is now available to all accounts.

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