What is a Geohash and How is it Used?

What is a Geohash and How is it Used?

What is a geohash and how is it used? We break it down here.

What is a Geohash?

Geohashing is a geocoding system that encodes geographic coordinates (latitude and longitude) into a short and compact string of characters.

Think of it like a secret code for locations on Earth – a short and easy-to-understand code. It turns a place’s latitude and longitude, which are like its coordinates on a big map, into a simple code.

Imagine you want to tell someone exactly where you are in the world.

Instead of saying, “I’m at latitude 40.7128 degrees North and longitude 74.0060 degrees West,” you can say, “I’m at 6gkzwgjz.”

This shorter code still tells them exactly where you are but is much easier to share or remember.

In a nutshell, a geohash is a clever way to turn complex latitude and longitude coordinates into simple codes that make it easier to talk about places and share location information.

This is also what makes geohash a versatile tool, making it easier to work with location-based data and services in a wide range of industries and applications.

How Does Geohash Work?

The main concept behind Geohash is to divide the world into a grid of rectangles and then represent each of these rectangles with a unique code. This code becomes shorter as you zoom out to cover larger areas and gets longer as you zoom in for more precision.

Here’s a technical explanation of how Geohash works:

  1. Dividing the world into rectangles
    Geohash starts by dividing the Earth into a grid of rectangles. The whole Earth is initially represented by one big rectangle.
  2. Choosing a binary representation
    Each rectangle is further divided into smaller rectangles. Geohash uses a binary search approach to determine which half of a rectangle contains a given point.
    It assigns a binary digit of 1 for the upper half of the rectangle and 0 for the lower half.
  3. Building the geohash string
    – Starting with the whole Earth as one big rectangle, geohash determines whether a point falls into the top or bottom half (binary digit 1 or 0) and appends that digit to the geohash string.
    – The Earth is then divided into the top or bottom half based on the chosen digit.
    – This process is repeated iteratively until you have the desired level of precision or length in the geohash string.
  4. Precision and length of the geohash
    – The length of the geohash string determines the level of precision: A shorter geohash represents a larger area, while a longer geohash represents a smaller and more precise area.
    – For example, a geohash of length 5 might represent a region the size of a city, while a geohash of length 10 could pinpoint a location within a few meters.
  5. Encoding characters
    – To enable the geohash string to be more easily read by humans and generally be more user-friendly, it translates the binary digits into a set of characters. Geohash typically uses a character set of 32 characters: 0-9 and the letters a through z (excluding i, l, o).
  6. Final geohash
    – The result is a geohash string that represents a specific geographic location. This string is both compact and can be easily shared or stored.

What Does Geohash look like?

Geohash divides the world into a grid of rectangles, as indicated in this portion of the world map.

Geohash

Real Estate Applications of Geohash

There are many practical applications for geohash across a broad range of industries.

Here we’ve narrowed down these examples to real-estate uses for geohash:

  • Location-based searches: Geohash is used in location-based search engines and applications, showing nearby points of interest, businesses, or places based on their current location or a specified area.
  • Geofencing: Geohash is employed to create geofences, or virtual boundaries, which can be used for triggering actions or alerts when a device or user enters or exits a specific geographic area, such as location-based marketing, asset tracking, and security applications.
  • Mapping and cartography: Geohash is used in cartography to represent geographic data efficiently. It can simplify the storage and retrieval of spatial information in mapping systems.

These are just a few examples, and the applications of geohash continue to expand as location-based data becomes increasingly important across various domains.

The simplified representation of geographic coordinates makes geohash more accessible and user-friendly, which is why it is such a versatile geocoding system with a wide range of uses in real-estate and beyond.

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What is a Cadastre?

What is a Cadastre?

Cadastres are used extensively in real estate and beyond. We break down what they are, how they’re stored, used and maintained in Australia.

What is a cadastre?

A cadastre is a comprehensive register or database that captures detailed information about real estate or land within a specific jurisdiction; with each cadastral record defining its respective boundary, as determined by cadastral surveying. Important attributes such as property location, characteristics, and value are also included in a cadastre.

Essentially, it serves as a vital legal and administrative tool for managing and regulating land ownership and usage, while also used for collecting property taxes, assessing land values, and resolving any disputes related to properties. It typically contains property boundaries, ownership details, and physical descriptions, such as size, shape, and topography. It may even encompass additional information pertaining to land use, zoning regulations, building permits, and environmental regulations.

Which file types are typically used to store a cadastre?

These file types are commonly used to store a cadastre:

  • Shape file (.shp)
  • GDB (.gdb)
  • Geojson (.geojson)

File sizes of cadastre files can become quite large, depending on the extent of the coverage.

For example, the cadastre for New South Wales (NSW) in Australia is approximately 1.4 GB when compressed. Working with large files can be more manageable in cloud environments like Amazon Web Services (AWS). These cloud platforms provide substantial computing power that can be accessed when needed, then switched off in a pay-per-use model to more efficiently handle the processing requirements of large cadastre files.

Primarily spatial files, they contain geometry data that represents the boundaries of each land parcel within the cadastre. The geometry information can be stored and represented in various text formats, which are universally understood by spatial data software applications.

The most common approaches for storing and representing the geometries are

which ensure compatibility and ease of interpretation across different software tools and platforms.

Additional attributes relating to the cadastre can also be served within the same spatial file, such as through the properties key within a cadastre’s GeoJSON document. Other formats such as WKT or WKB do not support the direct inclusion of additional attributes to the geometry, but can be associated with in different ways such as in an accompanying csv file containing any additional attributes.

What does a cadastre look like on a map?

The way a cadastre is represented on a map can vary significantly depending on the source of the data and the configuration settings used in the mapping software. Different factors like styling, symbols, and labeling options can influence how the cadastre appears visually on the map.

The following image is a typical representation of cadastre on a map, showing boundary lines that delineate the various land parcels or lots. These boundary lines help visually separate one property from another. While lot numbers are used as an identifying label to provide a quick reference to specific parcels within the cadastre.

Cadastre represented on a map

How does a cadastre look in a Snowflake Marketplace listing?

To incorporate a cadastre into Snowflake, it needs to be transformed into a table structure. The process involves loading the cadastre data in the form of GeoJson as a VARIANT data type in Snowflake. Then the GeoJson features are flattened and converted into individual rows within the table.

Alternatively, the cadastre file can be converted to a flat file outside of Snowflake, then loaded into Snowflake as you would with any other flat file.

This flattening process makes it easier to query and analyse the cadastre data using standard SQL operations within Snowflake, allowing for efficient storage, retrieval, and analysis of the information.

Attribute {A}Attribute {B}Attribute {C}Geometry
123POLYGON((30 10, 40 40, 20 40, 10 20, 30 10))

*The actual columns (feature attributes) available for each piece of land registered on a cadastre is dependent on the maintainer/publisher of the cadastre.

Australian cadastres

In Australia, individual state and territory governments are responsible for the maintenance of cadastres, rather than the federal government.

Each state and territory has its own land administration agency responsible for maintaining cadastres within their jurisdiction.

The following organisations maintain cadastres:

These agencies are responsible for updating and managing the cadastre, including recording changes to property ownership, boundaries, and other relevant information. They also provide access to the cadastre and related services to the public, including title searches, property reports, and other land-related information.

Who provides cadastres on Snowflake Marketplace?

  • The Proptech Cloud
  • Geoscape
  • Precisely

What would a cadastre be used for?

Cadastres can be used to:

  • Identify the unique number of properties in a country,
  • Identify changes to properties (merges, subdivisions, title registrations),
  • Spatially link other spatial information to a property,
  • Spatially lookup a property based, i.e. lookup properties based on latitude and longitude coordinates, or based on geospatial shape (think drawing a circle on map to search for properties on the map),
  • Represent property boundaries on a map.

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Unlocking Affordable Housing in Australia: The Data Revolution

Unlocking Affordable Housing in Australia: The Data Revolution

Australia’s property market has been a subject of discussion for years, fuelled by soaring prices, scarcity, and affordability issues. Enter proptech start-ups, which are leveraging technology to offer innovative solutions to these issues. Central to this wave of innovation is data, and its accessibility is being revolutionised by digital data marketplace platforms.

The Old Guard: Barriers to Entry

Historically, one of the largest barriers to entry for proptech start-ups was access to quality data. Whether it’s property values, zoning laws, ownership, or construction costs, such data sets are often fragmented, expensive, or behind bureaucratic walls. The effort and capital required to acquire and harmonise this data kept many potential innovators out of the space.

Complicating matters further, there is a noticeable lack of skilled data engineers available to streamline the complex process of data collection and integration, making it even more challenging for start-ups to break into the market.

Digital Data Marketplaces: A Game Changer

Centralised data repository platforms like the Snowflake Marketplace are breaking down these barriers. By providing a centralised, easily accessible marketplace for data acquisition and use, these platforms are significantly reducing the time and capital required for start-ups to get their operations off the ground. Start-ups no longer need to invest in expensive data scraping techniques or negotiate with multiple data providers; a treasure trove of valuable information is now just a few clicks away.

Speeding Up Time-to-Market

With the availability of easy-to-use data, proptech start-ups and established businesses can accelerate their development cycles. Time-to-market is a critical factor for any business, and in a sector as dynamic as real estate, this could not be more crucial. Platforms like Snowflake have enabled proptechs to launch and iterate products faster, making it easier to adapt to market needs, and more readily generate property solutions – including bringing affordable housing to the public.

Democratising investment opportunities

Driving Policy with Public-Private Partnerships

Easier access to data may stimulate public-private partnerships. Governments can leverage the insights generated by proptechs to guide policy decisions, be it in the form of zoning laws, tax incentives, or housing grants. With readily available data, these decisions can be made quicker and with more precision, ultimately benefitting the housing market at large.

Security and Governance

While data marketplace platforms make data more accessible, they also prioritise data security and governance. Reputable platforms will feature and document industry-leading controls and protocols to ensure high levels of governance for account holders and users, as well as all the data which is stored and accessed.

An “Even” Data Playing Field

When considering any “off-the-shelf” data from centralised data repositories, users benefit from a streamlined data acquisition process. This grants users access to a wealth of re-usable data offered by data providers, contributing to an even playing field as democratised data is universally available.

For tailored requirements, some data providers on Snowflake Marketplace make certain data products available by request.

Regardless of how you acquire the data, it is ultimately what you do with it that will derive the most meaning and value.

Whether it be the basis for automation and AI, personalisation, analysis and insights, the integration of that data forms the foundation for informed business decision making, innovation and progress.

The Data Revolution

The democratisation of data through platforms is a necessity for driving innovation in Australia’s housing market. By eliminating barriers to entry, these platforms allow organisations to focus on what they do best. In an industry begging for disruption, this newfound accessibility to data sets the stage for a seismic shift towards a more equitable and affordable housing landscape in Australia. The future looks promising, and much of that promise is driven by data.

 

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What’s the Difference Between GDA94 and GDA2020?

What’s the Difference Between GDA94 and GDA2020?

Geodetic datums, or geodetic systems, are often used by proptechs. Here is a rundown of everything you need to know about the different geodetic datums we use and reference in Australia.

What is a geodetic datum?

A geodetic datum is a set of reference points and parameters used to define the shape and orientation of the Earth’s surface for mapping and surveying purposes. It provides a coordinate system that allows locations on the Earth’s surface to be accurately described and located. In Australia, we use Geodetic Datum of Australia 1994(DA94) and Geodetic Datum of Australia 2020 (GDA2020).

History of Australia’s geodetic datums

Prior to GDA94, Australian surveyors primarily used the Australian Geodetic Datum 1966 (AGD66), which was based on a network of ground-based survey points and astronomical observations.

AGD66 was the standard datum used for mapping and surveying in Australia for several decades until it was superseded by GDA94 in the 1990s.

The decision to switch to GDA94 was driven by the need for a more accurate and up-to-date geodetic datum that could take advantage of advances in geospatial technology such as GPS. AGD66 was also affected by tectonic movements and other changes in the Earth’s surface, which made it increasingly difficult to use for accurate positioning and navigation.

GDA94 (Geocentric Datum of Australia 1994) was the geodetic datum used in Australia from 1994. Based on a mathematical model of the Earth’s surface defined using measurements from a network of ground-based survey points, and used as the standard datum for mapping and surveying in Australia.

Now, GDA2020 (Geocentric Datum of Australia 2020) is the current geodetic datum used in Australia. It was introduced in 2017 to replace GDA94 and is based on more recent measurements of the Earth’s surface using advanced satellite and ground-based technology.

GDA2020 provides a more accurate representation of the Earth’s surface than GDA94, and is designed to be compatible with global positioning systems (GPS) and other modern geospatial technologies.

Even though AGD66, and to some extent GDA94, are no longer the primary datums used in Australia, it’s still important to maintain historical data that was referenced to this datum. It is possible to transform data from AGD66 to GDA94 or GDA2020 using appropriate transformation parameters to ensure compatibility and accuracy when comparing or integrating data from different sources.

Conversions between geodetic datums

Conversions between AGD66 and GDA94 are not 100% accurate, because the two datums are based on different mathematical models of the Earth’s surface with different reference points and parameters.

To convert data from AGD66 to GDA94 (or vice versa), a mathematical transformation must be applied that takes the differences between the two datums into account. This transformation involves adjusting the latitude, longitude, and height values of the data to align with the new datum.

However, there are many factors that can affect the accuracy of this transformation, such as:

  1. The quality and accuracy of the original data: If the original data was collected using imprecise or inaccurate methods, the transformation may introduce additional errors or inaccuracies.
  2. The complexity of the transformation: Some transformations may require more complex mathematical models or additional parameters to be specified, which can increase the likelihood of errors.
  3. The location and terrain of the data: The accuracy of the transformation can vary depending on the location and terrain of the data. Some areas may be more affected by tectonic movements or other changes in the Earth’s surface, which can make the transformation more challenging.
  4. The type of data being transformed: Different types of data (e.g. points, lines, polygons) may require different transformation methods or parameters, which can affect the accuracy of the transformation.

While conversions between AGD66 and GDA94 can be relatively precise, they’re not 100% accurate. This is due to the inherent differences between the two datums, and the potential for errors or inaccuracies in the transformation process. It’s important to use appropriate transformation methods and understand the limitations and potential sources of error when converting data between different geodetic datums.

The difference between GDA94 and GDA2020

The key differences

The main difference between GDA94 and GDA2020 is their accuracy and the methods used to define them. GDA2020 is a more accurate and up-to-date datum, with improvements in the modeling of the Earth’s surface that take into account changes in its shape over time. This means that positions and distances measured using GDA2020 are more accurate than those measured using GDA94. Additionally, GDA2020 is designed to be compatible with modern geospatial technologies and is expected to be used for many years to come.

It’s worth noting that the difference between GDA94 and GDA2020 may not be significant for many applications, particularly those that don’t require high levels of accuracy. However, for applications that require precise positioning or measurement, such as surveying or mapping, using the correct geodetic datum is imperative to ensure accurate results.

Differences in distance and direction

The average distance and direction difference between GDA94 and GDA2020 depends on the location on the Earth’s surface. In general, the differences between the two datums are greatest in areas with high tectonic activity or areas where the Earth’s surface is undergoing significant changes, such as due to land subsidence or sea level rise.

According to Geoscience Australia, the organisation responsible for geodetic information and services in Australia, the average difference between GDA94 and GDA2020 in Australia is around 1.5 meters. However, this value can vary significantly depending on the location, with some areas showing differences of several meters or more.

The direction of the difference between the two datums also varies depending on the location, as it is related to the direction and magnitude of any tectonic movements or changes in the Earth’s surface. In general, the direction of the difference is determined by the vector between the two datums at a given location.

It’s important to note that the difference between GDA94 and GDA2020 is not constant over time and may continue to change in the future. This is because the Earth’s surface is constantly changing due to tectonic activity, sea level rise, and other factors. As such, it’s important to regularly update geodetic data and use the most up-to-date geodetic datum for accurate positioning and navigation.

Migrating from GDA94 to GDA2020

The differences between the two means that migrating from GDA94 to GDA2020 can present several challenges and issues, particularly for organisations or projects that rely heavily on geospatial data.

Some of the key issues with migrating to GDA2020 include: 

  1. Data compatibility: Data that was created using GDA94 may not be compatible with GDA2020. This can cause issues when trying to integrate or compare datasets that use different datums.
  2. Application compatibility: Applications that were designed to work with GDA94 may not be compatible with GDA2020. This can require updates or modifications to existing software or the adoption of new tools.
  3. Training and expertise: Staff who work with geospatial data may need to be trained on the new GDA2020 datum and its associated tools and workflows. This can take time and resources.
  4. Time and cost: Migrating to GDA2020 can be a complex and time-consuming process, particularly for large organisations or projects. There may be costs associated with updating software, purchasing new equipment, or retraining staff.
  5. Accuracy: While GDA2020 is a more accurate datum than GDA94, some existing data may still be more accurate when referenced to GDA94. This can make it difficult to compare or integrate data from different sources.
  6. Data transformation: In some cases, it may be necessary to transform data from GDA94 to GDA2020, which can introduce errors or inaccuracies. The accuracy of the transformation depends on the quality of the original data and the transformation method used.

Migrating from GDA94 to GDA2020 requires careful planning and consideration of the potential issues and challenges. It’s crucial to work closely with geospatial experts and stakeholders to ensure a smooth and successful transition.

What is WGS84 and why is it used by software?

WGS84 (World Geodetic System 1984) is a geodetic datum used for positioning and navigation purposes. It defines a reference system for the Earth’s surface that allows locations to be specified in latitude and longitude coordinates.

The WGS84 datum was developed by the United States Department of Defense for use by the military and intelligence agencies, but it has since become the standard geodetic datum used by many organisations and applications around the world, including GPS (Global Positioning System) devices and mapping software.

The WGS84 datum is based on a mathematical model of the Earth’s surface that takes into account its shape, size, and rotation. It defines a set of reference points and parameters that allow positions on the Earth’s surface to be accurately calculated and communicated.

The WGS84 datum is widely used because it is compatible with GPS and other global navigation systems, allowing precise positioning and navigation in real-time. However, while there may be regional differences in the Earth’s surface that are not fully captured by the WGS84 model, that other geodetic datums may be more appropriate for certain applications or regions.

How to convert between GDA2020 and WGS84

To convert between GDA2020 (Geocentric Datum of Australia 2020) and WGS84 (World Geodetic System 1984), you can use coordinate transformation parameters provided by geodetic authorities. The transformation process involves converting coordinates from one datum to another using a mathematical model.

In the case of GDA2020 and WGS84, the transformation parameters provided by the Intergovernmental Committee on Surveying and Mapping (ICSM) in Australia are known as the National Transformation Version 2 (NTv2) grid files. These grid files contain the necessary information for accurate transformations.

The accuracy of the transformation depends on the specific region and the quality of the NTv2 grid files used. Always use the most up-to-date and accurate transformation parameters available from reputable sources.

To convert coordinates between the GDA2020 (Geocentric Datum of Australia 2020) and WGS84 (World Geodetic System 1984) datums using Python, you can utilise the pyproj library. pyproj provides a convenient interface to the PROJ library, which is a widely used cartographic projection and coordinate transformation library.

Usage in Australia

In Australia, a lot of data providers are providing data sets in both GDA94 and GDA2020 geodetic datums because the uptake of GDA2020 is not universal. Most data providers of spatial data sets will reference the geodetic datum used to build the data set.

When combining geospatial data sets, ensure you are using a consistent geodetic datum to prevent incorrectly linking two or more shapes.

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Properties, Parcels, Titles and Addresses. What’s The Difference?

Properties, Parcels, Titles and Addresses. What’s The Difference?

​Properties, parcels, titles, addresses. These terms can sometimes be used interchangeably, but are they the same thing?

And if not, what’s the difference? Let’s discuss it here.

Parcel

A “Parcel” refers to a specific portion or subdivision of land within a larger property.

It is a defined area of land with distinct boundaries and can have its own unique identification number. Parcels are often used for administrative or legal purposes, such as land registration.

A parcel can sometimes be referred to a Lot and Plan, which describes the identification number components in some states (e.g. NSW).

A property can have more than one parcel associated with it, e.g. a farm may be made up of several parcels but when it is sold, a parcels are included in the transfer.

Volume Folio

The “Volume Folio” or “Title Reference” is a unique identifier assigned to a property title in the Australian land registration system. It represents the registered ownership and legal description of a property.

The Volume refers to the specific book or register where the title is recorded, while the Folio refers to the page or entry within that volume. The Title Reference is commonly used in land transactions and legal documentation to accurately identify a property.

Address

An “Address” refers to the specific location or postal address of a property. It includes elements such as the street number, street name, suburb, state, and postcode.

The address is used for communication, mail delivery, and identification of a property’s location.

In Australia, addresses are often structured in a standardised format to ensure consistency and facilitate efficient mail handling. A property can have more than one address associated with it, e.g. corner blocks and back lanes.

Property

A “Property” can be many things depending on the context of the data. Some State Governments will provide an identifier for a property, which relates generally to land which can be bought and sold.

In this context, a Property can have one or more Parcels and usually one or more addresses and be recorded on a Volume Folio.

Read our blog What is a Property to gain a greater understanding of why it is difficult to define a “Property”.

Can a parcel appear on more than one volume folio?

No, a parcel typically cannot appear on more than one Volume Folio in the Australian land registration system. A parcel of land is usually associated with a specific Volume Folio, which represents the registered ownership and legal description of that particular property.

Are addresses unique?

In theory, yes, addresses are unique.

However, in reality, no.

Addresses are generally unique, but there are always exceptions. The origin of the address data will influence whether addresses are unique.

A few examples where address uniqueness can pose an issue:

  • Unit addresses, where identifying information like unit numbers have been left off.
  • Rural addresses, where a property does not have a frontage to a public road.
  • Multi-building complexes, where the same unit number appears in multiple buildings and the building names are omitted.

To delve further into this topic, reference our handy article on Useful Websites for Australian Properties, Parcels and Addresses for links to websites to research parcels, volumes and folios, addresses and properties.

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