Useful Websites for Australian Properties, Parcels and Addresses

Useful Websites for Australian Properties, Parcels and Addresses

Mar 16, 2025 | Data Domain

Researching whether a property exists or verifying property data can be challenging, often resulting in conflicting answers.

Depending on your definition of a property, it may be necessary to visit various websites to validate property data.

Here we’ve rounded up the top websites handy for verifying property data in each Australian state.

Save time by bookmarking this resource and avoid the hassle of constantly searching online.

Australian Capital Territory (ACT)

Access Canberra

Website: https://actlis.act.gov.au/titleSearch

Available searches: title search, parcel search, address search.

Available information: parcel, title, address, title status

New South Wales (NSW)

NSW LRS Online

Website: https://online.nswlrs.com.au/wps/portal/six/find-records/

Available searches: title search, parcel search, address search.

Available information: parcel, title, address, parcel boundary

ePlanning Spatial Viewer

Website: https://www.planningportal.nsw.gov.au/spatialviewer/#/find-a-property/address

Available searches: parcel search, address search.

Available information: parcel, address, parcel boundary, planning rules, council/county/jurisdiction

Northern Territory (NT)

Northern Territory Title Search

Website: https://www.ntlis.nt.gov.au/title-search/

Available searches: title search, parcel search, address search.

Available information: parcel, title, address, title status

Queensland (QLD)

Queensland Globe

Website: https://qldglobe.information.qld.gov.au/

Available searches: parcel search, address search, spatial search

Available information: parcel, parcel boundary, title, address, title status, tenure

South Australia (SA)

Sailis Land Services SA
Property Research Report (Residential)

Website: https://sailis.lssa.com.au/products/valuationSearch/prr/propertyResearchReportResidential?form

Available searches: address, title, parcel, valuation

Available information: parcel, title, address, valuation status

Tasmania (TAS)

Land Information System Tasmania

Website: https://maps.thelist.tas.gov.au/listmap/app/list/map

Available searches: address, property id, title, volume folio

Available information: parcel, parcel boundary, parcel identifier, address, property

Victoria (VIC)

Landata

Website:
https://www.landata.vic.gov.au/

Available searches: address, property id, standard parcel identifier, volume folio

Available information: address, property , volume folio, standard parcel identifier

Western Australia (WA)

Landgate – Western Australia’s land information authority

Website: https://www0.landgate.wa.gov.au/

Available searches: address search, lot plan, volume folio

Available information: address, volume folio, standard parcel identifier

Originally published: 24 April 2023

Last updated: 17 March 2025

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Understanding Housing Affordability: Key Metrics and Statistics

Understanding Housing Affordability: Key Metrics and Statistics

Mar 11, 2025 | Data Domain, Inference and Analytics

Housing affordability is a significant concern in many parts of the world, affecting the quality of life and economic wellbeing of individuals and families.

Professor Nicole Gurran from the School of Architecture, Design and Planning says governments around the world are searching for solutions to fix housing affordability, with two opposing schools of thought seeing the solutions as:

  1. Increasing supply. Those in support of this point of view see housing as more expensive because there’s not enough new supply. They see land use regulation and planning processes as restrictive to new construction, adding costly delays and uncertainty to the development process.
  2. On the flipside, others argue that ‘demand side’ factors underlying global house price inflation, such as low cost credit under financial deregulation, or government incentives to encourage property investment are being ignored. They highlight the political influence of property industry groups sustaining housing demand while advocating for reduced regulations. Some even suggest that extensive rezoning reforms may trigger surges in redevelopment and gentrification, potentially displacing individuals with lower incomes.

To truly understand the dynamics of housing affordability we need to take a detailed look at a range of different metrics and statistics to gain a full picture.

Shedding light on these crucial measures can offer insights for homebuyers, policymakers, real estate professionals, and urban planners.

1. Median and Average Home Prices

These figures provide a baseline for understanding the cost of purchasing a home in a particular area.

The median home price provides a middle point and the average home price presents an overall trend.

2. Price-to-Income Ratio

This critical ratio compares home prices to average household incomes. A higher ratio suggests that homes are less affordable relative to income.

Statista has published the the house price-to-income ratio in Australia as 122.1 as of the third quarter of 2024. This ratio is calculated by dividing nominal house prices by nominal disposable income per head and has increased from the previous quarter.

3. Housing Affordability Measures

A Housing Affordability Index (HAI) assesses whether a typical family can afford the mortgage on a median-priced home, based on their income. An index above 100 indicates greater affordability.

The issue with the HAI is that it primarily focuses on purchase affordability.

The Australian Institute of Health and Welfare (AIHW) broadens what they classify as housing costs in measuring housing affordability.

AIHW defines housing costs as “the sum of rent payments, rate payments (water and general), and housing–related mortgage payments”,

AIHW expresses housing affordability as “the ratio of housing costs to gross household income”,

While housing stress is typically described as “lower-income households that spend more than 30% of gross income on housing costs“.

The second measure is a more comprehensive approach which considers a range of housing costs, the complexity of housing affordability and its impact on households.

4. Rent-to-Income Ratio

Rent-to-Income Ratio compares a tenant’s monthly rent to their gross monthly income expressed as a ratio. For those in the rental market, this ratio measures how much of a household’s income is spent on rent, with higher values indicating less affordability.

PropTrack classifies unaffordable rental housing as a household spending more than a quarter of their pre-tax income on rent. PropTrack recently released its 2025 Rental Affordability Report, and renters are facing the toughest conditions seen in Australia.

Rental property

5. Mortgage Interest Rates

Interest rates directly affect the cost of borrowing money for home purchases.

An increase in mortgage interest rates typically mean an increase in mortgage repayments, which can negatively impact affordability.

While a reduction in rates typically means reduced mortgage repayments, which may improve affordability.

6. Mortgage Payment as a Percentage of Income

Mortgage payment as a percentage of income is an important measure of affordability by demonstrating the burden of mortgage payments relative to a household’s income.

This percentage is calculated by dividing monthly mortgage repayments by gross monthly wages. 

The recommended figure is 28% of pre-tax income. Or in other words, no more than 28% of gross monthly income should go towards monthly mortgage repayments.

7. Homeownership Rates

Broad changes in homeownership rates can signal shifts in affordability, and the overall health of the housing market. 

To gain an idea of homeownership rates in Australia, AIHW shares a view of Home ownership and housing tenure in Australia.

8. Cost of Living

Several measures are published to calculate and help gauge changes in the cost of living. Changes in cost of living impacts our household purchasing power and has implications for housing demand. 

The main ways we measure cost of living is the Consumer Price Index.

Consumer Price Index (CPI)

According to the Australian Bureau of Statistics, CPI is a measure of the average change over time in the prices paid by households for a fixed basket of goods and services (which is grouped into 11 categories: Food and non-alcoholic beverages, Alcohol and tobacco, Clothing and footwear, Housing, Furnishings, household equipment and services, Health, Transport, Communication, Recreation and culture, Education, and Insurance and financial services).

 It’s important to note that the calculation of CPI does not include the cost of buying established dwellings, nor mortgage repayments. However, it does include rents, the cost of new dwellings (excluding value of land) and major alterations and additions to dwellings. 

Included in CPI

Not included in CPI

  • Rent
  • Cost of new dwellings (excluding value of land)
  • Major alterations and additions to dwellings
  • Rates and charges
  • Utilities
  • The cost of buying established dwellings
  • The cost of purchasing land
  • Mortgage repayments
  • Costs associated with servicing a mortgage
Consumer Price Index

9. Gini Coefficient of Home Prices

The Gini Coefficient statistical measure is typically used as a measure of income inequality, although it can be used to assess inequality in various other contexts, including home values in a real estate market.

A Gini index of 0 represents perfect equality, while an index of 100 implies perfect inequality.

This measure can indicate the inequality in home values within a market, with higher values suggesting greater disparity.

10. Building Permits and Housing Starts

Building permits and housing starts are indicators of building activity and housing supply.  They can signal future market changes which may impact affordability.

The Proptech Cloud publishes ready-to-use Construction Activity data from the Australian Bureau of Statistics on the Snowflake Marketplace.

11. Vacancy Rates

A vacancy rate is a measure of the percentage of all rental properties that are currently vacant and available for rent.

Fluctuations in vacancy rates can impact rental prices, as elevated rates often correlate with decreased rents, and conversely, lower vacancy rates may lead to higher rental prices. 

12. Debt-to-Income Ratio

An individual’s Debt-to-Income Ratio is calculated by taking their total monthly debt and dividing it by their monthly income.

This ratio reflects a person’s capacity to afford housing in light of their existing debts.

14. Population Growth and Urbanisation

Rapid population growth or accelerated urbanisation can significantly drive up housing demand, often outpacing the supply of available homes. This increased competition for housing can lead to rising property prices and rental costs, making affordability a growing concern, particularly in high-demand urban centres.

Additionally, infrastructure, public services and planning regulations may struggle to keep pace with rapid expansion, further exacerbating affordability challenges. Understanding these dynamics is crucial for policymakers, developers, and investors looking to create sustainable housing solutions..

A Multifaceted View of Housing Affordability

This diverse set of metrics can collectively provide a comprehensive perspective on housing affordability by capturing the various factors that influence pricing while revealing the complexities of the housing market.

These indicators are vital for informed decision-making, policy development and market analysis.

Regularly tracking these metrics allow stakeholders to spot emerging trends, assess market stability and make data-driven decisions.

For those navigating the housing sector, staying informed on these indicators can allow them to anticipate shifts, mitigate risks and capitalise on opportunities in dynamic market.

 

 

Originally published: 18 January, 2024

Last updated: 11 March, 2025

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What’s the Difference Between GDA94 and GDA2020?

What’s the Difference Between GDA94 and GDA2020?

Feb 11, 2025 | Data Domain

Geodetic datums, or geodetic systems, are often used by proptechs for mapping  or analysing spatial data.

Here is a rundown of everything you need to know about the different geodetic datums we use and reference in Australia.

Table of Contents

Jump ahead ↓

What is a Geodetic Datum?

A geodetic datum is a reference framework used to define the Earth’s shape and orientation, providing a coordinate system that allows for accurate mapping, surveying, and pinpointing exact locations on the Earth’s surface.

In Australia, we use Geodetic Datum of Australia 1994 (DA94) and Geodetic Datum of Australia 2020 (GDA2020).

The 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. And 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, selecting the correct geodetic datum is important 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.

Geodetic Datum Usage in Australia

In Australia, a lot of data providers offer data sets in both GDA94 and GDA2020 geodetic datums because the uptake of GDA2020 is not universal. It’s common practice for these providers to specify which datum was used to create each dataset.

When combining geospatial datasets, it’s important for data professionals to ensure consistency in the geodetic datums employed.

Using different datums without proper alignment can lead to inaccuracies, such as misaligning spatial features. For this reason, careful attention to datum consistency is essential to maintain the integrity and accuracy of integrated geospatial data.

 

Originally published: 5 August, 2023

Last updated: 11 February, 2025

 

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Alternative Data: What Is It, Who Uses It And Why It Matters

Alternative Data: What Is It, Who Uses It And Why It Matters

Dec 12, 2024 | Data Domain

Often in business, staying ahead means looking beyond the obvious.

Alternative data, derived from non-traditional sources, offers a depth and uniqueness that traditional data sources can lack.

In this blog, we’ll cover what alternative data is, how it differs from traditional data, who uses it, its role in business, and the pros and cons of integrating it into decision-making.

Table of Contents

Jump ahead ↓

What Is Alternative Data?

Alternative data (or Alt data) refers to non-traditional data sources that provide unique insights and information not typically captured by conventional data sets. The depth, detail, variety and uniqueness of alternative data are what make it such a powerful form of intel.

Examples include:

  • Social media sentiment analysis
  • Geolocation data tracking foot traffic
  • Credit card transaction volumes
  • Satellite imagery
  • Drone imagery
  • Wearable tech data
  • Web traffic data
  • Mobile app usage statistics
  • IoT sensor data
  • Product reviews
  • Weather data
  • Flight data
  • App usage
  • ESG (environmental, social and corporate governance) data
  • Market prices
  • Company filings
  • Jet tracking

Alternative data is far from a new concept. For centuries, astute business people have sought to understand their trading environments by observing the world through different lenses. These observations often generated insights—data that, while not traditional, provided a valuable edge in navigating markets effectively.

What has changed in recent years is the remarkable accessibility of alternative data, driven by technological advancements across industries. This progress has expanded the volume and variety of data, making it easier for businesses to derive insights and make more informed decisions.

Source: Casting the Net

What is the Difference Between Alternative and Traditional Data?

Traditional data comes from established, conventional sources like financial statements, government reports and structured databases. It is typically well-organised and standardised.

Alternative data comes from unconventional, non-traditional sources. It is often unstructured or semi-structured, and thus less readily accessible or usable, and not easily searchable.

It generally requires advanced processing techniques, substantial computational power and storage, as well as the ability to link seemingly unrelated pieces of information to develop a holistic understanding or derive meaningful insights.

Who Uses Alternative Data?

Alternative data is often used by hedge funds, private equity firms, investment banks and retail investors to gain insights and identify opportunities beyond traditional data sources.

It is commonly used to:

  • Uncover potential risks not evident from traditional financial data.
  • Conduct stress tests and scenario analyses.
  • Identify and manage tail risks.
  • Discover new investment opportunities.
  • Reduce information asymmetry.
  • Optimise portfolio construction.

Other specific examples include:

  • Environmental, Social and Governance (ESG)
    Alternative data like social media sentiment and news can be used to assess companies’ environmental, social, and governance (ESG) performance which can help investors incorporate ESG factors into decision-making.
  • Fintech
    Alternative data can also be used by fintech firms to offer tailored financial advice, identify potential customers and develop innovative investment products accessible to retail investors.

Pros & Cons of Using Alternative Data

Pros

By using unconventional insights, businesses and investors can uncover opportunities and sharpen their strategies using alternative data. Here’s how it can help deliver an edge:

More Detailed and Accurate Analysis

Alt data provides additional data points of a business’s performance beyond traditional sources. When analysed holistically, it can potentially offer a more complete understanding of business performance and customer loyalty.

Decisions Backed by Historical Trends

The access to historical data enables predictive analysis, helping anticipate outcomes, identify opportunities and avoid potential risks.

Improved Investments and Partnerships

A broader range of data points allows businesses to assess compatibility with potential partners and make more strategic, mutually beneficial investment decisions.

Enhanced Customer Relationships

Data on customer feedback, web traffic and audience demographics helps businesses refine strategies to improve customer satisfaction and loyalty.

Competitive Advantage

Real-time insights allow quicker, informed decisions, helping businesses stay ahead of competitors reliant on traditional data.

Cons

While alternative data offers exciting possibilities, it’s not without its hurdles. Effectively leveraging these unconventional insights requires addressing some critical challenges. Here are the key drawbacks businesses might consider:

Inconsistent Data Quality

Due to the wide variety and the varied applications, alt data is hard to regulate. It can come aggregated or as a straight data feed. The lack of standardisation and rules around alt data means these types of data sets may contain errors, which can lead to misinterpretations which, in turn, affects decision-making.

Transparency and Ethical Concerns

Data collection methods, such as tracking GPS or online activity, may erode consumer trust if it is seen as invasive or unethical.

Privacy and Security Risks

Sensitive data usage exposes businesses to breaches, legal violations and potential harm to individuals. This can pose serious risks to a brand’s reputation and business compliance.

Discrimination and Bias Risks

Using personal demographics in decision-making can lead to unintentional discrimination, flawed data sets and long-term reputational damage.

Manipulated Data Variables

Publicly available data can sometimes be intentionally skewed to serve specific interests—businesses might highlight only positive reviews, while individuals may curate information to boost their credibility. This highlights the importance of adopting a comprehensive approach, drawing from a diverse range of data channels rather than relying on a single source.

The True Value of Alternative Data

Alternative or alt data offers deeper insights, empowering businesses and investors to make more informed decisions and gain a competitive edge.

As accessibility to alt data continues to grow, so do the opportunities to harness its potential in creative and transformative ways.

But challenges like data quality, transparency and privacy means that alt data requires careful management.

By adopting a thoughtful and ethical approach, progressive businesses can tap into alt data’s inherent value to inspire smarter investments, spark innovations and deliver groundbreaking solutions.

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What Is A Geohash And How Is It Used?

What Is A Geohash And How Is It Used?

Nov 25, 2024 | Data Domain

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

Table of Contents

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What Is A Geohash?

Geohashing is a geocoding system created in 2008 that encodes geographic coordinates (latitude and longitude) into a short and compact string of characters made up of letters and numbers. The resulting compact string of characters is a Geohash.

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.

For example, the coordinates “latitude 40.7128 degrees North and longitude 74.0060 degrees West” is the same as geohash “6gkzwgjz.” – this shorter code pinpoints the same location 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.

Breaking Down Geohash – How the World is Encoded into Precise Rectangles

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:
    – A Geohash of length 1 represents a large area, such as a continent.

    – A Geohash of length 2 represents a smaller area, such as a country.
    – A Geohash of length 3 represents a region or large city.
    – A Geohash of length 4 represents a smaller city or town.
    – Geohashes of length 5 or higher represent progressively smaller areas, down to street level and even specific locations.

  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

Source: Geohash Explorer

Use Cases of Geohash

Geohash is widely used for its simplicity and efficiency in spatial indexing, making it useful for a wide range of practical applications across industries.

  • 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, security applications, social networking and even dating apps.
  • 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.
  • Digital adventures
    Users can connect with people and discover new destinations worldwide via apps which leverage geohashes to enhance travel journaling and social interactions, making global adventures more interactive and engaging.

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.

How Does Geohash Compare With Other Spatial Encoding Systems?

A geohash is one of many spatial encoding systems designed to represent geographic locations compactly and efficiently. Geohash can be substituted with alternative systems depending on the specific requirements of the application.

Each spatial encoding system is tailored to address particular needs, offering unique features and trade-offs that make some systems more suitable for specific use cases. For example, geohashes excel in simplicity and spatial indexing, while systems like H3 or Plus Codes may provide advantages in precision, scalability, or user-friendliness.

Read our blog which compares Geohash with H3>

Originally published: 26 September, 2023

Last updated: 26 November, 2024

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What Is A Cadastre?

What Is A Cadastre?

Nov 18, 2024 | Data Domain

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

Cadastre At A Glance (TL;DR)

A cadastre is an official record of land ownership, boundaries and value, crucial for property management, taxation and legal clarity.

Traditional cadastral systems relied on paper maps and manual record-keeping, whereas modern cadastres keep property data accurate, interactive and accessible.

Cadastres are often created and managed with technologies like Geographic Information System (GIS) which capture, store, analyse and visualise spatial or geographic data.

Around the world, innovations like 3D cadastres and digital platforms are enhancing how we manage, visualise and understand land data.

Table of Contents

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What Is A Cadastre?

A cadastre is a detailed register or database that holds information about land or property within a specific area. Each record in the cadastre defines the boundaries of a property, as mapped by land surveys. It also includes important details like the property’s location, features, and value.

A cadastre is an essential tool for managing and regulating land ownership and use. It helps with collecting property taxes, assessing land values, and resolving property disputes. It usually includes property boundaries, ownership details, and physical descriptions like size, shape, and terrain. It may also contain information on land use, zoning rules, building permits and environmental regulations.

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

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 provide access to the cadastre and offer related services to the public, including title searches, property reports, and other land-related information.

What File Types Are Used To Store Cadastres?

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 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.

Who Provides Cadastres On The Snowflake Marketplace?

Here are a few providers of cadastres on the Snowflake Marketplace:

  • The Proptech Cloud
  • Geoscape
  • Precisely

How Are Cadastres Used?

Cadastres play a pivotal role in linking spatial data to real-world applications.

In the context of the built environment, cadastres serve a number of purposes, such as:

  • 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.

  • Assess property risks, develop climate change adaption strategies, evacuation routes and emergency responses.

  • Effective land use planning to guide urban development and expansion, the management of rural land resources and supporting environmental protection initiatives.

  • Planning and managing infrastructure projects, including tility networks.

The Future of Cadastres

Around the world, countries are adopting 3D cadastres to better capture the complexity of modern property landscapes.

For example, a collaborative project between Russia and the Netherlands explores how 3D models can improve the recording of rights associated with multi-level buildings, complex structures, and underground networks, such as gas pipelines.

The Netherlands has also developed 3D cadastre solutions to address the limitations of 2D cadastral maps in representing complex spatial property arrangements.

In Australia, the Australian CADASTRE 2034 strategy aims to create a fully digital, interoperable cadastre that can support various applications beyond traditional land administration.

As technology advances, so too does our ability to understand and shape the spaces in which we live and grow.

These advancements are an inspiring shift toward a future where cadastres will play a bigger role in urban planning, environmental management, and beyond.

Originally published: 25 September, 2023

Last updated: 19 November, 2024

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