Location Intelligence

/Location Intelligence
1 07, 2020

Building-level Geocoding of G-NAF (Address Database) for Improved Flood & Bushfire Risk Analysis in Australia

July 1st, 2020|AI, Bushfire, Cloud Computing, Earth Observation, Exposure, Flood, Geocoding, Geospatial Big Data Analytics, Image Analysis, Land parcel, Location Intelligence, Property Information, Risk|

It is well known that exposure location is a major source of uncertainties in either site-level or aggregate risk analysis. Back in 2016, we released a product called Geocoding DoubleCheck (link) to address the location accuracy of parcel-level geocoding. Then we compared the difference between parcel-level and building-level geocoding (Figure 1), and [...]

1 07, 2020

Extracting Features from High-resolution Imagery: An AI-based Processing Service

July 1st, 2020|AI, Cloud Computing, Earth Observation, Exposure, Geocoding, Geospatial Big Data Analytics, Image Analysis, Location Intelligence, Property Information, Risk|

Artificial Intelligence (AI) methods or techniques have been actively explored and used for a long time, but the last decade has seen a surge of very successful and profound applications thanks to the rapid advances in deep convolutional neural networks, the availability of large and high-quality data sources, easy access to high-performance [...]

21 04, 2020

Four Property Location Information Products to Enrich G-NAF (Address Database) in Australia

April 21st, 2020|APIs, Apps, Asset Management, Australia, Elevation, Exposure, Geospatial Big Data Analytics, Insurance, Location Intelligence, Property Information, Real Estate, Risk|

21 April 2020 Geocoded National Address File (G-NAF) is Australia’s authoritative, geocoded address database. It contains more than 14 million physical address records (e.g. residential, commercial and industrial), each having spatially-explicit geocodes such as latitude/longitude coordinates. G-NAF, developed by PSMA Australia, has been available since 2004. A public version, Open G-NAF, has [...]

11 04, 2020

New Web App: Mapping Daily Confirmed COVID-19 Cases in NSW by Postcode and LGA

April 11th, 2020|Apps, Australia, Census, Cloud Computing, Emergency, Exposure, Geospatial Big Data Analytics, Location Intelligence, Major Events, Risk|

11 April 2020 Strongly motivated by the recent release of more detailed COVID-19 data by the New South Wales (NSW) Government, we have developed a new web app that maps the daily confirmed COVID-19 cases in Sydney and NSW by Postcode and Local Government Area (LGA). Please note that so far [...]

11 03, 2020

Top 10 Blogs of the Past Two Years from BigData Earth

March 11th, 2020|APIs, Apps, Australia, Bushfire, Cloud Computing, Emergency, Exposure, Flood, Geospatial Big Data Analytics, Insurance, Location Intelligence, Property Information, Risk, Tropical Cyclone, USA|

11 March 2020 Exactly four years ago, we started blogging what we have been exploring and creating in geospatial big data analytics, cloud computing, property location metrics, hazard and risk modelling, etc. So far, more than 50 blogs have been produced. Here we select and share top 10 blogs from the [...]

9 12, 2019

New Tile Maps on Terrain and Hydrology: Part 3 (Increasing Details)

December 9th, 2019|APIs, Apps, Australia, Emergency, Exposure, Flood, Geospatial Big Data Analytics, Insurance, Location Intelligence, Property Information, Risk|

9 December 2019 LiDAR point clouds can represent 3D features very accurately, but due to their large data sizes, point clouds are commonly turned into easy-to-use DEMs at various spatial resolutions (e.g. 1m, 5m or 10m). Such DEMs are increasingly available via government web portals. The vertical accuracy of 1m-resolution Lidar-derived [...]

9 12, 2019

New Tile Maps on Terrain and Hydrology: Part 2 (Extending Coverage)

December 9th, 2019|APIs, Apps, Australia, Emergency, Exposure, Flood, Geospatial Big Data Analytics, Insurance, Location Intelligence, Property Information, Risk|

9 December 2019 Many of us work with elevation data (e.g. LiDAR point clouds and Digital Elevation Models - DEMs) on a daily basis. Nowadays there are an increasing number of government sources for open elevation data, including high-quality, LiDAR-derived DEMs. As we have recently introduced (link to the previous blog), elevation [...]

18 09, 2019

New Tile Maps on Terrain and Hydrology: Part 1 (Enriching Google Maps)

September 18th, 2019|APIs, Apps, Australia, Emergency, Exposure, Flood, Geospatial Big Data Analytics, Insurance, Location Intelligence, Property Information, Risk|

18 September 2019 Google Maps is very popular and easy to use, and many of us would have imagined creating and delivering domain-specific mapping layers in the same or similar way Google Maps does. To realise this, we have recently created and released a set of new, high-resolution tiled web maps (or [...]

12 08, 2019

New R&D in Property Location and Hazard Risk Analytics: A Transformative Journey from Desktop Computing to Cloud Computing

August 12th, 2019|APIs, Apps, Asia, Australia, Emergency, Exposure, Flood, Geospatial Big Data Analytics, Insurance, Location Intelligence, Property Information, Risk, USA|

12 August 2019 Over the past four years we have been undertaking significant new R&D in property location and hazard risk analytics with cloud computing. In particular, we have developed an organic set of products based on three new technologies (Web APIs, Web Apps and Web Maps) to support two cloud-based [...]

18 06, 2019

Applications of New National Contour Web Maps: Part 3 (Identifying Riverine Flood-prone Areas)

June 18th, 2019|APIs, Apps, Australia, Emergency, Exposure, Flood, Geospatial Big Data Analytics, Insurance, Location Intelligence, Property Information, Risk|

18 June 2019 We keep showcasing the potential application of new high-resolution contour web maps for Australia that have been recently developed (link). Previous blogs in this series include: Applications of New National Contour Web Maps: Part 2 (Identifying Low-lying Coastal Areas) - link Applications of New National Contour Web Maps: [...]