Digital Earth for a Physical World – Geospatial Big Data Sources

Open Data in the Public Domain

A vast amount of open geospatial data, predominantly released by the government, is already in the public domain. Often they are scattered, and for their effective integration into applications a critical examination is needed.

Commercial & Proprietary Data

Terabytes and petabytes of frequently captured geospatial data (e.g. high-resolution satellite imagery, aerial photos and LiDAR point clouds) need to be processed in a highly efficient manner for feature extraction. We are able to assist.

Emerging Location Data

New location data (especially those from ubiquitous mobile/smart devices) have been generated and collected at an unprecedented rate. This not only demands new thinking and new treatment but also promises new applications.

Where is the Smart Data Everyone Needs?

How much information can we extract from the data? How can we turn the Geospatial Big Data into smart location insights? Ultimately, the value of the data should be easily appreciated with common sense, not the Big Data hype!

Main Data Sources We Analyse

Digital Satellite and Aerial Imagery at All Spatial Resolutions

Low- to medium-resolution satellite imagery (e.g. JMA Himawari 8/9, NOAA GOES 16/17, NASA/USGS MODIS and Landsat, Copernicus/ESA Sentinel)
Medium- to high-resolution satellite imagery (e.g. 5m-resolution RapidEye, 1.5m-resolution SPOT 6/7)
High-resolution satellite imagery (e.g. 30cm-resolution WorldView-3, 50cm-resolution Pléiades)
Very high-resolution digital aerial imagery (e.g. 10cm resolution), including those captured by the new-generation drones/UAV/UAS

Digital Elevation Model and LiDAR Point Clouds

Medium-resolution DEMs for a near-global coverage (e.g. NASA/USGS 90m- and 30m-resolution SRTM)
Medium- to high-resolution elevation mosaic at the country level (e.g. 10m-resolution)
High-resolution DEMs derived from satellite stereo pairs (e.g. 2m-resolution from WorldView-2)
LiDAR point clouds, photogrammetric point clouds, including those from the recent drones/UAV/UAS captures

1997 - 2015 EL NINO comparison animation

El Niño: 1997 vs. 2015 (Source: NASA JPL)

Climate and Weather

Historical weather records across monitoring stations (e.g. usually from national meteorological agencies)
Historical climate grids (e.g. typically derived from the time series of weather records)
Climate cycles data (e.g. ENSO, Atlantic Multidecadal Oscillation – AMO, the Indian Ocean Dipole – IOD) and global/regional climate change forecast
Data from the new generation of meteorological satellites (e.g. JMA Himawari-8 imagery with a high revisit frequency of minutes)

2012 Hurricane Sandy (Source: NASA EO, NASA LANCE)

Natural Hazards

Near real-time monitoring and modelled data for tectonic and geologic hazards (e.g. earthquake and tsunami)
Near real-time monitoring and modelled data for meteorological hazards (e.g. flood and cyclone)
Near real-time social media communication data in response to major disasters worldwide
Fresh Earth observation data in response to major disasters worldwide

Google Street, Street View, Google Earth, Land Parcel, Features of Interest

Source: Google Maps

Street, Address, Land Parcel and Property Location

Street networks
Physical addresses and locations for residential, commercial and industrial assets
Cadastre and land parcels
Building footprints

LandScan - global population data at 1km resolution

LandScan global population distribution (Source: ORNL)

Infrastructure, Population, Dwellings and other Census Stats

Infrastructure (e.g. roads, railways, telecommunications, energy, utilities and drainage)
Population, dwellings and other socioeconomic attributes from national census
Hierarchical spatial digital boundaries used by national census
Modelled ambient population distributions for lager areas

Others

Land cover, land use
Environmental pollution (e.g. air, water and soil)
Business data (e.g. insurance portfolio and claims)
Traffic flows
…