The potential to produce official statistics derived from Earth observation data is now gaining interest within national statistical offices around the world. The Australian Bureau of Statistics (ABS) is currently working with Geoscience Australia (GA) to demonstrate the value of "analysis-ready" data for this purpose. Through collaboration with GA the ABS has been able to access composite data of Fractional Cover for specific reference periods, which were created using the Australian Geoscience Data Cube (AGDC). Statistical summaries of Fractional Cover are being prepared for regions defined in the Australian Statistical Geography Standard (ASGS). The use of the ASGS provides an opportunity to integrate these summaries with other environmental and socio-economic statistics, thereby enabling new insights into relationships between these variables and the condition of the land. Results of this work will be featured in an upcoming ABS environment-economic publication. This work represents the first step in a broader collaboration between ABS and GA to leverage time-series Earth observations from the AGDC to produce official statistics for Australia.

The rise of the new middle classes with distinct cultural aesthetics and consumption patterns, combined with new urban governance regimes that have channelled capital flows into central suburbs, have helped to refashion the physical and socio-demographic character of inner-city areas. Within urban policy circuits it is argued that these trends mark a significant moment in the remaking of the city and contain the promise of a new urban cosmopolitanism. In contrast, the gentrification literature points to the continued power of displacement within the city. In this paper we revisit Ponsonby, a suburb long noted as a site of gentrification, and examine the role of house prices (from 1986-2015) in the construction of a high status residential area. In particular, we chart the on-going nature of ethnic displacement at work in Ponsonby.

In this study, we performed a global analysis of nighttime lights of all densely populated areas (n = 4,153) , using the new VIIRS sensor onboard the Suomi NPP satellite in January 2014 and in July 2014, to uncover the factors controlling cities' night-time brightness. We found that in addition to GDP per capita, the nighttime brightness of densely populated areas was positively correlated with MODIS derived percent urban area (0.46 < Rs < 0.60), the density of the road network (0.51 < Rs < 0.67), and with latitude (0.31 < Rs < 0.42) at p < 0.001. NDVI values (representing vegetation cover) were found to be negatively correlated with cities’ brightness in winter time (-0.48 < Rs < -0.22), whereas snow cover (enhancing artificial light reflectance) was found to be positively correlated with cities’ brightness in winter time (0.17 < Rs < 0.35). Overall, the generalized linear model we built was able to explain more than 45% of the variability in cities’ nighttime brightness, when both physical and socio-economic variables were included. Explaining cities’ nighttime brightness is therefore affected not only by country level factors (such as GDP), but also by the built environment and by climatic factors.

The Australian Bureau of Statistics (ABS) is undergoing a transformation to enable it to produce statistical solutions using new methods.
One response to this has been the development of Geostatistics: statistics created using geospatial data and analysis.
This approach to creating statistical data is exciting because it creates new measures to understand complex problems that aren’t possible using traditional statistical methods. It is also exciting because it does this in a way that adds value to existing data relatively quickly.
This approach is particularly applicable to understanding the built environment and the ABS has produced a number of datasets including measures of accessibility to public green space and measures of changes in house and block sizes among others. Work is also being undertaken to add a measure of commuting distance to the Census data.
Within the ABS this work is relatively new and consideration needs to be given to how governments, academics and commercial organisations can work together to create Geostatistics that allow us to better understand how our urban environments are changing, how they compare with each other and what this means for the people and businesses that operate within them.