Big Earth Data Enabling Baseline Data Collection in Support of SDG Indicators: the Experience of TERN Landscapes of Australia
Creators: name: Metternicht, Graciela
Publisher: name: UNSW Sydney
Year: 2018

description: The 17 Sustainable Development Goals, with 169 associated targets aspire to integrate in a balanced way the economic, social and environmental dimensions of sustainable development. The goals address a variety of complex problems that emphasise on human-environment interactions –environmental degradation, climate change, sustainable management of natural resources, fresh water scarcity, loss of biodiversity - whose addressing will require cross-sectoral solutions, collaborative work across disciplines, and integration of socio-economic and environmental data and information. Big Earth Data, providing a wide range of long-term time series and multiple spatio-temporal scales covering all of Earth's spheres (ie.g atmosphere, hydrosphere, lithosphere, and biosphere), open windows of opportunity for applications in support of the SDG global indicator framework, including baseline data collection and monitoring of SDG targets’ trends. Opportunities of using Big EO data in support of the implementation of the SDG indicator framework come with some challenges, including data storage and management, data quality and reliability, whether methods are transferable to different geographies and scales, or how the results can be interpreted to produce Voluntary National Review reports that inform the progress towards the implementation of the SDGs. Through the Australia's National Collaborative Research Infrastructure Strategy (NCRIS), since 2010, 12 government and academic institutions have been working cooperatively in the implementation of the Terrestrial Ecosystem Research Network (TERN). One component of this network, the TERN's Landscapes platform, conducts environmental monitoring using remote sensing techniques to characterise and monitor Australian ecosystems at a landscape and continental scale. The platform also undertakes modelling and synthesis activities to extrapolate and interpolate from observational data to produce modelled data products (e.g. land cover vegetation fraction). The TERN Landscape is an example of using Big Earth Observation data to characterise and detect change relating to vegetation structure and composition, land cover underlying forces, and bushfire dynamics and impacts, etcetera. Valuable lessons related to open data access, validation, calibration, inter-institutional cooperation for value added products in support of environmental management have been learned through its implementation. This presentation will discuss key aspects of the formulation, development and implementation of TERN Landscapes, using dense time-series of optical satellite data from the Australian Geoscience Data Cube (AGDC), high resolution MiniSat data, and C- and L-band Synthetic Aperture Radar (SAR; collation of publicly available field, drone and aircraft observations; and the collection of new datasets under common protocols. It will reflect on the opportunities and challenges that national initiatives like TERN Landscapes present for effective operational delivery of value added Big EO in support of the SDGs indicators.
description: The 3rd Digital Belt and Road Conference; Tengchong, China; 2018-12-05 - 2018-12-07