The Great Barrier Reef Marine Park, an area almost the size of Japan, has a new network of no-take areas that significantly improves the protection of biodiversity. The new marine park zoning implements, in a quantitative manner, many of the theoretical design principles discussed in the literature. For example, the new network of no-take areas has at least 20% protection per "bioregion," minimum levels of protection for all known habitats and special or unique features, and minimum sizes for no-take areas of at least 10 or 20 km across at the smallest diameter. Overall, more than 33% of the Great Barrier Reef Marine Park is now in no-take areas (previously 4.5%). The steps taken leading to this outcome were to clarify to the interested public why the existing level of protection was inadequate; detail the conservation objectives of establishing new notake areas; work with relevant and independent experts to define, and contribute to, the best scientific process to deliver on the objectives; describe the biodiversity (e.g., map bioregions); define operational principles needed to achieve the objectives; invite community input on all of the above; gather and layer the data gathered in round-table discussions; report the degree of achievement of principles for various options of no-take areas; and determine how to address negative impacts. Some of the key success factors in this case have global relevance and include focusing initial communication on the problem to be addressed; applying * email leannef@gbrmpa.gov.au the precautionary principle; using independent experts; facilitating input to decision making; conducting extensive and participatory consultation; having an existing marine park that encompassed much of the ecosystem; having legislative power under federal law; developing high-level support; ensuring agency priority and ownership; and being able to address the issue of displaced fishers.Key Words: biophysical operational principles, cultural operational principles, economic operational principles, reserve-design software, social operational principles Establecimiento deÁreas sin Captura Representativas en la Gran Barrera Arrecifal: Implementación a Gran Escala de la Teoría sobreÁreas Marinas Protegidas Resumen: El Parque Marino Gran Barrera Arrecifal, con una superficie casi del tamaño de Japón, tiene una red deáreas sin captura que incrementa la protección de la biodiversidad significativamente. La nueva zonificación en el parque marino implementa, de manera cuantitativa, muchos de los principios teóricos de diseño discutidos en la literatura. Por ejemplo, la nueva red deáreas sin captura tiene niveles mínimos de protección de por lo menos 20% de protección por "bioregión" en todos los hábitats y rasgos especiales oúnicos conocidos, y tamaños mínimos para lasáreas sin captura de por lo menos 10 o 20 km en el diámetro menor. En general, más de 33% del Parque Marino Gran Barrera Arrecifal está enáreas sin captura (4.5% anteriormente). Los pasos hacia este resultado fueron clarificar al público interesa...

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The effort and cost required to convert satellite Earth Observation (EO) data into meaningful geophysical variables has prevented the systematic analysis of all available observations. To overcome these problems, we utilise an integrated High Performance Computing and Data environment to rapidly process, restructure and analyse the Australian Landsat data archive. In this approach, the EO data are assigned to a common grid framework that spans the full geospatial and temporal extent of the observations -the EO Data Cube. This approach is pixel-based and incorporates geometric and spectral calibration and quality assurance of each Earth surface reflectance measurement. We demonstrate the utility of the approach with rapid time-series mapping of surface water across the entire Australian continent using 27 years of continuous, 25 m resolution observations. Our preliminary analysis of the Landsat archive shows how the EO Data Cube can effectively liberate high-resolution EO data from their complex sensor-specific data structures and revolutionise our ability to measure environmental change.ARTICLE HISTORY

Petascale archives of Earth observations from space (EOS) have the potential to characterise water resources at continental scales. For this data to be useful, it needs to be organised, converted from individual scenes as acquired by multiple sensors, converted into "analysis ready data", and made available through high performance computing platforms. Moreover, converting this data into insights requires integration of non-EOS data-sets that can provide biophysical and climatic context for EOS. Digital Earth Australia has demonstrated its ability to link EOS to rainfall and stream gauge data to provide insight into surface water dynamics during the hydrological extremes of flood and drought. This information is supporting the characterisation of groundwater resources across Australia's north and could potentially be used to gain an understanding of the vulnerability of transport infrastructure to floods in remote, sparsely gauged regions of northern and central Australia.

Combining data from multiple sensors into a single seamless time series, also known as data interoperability, has the potential for unlocking new understanding of how the Earth functions as a system. However, our ability to produce these advanced data sets is hampered by the differences in design and function of the various optical remote-sensing satellite systems. A key factor is the impact that calibration of these instruments has on data interoperability. To address this issue, a workshop with a panel of experts was convened in conjunction with the Pecora 20 conference to focus on data interoperability between Landsat and the Sentinel 2 sensors. Four major areas of recommendation were the outcome of the workshop. The first was to improve communications between satellite agencies and the remote-sensing community. The second was to adopt a collections-based approach to processing the data. As expected, a third recommendation was to improve calibration methodologies in several specific areas. Lastly, and the most ambitious of the four, was to develop a comprehensive process for validating surface reflectance products produced from the data sets. Collectively, these recommendations have significant potential for improving satellite sensor calibration in a focused manner that can directly catalyze efforts to develop data that are closer to being seamlessly interoperable.

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