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| 1 | Variability in vitamin D assays impairs clinical assessment of vitamin D status显示文摘 | J. K. C.Lai R. M.Lucas E.Banks A.‐L.Ponsonby | 2012 | Internal Medicine Journal2012，，1： | 1 |
| 2 | Computational Intelligence and Games:Challenges and Opportunities显示文摘The last few decades have seen a phenomenal increase in the quality,diversity and pervasiveness of computer games.The worldwide computer games market is estimated to be worth around USD 21bn annually,and is predicted to continue to grow rapidly. This paper reviews some of the recent developments in applying computational intelligence(CI)methods to games,points out some of the potential pitfalls,and suggests some fruitful directions for future research. | Simon M.Lucas | 2008 | International Journal of Automation and computing2008，5，1： | 1 |
| 3 | Phadiatop<sup>TM</sup> compared to skin‐prick test as a tool for diagnosing atopy in epidemiological studies in schoolchildren显示文摘 | LuisGarcia‐Marcos ManuelSanchez‐Solis Antonia E.Martinez‐Torres Jose M.Lucas Moreno Vicente HernandoSastre | 2007 | Pediatric Allergy and Immunology2007，，3： | 1 |
| 4 | Operational continental-scale land cover mapping of Australia using the Open Data Cube显示文摘To comprehensively support national and international initiatives for sustainable development,land cover products need to be reliably and routinely generated within operational frameworks.Coupled with consistent semantics and taxonomies,ensuring confidence in mapping land cover for multiple time periods,facilitates informed decision-making at scales appropriate to multiple policy domains.The United Nations Food and Agriculture Organisation(FAO)Land Cover Classification System(LCCS)provides a taxonomy that comparable at different scales,level of detail and geographic location.The Open Data Cube(ODC)initiative offers a framework for operational continental-scale land cover mapping using analysis-ready Earth Observation data.This study utilised the FAO LCCS framework and the Landsat sensor data through Digital Earth Australia(DEA;Australia’s ODC instance)to generate consistent and continent-wide land cover mapping(DEA Land Cover)of the Australian continent.DEA Land Cover provides annual maps from 1988 to 2020 at 25 m resolution.Output maps were validated with∼12,000 independent validation points,giving an overall map accuracy of 80%.DEA Land Cover provides Australia with a nationally consistent picture of land cover,with an open-source software package using readily available global coverage data and demonstrates a pathway of adoption for national implementations across the world. | Christopher J.Owers Richard M.Lucas Daniel Clewley Belle Tissott Sean M.T.Chua Gabrielle Hunt Norman Mueller Carole Planque Suvarna M.Punalekar Pete Bunting Peter Tan Graciela Metternicht | 2022 | International Journal of Digital Earth2022，15，1： | 1 |
| 5 | Living Earth:Implementing national standardised land cover classification systems for Earth Observation in support of sustainable development显示文摘Earth Observation(EO)has been recognised as a key data source for supporting the United Nations Sustainable Development Goals(SDGs).Advances in data availability and analytical capabilities have provided a wide range of users access to global coverage analysis-ready data(ARD).However,ARD does not provide the information required by national agencies tasked with coordinating the implementation of SDGs.Reliable,standardised,scalable mapping of land cover and its change over time and space facilitates informed deci-sion making,providing cohesive methods for target setting and reporting of SDGs.The aim of this study was to implement a global framework for classifying land cover.The Food and Agriculture Organisation’s Land Cover Classification System(FAO LCCS)provides a global land cover taxonomy suitable to comprehensively support SDG target setting and reporting.We present a fully implemented FAO LCCS optimised for EO data;Living Earth,an open-source software package that can be readily applied using existing national EO infrastructure and satellite data.We resolve several semantic challenges of LCCS for consistent EO implementation,including modifications to environmental descriptors,inter-dependency within the mod-ular-hierarchical framework,and increased flexibility associated with limited data availability.To ensure easy adoption of Living Earth for SDG reporting,we identified key environmental descriptors to provide resource allocation recommendations for generating routinely retrieved input parameters.Living Earth provides an optimal platform for global adoption of EO4SDGs ensuring a transparent methodology that allows monitoring to be standardised for all countries. | Christopher J.Owers Richard M.Lucas Daniel Clewley Carole Planque Suvarna Punalekar Belle Tissott Sean M.T.Chua Pete Bunting Norman Mueller Graciela Metternicht | 2021 | Big Earth Data2021，5，3： | 1 |
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