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个人简介
Chris's work focuses on leading production of geospatial datasets using open source methods, with a particular emphasis on the classification of building use via machine learning. These datasets are in essence digital maps that offer a range of geographical information (i.e. buildings, lights at night, accessibility, landcover, climatic, etc.) and act as essential inputs to population modelling. Building classification datasets additionally directly inform development policy in the context of urban planning, resource allocation, and service delivery. His role involves advising re. the production and analysis of geospatial data (with project partners as well as within the WorldPop team) as required in multiple research and implementation projects. Chris also produces written training materials targeted at external GIS professionals, and co-supervises PhD research.
Research interests
GIS and Remote Sensing
Open Source Geospatial Tools
Building Classification using Machine Learning
Spatial Demography
Glacial Geomorphology and Geology
研究兴趣
论文共 48 篇作者统计合作学者相似作者
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SOCIAL COHESION AND WELFARE STATES: From Fragmentation to Social Peacepp.1-5, (2022)
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Social Cohesion and Welfare Statespp.6-27, (2022)
SOCIAL COHESION AND WELFARE STATES: From Fragmentation to Social Peacepp.6-27, (2022)
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The Journal of American Cultureno. 2 (2021): 156-157
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